yangxue0827 / fpn_tensorflow Goto Github PK

A Tensorflow implementation of FPN detection framework.

Python 100.00%

fpn tensorflow detection resnet

fpn_tensorflow's Introduction

Feature Pyramid Networks for Object Detection

Recommend an improved version of FPN： https://github.com/DetectionTeamUCAS

A Tensorflow implementation of FPN detection framework.
You can refer to the paper Feature Pyramid Networks for Object Detection
Rotation detection method baesd on FPN reference R2CNN, RRPN and R2CNN_HEAD and R-DFPN
If useful to you, please star to support my work. Thanks.

Configuration Environment

ubuntu(Encoding problems may occur on windows) + python2 + tensorflow1.2 + cv2 + cuda8.0 + GeForce GTX 1080
You can also use docker environment, command: docker pull yangxue2docker/tensorflow3_gpu_cv2_sshd:v1.0

Installation

Clone the repository

git clone https://github.com/yangxue0827/FPN_Tensorflow.git

Make tfrecord

The data is VOC format, reference here
data path format ($FPN_ROOT/data/io/divide_data.py)

├── VOCdevkit
│   ├── VOCdevkit_train
│       ├── Annotation
│       ├── JPEGImages
│    ├── VOCdevkit_test
│       ├── Annotation
│       ├── JPEGImages

cd $FPN_ROOT/data/io/  
python convert_data_to_tfrecord.py --VOC_dir='***/VOCdevkit/VOCdevkit_train/' --save_name='train' --img_format='.jpg' --dataset='ship'

Demo

1、Unzip the weight $FPN_ROOT/output/res101_trained_weights/*.rar
2、put images in $FPN_ROOT/tools/inference_image
3、Configure parameters in $FPN_ROOT/libs/configs/cfgs.py and modify the project's root directory 4、image slice

cd $FPN_ROOT/tools
python inference.py

5、big image

cd $FPN_ROOT/tools
python demo.py --src_folder=.\demo_src --des_folder=.\demo_des

Train

1、Modify $FPN_ROOT/libs/lable_name_dict/***_dict.py, corresponding to the number of categories in the configuration file
2、download pretrain weight(resnet_v1_101_2016_08_28.tar.gz or resnet_v1_50_2016_08_28.tar.gz) from here, then extract to folder $FPN_ROOT/data/pretrained_weights
3、

cd $FPN_ROOT/tools
python train.py

Test tfrecord

cd $FPN_ROOT/tools    
python $FPN_ROOT/tools/test.py

eval(Not recommended, Please refer here)

cd $FPN_ROOT/tools   
python ship_eval.py

Summary

tensorboard --logdir=$FPN_ROOT/output/res101_summary/

Graph

Test results

airplane

sar_ship

ship

Note

This code works better when detecting single targets, but not suitable for multi-target detection tasks. Recommend improved code: https://github.com/DetectionTeamUCAS/FPN_Tensorflow.

fpn_tensorflow's People

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fpn_tensorflow's Issues

About ResNet and Faster_rcnn

Hi, thanks for your work firstly. I'm looking at your code and there is somewhere confused me. In the train step, as your instructor, i can download resnet-50 or resnet-101 pretrained model to run " python train.py" command line. The code in tools/train.py, i saw that there are some sentences like

tf.summary.scalar('rpn/rpn_total_loss') or tf.summary.scalar('fast_rcnn/fast_rcnn_total_loss')

so it confused me. The train model is resnet or fast-rcnn or others? And i did not see 'FPN' at all. May be something i understand wrong about the networks. I'll very appreciate for your reply.

Thanks.

out of memory when it is training

hello,have you met the problem? when it is training, the memory is exploding. I doubt the follow warning is the reason. I hope you can help me out.

anchor正负样本标定中对应的gtbox index确定

你好，libs/rpn/build_rpn.py中gtbox index确定过程
matched_gtboxes_index = tf.cast(tf.argmax(ious, axis=1), tf.int32)
如果某anchor是因为与gtbox_i的iou最大被标为正样本，但gtbox_i_iou在[gtbox_1_iou, gtbox_2_iou...]不为最大值，此时gtbox index 应该取gtbox_i的还是直接取iou最大的？

Strange questions, have anyone ever met ?

2018-05-25 22:02:57: step901 image_name:b'in000038.jpg' |
rpn_loc_loss:0.4218079447746277 | rpn_cla_loss:0.11451516300439835 | rpn_total_loss:0.5363231301307678 |
fast_rcnn_loc_loss:0.0 | fast_rcnn_cla_loss:0.09883365035057068 | fast_rcnn_total_loss:0.09883365035057068 |
total_loss:1.065047264099121 | pre_cost_time:50.461886167526245s
Traceback (most recent call last):
File "C:\Program Files\Anaconda2\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1139, in _do_call
return fn(*args)
File "C:\Program Files\Anaconda2\envs\tensorflow\lib\site-packages\tensorflow\python\client\session.py", line 1121, in _run_fn
status, run_metadata)
File "C:\Program Files\Anaconda2\envs\tensorflow\lib\contextlib.py", line 66, in exit
next(self.gen)
File "C:\Program Files\Anaconda2\envs\tensorflow\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 466, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.UnknownError: OverflowError: Python int too large to convert to C long
[[Node: fast_rcnn_loss/PyFunc_1 = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT32], Tout=[DT_UINT8], token="pyfunc_7", _device="/job:localhost/replica:0/task:0/cpu:0"](fast_rcnn_loss/Squeeze_1, fast_rcnn_loss/mul_1, fast_rcnn_loss/strided_slice_1)]]

InvalidArgumentError (see above for traceback): LossTensor is inf or nan

After running some steps, it raised the following error, please check it.
Thank you.

Caused by op u'train_op/CheckNumerics', defined at:
File "train.py", line 228, in
train()
File "train.py", line 138, in train
train_op = slim.learning.create_train_op(total_loss, optimizer, global_step) # rpn_total_loss,
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/slim/python/slim/learning.py", line 439, in create_train_op
check_numerics=check_numerics)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/training/python/training/training.py", line 464, in create_train_op
'LossTensor is inf or nan')
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 569, in check_numerics
"CheckNumerics", tensor=tensor, message=message, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2956, in create_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1470, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): LossTensor is inf or nan : Tensor had NaN values
[[Node: train_op/CheckNumerics = CheckNumericsT=DT_FLOAT, message="LossTensor is inf or nan", _device="/job:localhost/replica:0/task:0/device:CPU:0"]]

Unknown command line flag 'src_folder'

When I run the demo,it shows that absl.flags._exceptions.UnrecognizedFlagError: Unknown command line flag 'src_folder'.How can I deal with this problem?

您好，请问训练中途停止是什么原因呢？

所报错误是ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[320992,1962]
[[Node: rpn_losses/rpn_minibatch/rpn_find_positive_negative_samples/iou_caculate/Maximum_1 = Maximum[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](rpn_losses/rpn_minibatch/rpn_find_positive_negative_samples/iou_caculate/split, rpn_losses/rpn_minibatch/rpn_find_positive_negative_samples/iou_caculate/unstack)]]
[[Node: gradients/fast_rcnn_roi/Gather_2_grad/Reshape_1/_3699 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_19918_gradients/fast_rcnn_roi/Gather_2_grad/Reshape_1", tensor_type=DT_INT64, _device="/job:localhost/replica:0/task:0/cpu:0"]]
非常感谢！

It occurs a problem when i train my dataset,thank you in advance!

restore model
Traceback (most recent call last):
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1361, in _do_call
return fn(*args)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1340, in _run_fn
target_list, status, run_metadata)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py", line 516, in exit
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.OutOfRangeError: PaddingFIFOQueue '_1_get_batch/batch/padding_fifo_queue' is closed and has insufficient elements (requested 1, current size 0)
[[Node: get_batch/batch = QueueDequeueManyV2[component_types=[DT_STRING, DT_FLOAT, DT_INT32, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](get_batch/batch/padding_fifo_queue, gradients/range/delta)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "./train.py", line 229, in
train()
File "./train.py", line 196, in train
fast_rcnn_total_loss, total_loss, train_op])
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 905, in run
run_metadata_ptr)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1137, in _run
feed_dict_tensor, options, run_metadata)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1355, in _do_run
options, run_metadata)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1374, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: PaddingFIFOQueue '_1_get_batch/batch/padding_fifo_queue' is closed and has insufficient elements (requested 1, current size 0)
[[Node: get_batch/batch = QueueDequeueManyV2[component_types=[DT_STRING, DT_FLOAT, DT_INT32, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](get_batch/batch/padding_fifo_queue, gradients/range/delta)]]

Caused by op 'get_batch/batch', defined at:
File "./train.py", line 229, in
train()
File "./train.py", line 34, in train
is_training=True)
File "../data/io/read_tfrecord.py", line 89, in next_batch
dynamic_pad=True)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/training/input.py", line 989, in batch
name=name)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/training/input.py", line 763, in _batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/data_flow_ops.py", line 483, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 2430, in _queue_dequeue_many_v2
component_types=component_types, timeout_ms=timeout_ms, name=name)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3271, in create_op
op_def=op_def)
File "/home/emg/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1650, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

OutOfRangeError (see above for traceback): PaddingFIFOQueue '_1_get_batch/batch/padding_fifo_queue' is closed and has insufficient elements (requested 1, current size 0)
[[Node: get_batch/batch = QueueDequeueManyV2[component_types=[DT_STRING, DT_FLOAT, DT_INT32, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](get_batch/batch/padding_fifo_queue, gradients/range/delta)]]

How to understand this step(Train1)?

Train1.Modify $FPN_ROOT/libs/lable_name_dict/***_dict.py, corresponding to the number of categories in the configuration file

I don't know what should I modify in label_dict.py and what is the configuration file.
I skip this step,and some problem appear when running train.py .The problem is like this.

W tensorflow/core/framework/op_kernel.cc:1158] Out of range: PaddingFIFOQueue '_1_get_batch/batch/padding_fifo_queue' is closed and has insufficient elements (requested 1, current size 0)

How can i solve this problem?

`Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1350, in _do_call
return fn(*args)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1329, in _run_fn
status, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/errors_impl.py", line 473, in exit
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.UnknownError: OverflowError: signed integer is less than minimum
[[Node: draw_proposals/PyFunc_1 = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT32], Tout=[DT_UINT8], token="pyfunc_5", _device="/job:localhost/replica:0/task:0/device:CPU:0"](rpn_losses/Squeeze/_3081, rpn_proposals/cond/Merge/_3157, draw_proposals/strided_slice_1/_3159)]]
[[Node: fast_rcnn_loss/Reshape_2/tensor/_3243 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_3177_fast_rcnn_loss/Reshape_2/tensor", tensor_type=DT_UINT8, _device="/job:localhost/replica:0/task:0/device:GPU:0"]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/home/xjyu/work/FPN_Tensorflow-master/tools/train.py", line 227, in
train()
File "/home/xjyu/work/FPN_Tensorflow-master/tools/train.py", line 209, in train
summary_str = sess.run(summary_op)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 895, in run
run_metadata_ptr)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1128, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1344, in _do_run
options, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1363, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.UnknownError: OverflowError: signed integer is less than minimum
[[Node: draw_proposals/PyFunc_1 = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT32], Tout=[DT_UINT8], token="pyfunc_5", _device="/job:localhost/replica:0/task:0/device:CPU:0"](rpn_losses/Squeeze/_3081, rpn_proposals/cond/Merge/_3157, draw_proposals/strided_slice_1/_3159)]]
[[Node: fast_rcnn_loss/Reshape_2/tensor/_3243 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_3177_fast_rcnn_loss/Reshape_2/tensor", tensor_type=DT_UINT8, _device="/job:localhost/replica:0/task:0/device:GPU:0"]]

Caused by op 'draw_proposals/PyFunc_1', defined at:
File "/home/xjyu/work/FPN_Tensorflow-master/tools/train.py", line 227, in
train()
File "/home/xjyu/work/FPN_Tensorflow-master/tools/train.py", line 88, in train
text=tf.shape(rpn_proposals_boxes)[0])
File "/home/xjyu/work/FPN_Tensorflow-master/libs/box_utils/show_box_in_tensor.py", line 63, in draw_box_with_color
Tout=[tf.uint8])
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/script_ops.py", line 300, in py_func
func=func, inp=inp, Tout=Tout, stateful=stateful, eager=False, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/script_ops.py", line 209, in _internal_py_func
input=inp, token=token, Tout=Tout, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_script_ops.py", line 93, in _py_func
"PyFunc", input=input, token=token, Tout=Tout, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3160, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1625, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

UnknownError (see above for traceback): OverflowError: signed integer is less than minimum
[[Node: draw_proposals/PyFunc_1 = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT32], Tout=[DT_UINT8], token="pyfunc_5", _device="/job:localhost/replica:0/task:0/device:CPU:0"](rpn_losses/Squeeze/_3081, rpn_proposals/cond/Merge/_3157, draw_proposals/strided_slice_1/_3159)]]
[[Node: fast_rcnn_loss/Reshape_2/tensor/_3243 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device_incarnation=1, tensor_name="edge_3177_fast_rcnn_loss/Reshape_2/tensor", tensor_type=DT_UINT8, _device="/job:localhost/replica:0/task:0/device:GPU:0"]]`

convert_data_to_tfrecord.py error!

****when i run convert_data_to_tfrecord.py,
Traceback (most recent call last):
File "convert_data_to_tfrecord.py", line 134, in
convert_pascal_to_tfrecord()
File "convert_data_to_tfrecord.py", line 106, in convert_pascal_to_tfrecord
img_height, img_width, gtbox_label = read_xml_gtbox_and_label(xml)
File "convert_data_to_tfrecord.py", line 64, in read_xml_gtbox_and_label
label = NAME_LABEL_MAP[child_item.text]
KeyError: '5'
I don't know how to solve this probelms

occurs errors when i execute train.py

2018-07-22 19:19:07.851388: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at matching_files_op.cc:49 : Not found: ../data/tfrecords; No such file or directory
2018-07-22 19:19:07.851869: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at matching_files_op.cc:49 : Not found: ../data/tfrecords; No such file or directory
Traceback (most recent call last):
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1327, in _do_call
return fn(*args)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1312, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1420, in _call_tf_sessionrun
status, run_metadata)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 516, in exit
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.NotFoundError: ../data/tfrecords; No such file or directory
[[Node: get_batch/matching_filenames/MatchingFiles = MatchingFiles_device="/job:localhost/replica:0/task:0/device:CPU:0"]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "./tools/train.py", line 229, in
train()
File "./tools/train.py", line 176, in train
sess.run(init_op)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 905, in run
run_metadata_ptr)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1140, in _run
feed_dict_tensor, options, run_metadata)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1321, in _do_run
run_metadata)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: ../data/tfrecords; No such file or directory
[[Node: get_batch/matching_filenames/MatchingFiles = MatchingFiles_device="/job:localhost/replica:0/task:0/device:CPU:0"]]

Caused by op 'get_batch/matching_filenames/MatchingFiles', defined at:
File "./tools/train.py", line 229, in
train()
File "./tools/train.py", line 34, in train
is_training=True)
File "/vol/home/alex/FPN_Tensorflow/data/io/read_tfrecord.py", line 77, in next_batch
filename_tensorlist = tf.train.match_filenames_once(pattern)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/training/input.py", line 72, in match_filenames_once
name=name, initial_value=io_ops.matching_files(pattern),
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/ops/gen_io_ops.py", line 397, in matching_files
"MatchingFiles", pattern=pattern, name=name)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3290, in create_op
op_def=op_def)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1654, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

NotFoundError (see above for traceback): ../data/tfrecords; No such file or directory
[[Node: get_batch/matching_filenames/MatchingFiles = MatchingFiles_device="/job:localhost/replica:0/task:0/device:CPU:0"]]

tip:no ../data/tfrecords directory, but I have this directory, position is correct

icdar 的精度

作者您是否测试过在ICDAR2015上的精度，能否复现作者在论文上的效果

PaddingFIFOQueue

The reason for the PaddingFIFOQueue is that your generate wrong tfrecord:
(1) First you can test separately whether you can read data from tfrecord;
(2) If you can't read it, please check the path of tfrecord (read_tfrecord.py).
(3) In addition, There is a place in the picture that may need to be changed, depending on the different environment.

The problem for not fixing BN

What is the Map in pascal voc 07 dataset using this code? As i read your code, i find that you do not fix the BN parameters. The batchsize is small, following the paper FPN or Mask RCNN, you need to set the training and trainbale to False for the slim.batch_norm op. I am testing whether this is the problem for the bad generalization for mutiple objects.

fast rcnn阶段的rois获取问题

代码中levels=tf.round(4. + tf.log(tf.sqrt(wh + 1e-8)/224.0) / tf.log(2.))
这句代码怎么理解，如果我的训练图片大小是896896，是否仅仅需要将224换成896？

在运行vggnet16时TypeError: list indices must be integers, not str，不知道怎么解决，我是直接读取npy文件的

请问楼主这是什么问题导致啊？

aused by op u'draw_proposals/PyFunc_1', defined at:
File "train.py", line 229, in
train()
File "train.py", line 89, in train
text=tf.shape(rpn_proposals_boxes)[0])
File "../libs/box_utils/show_box_in_tensor.py", line 64, in draw_box_with_color
Tout=[tf.uint8])
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/script_ops.py", line 198, in py_func
input=inp, token=token, Tout=Tout, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_script_ops.py", line 38, in _py_func
name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2506, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1269, in init
self._traceback = _extract_stack()

UnknownError (see above for traceback): exceptions.OverflowError: signed integer is less than minimum
[[Node: draw_proposals/PyFunc_1 = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT32], Tout=[DT_UINT8], token="pyfunc_5", _device="/job:localhost/replica:0/task:0/cpu:0"](draw_proposals/Squeeze_1/_4341, rpn_proposals/cond/Merge/_4343, draw_proposals/strided_slice_1/_4345)]]
[[Node: fast_rcnn_loss/Reshape_2/tensor/_4295 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_6790_fast_rcnn_loss/Reshape_2/tensor", tensor_type=DT_UINT8, _device="/job:localhost/replica:0/task:0/gpu:0"]]

something about dataset

Does your data set about the aircraft do it yourself or download the dataset of someone else?

The training is not going on

I modified the config to train my own data, and there is no any error reported. However, the training is always on the step 0. Hope you can give me some clues. My device is GeForce GTX 1060 6GB. THKS!

signed integer is less than minimum

Caused by op u'rpn_losses/PyFunc_2', defined at:
File "train.py", line 228, in
train()
File "train.py", line 78, in train
rpn_location_loss, rpn_classification_loss = rpn.rpn_losses()
File "../data/io/../../libs/rpn/build_rpn.py", line 395, in rpn_losses
text=tf.shape(top_k_scores)[0])
File "../data/io/../../libs/box_utils/show_box_in_tensor.py", line 63, in draw_box_with_color
Tout=[tf.uint8])
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/script_ops.py", line 198, in py_func
input=inp, token=token, Tout=Tout, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_script_ops.py", line 38, in _py_func
name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2506, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1269, in init
self._traceback = _extract_stack()

UnknownError (see above for traceback): exceptions.OverflowError: signed integer is less than minimum
[[Node: rpn_losses/PyFunc_2 = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT32], Tout=[DT_UINT8], token="pyfunc_3", _device="/job:localhost/replica:0/task:0/cpu:0"](rpn_losses/Squeeze_2, rpn_losses/Gather_3, rpn_losses/strided_slice_3)]]

队列关闭

您好，请问训练过后如何在benchmark数据库上检测训练结果的准确率？

如题，请问是否是运行/tools/eval.py? 请问第297行fr1 = open('predict_dict.pkl', 'r') 与第298行fr2 = open('gtboxes_dict.pkl', 'r')，这两个pkl文件是指什么呢？如何生成这两个文件？望您回复，感谢！

楼主测过在voc数据集上的mAP吗？

如题，感谢楼主的代码实现

Dataset

i could't find the dataset ship,airplane,etc. and i really want to learn this project. Could you share these dataset with me ？ if it is included in a paper, i will cite this in my future paper. Thank you!
my email is [email protected] can also sent me a link where i can download .waiting for your good news!

Do the pictures have to be named by numbers?

fpn网络定义在哪呢？

实在是找不到你fpn层的定义在哪...

SIGNED INTEGER IS LESS THAN MINIMUM

Traceback (most recent call last):
File "train.py", line 229, in
train()
File "train.py", line 211, in train
summary_str = sess.run(summary_op)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 895, in run
run_metadata_ptr)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1124, in _run
feed_dict_tensor, options, run_metadata)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1321, in _do_run
options, run_metadata)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.UnknownError: exceptions.OverflowError: signed integer is less than minimum
[[Node: draw_proposals/PyFunc = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT32], Tout=[DT_UINT8], token="pyfunc_4", _device="/job:localhost/replica:0/task:0/cpu:0"](draw_proposals/Squeeze/_2597, draw_proposals/Gather/_2599, draw_proposals/strided_slice/_2601)]]
[[Node: fast_rcnn_loss/fast_rcnn_minibatch/RandomShuffle_2/_2483 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_3787_fast_rcnn_loss/fast_rcnn_minibatch/RandomShuffle_2", tensor_type=DT_INT64, _device="/job:localhost/replica:0/task:0/gpu:0"]]

Caused by op u'draw_proposals/PyFunc', defined at:
File "train.py", line 229, in
train()
File "train.py", line 87, in train
text=tf.shape(rpn_object_boxes)[0])
File "../libs/box_utils/show_box_in_tensor.py", line 63, in draw_box_with_color
Tout=[tf.uint8])
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/ops/script_ops.py", line 203, in py_func
input=inp, token=token, Tout=Tout, name=name)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/ops/gen_script_ops.py", line 36, in _py_func
name=name)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1204, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

UnknownError (see above for traceback): exceptions.OverflowError: signed integer is less than minimum
[[Node: draw_proposals/PyFunc = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT32], Tout=[DT_UINT8], token="pyfunc_4", _device="/job:localhost/replica:0/task:0/cpu:0"](draw_proposals/Squeeze/_2597, draw_proposals/Gather/_2599, draw_proposals/strided_slice/_2601)]]
[[Node: fast_rcnn_loss/fast_rcnn_minibatch/RandomShuffle_2/_2483 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_3787_fast_rcnn_loss/fast_rcnn_minibatch/RandomShuffle_2", tensor_type=DT_INT64, _device="/job:localhost/replica:0/task:0/gpu:0"]]

It seems that there is a problem of the summary_op part

请问，VOC数据集上训练，rpn loss不收敛，有什么可能的原因吗？

rpn_loc_loss 在某些图片上是0.xx，在有些图片上有30多

最后拿模型做test也没有正确的结果，所有图片都认为是0，也没有预测框

求助，谢谢:(

贴一段训练的log，这是将学习率调整为0.0001之后的log

 2018-06-14 12:20:30: step60403    image_name:008105.jpg |	
                                rpn_loc_loss:2.05723357201 |	 rpn_cla_loss:0.900643050671 |	 rpn_total_loss:2.95787668228 |
                                fast_rcnn_loc_loss:0.29182729125 |	 fast_rcnn_cla_loss:0.494256854057 |	 fast_rcnn_total_loss:0.78608417511 |
                                total_loss:4.47591352463 |	 pre_cost_time:0.469601869583s
 2018-06-14 12:20:35: step60413    image_name:004556.jpg |	
                                rpn_loc_loss:19.2806301117 |	 rpn_cla_loss:0.116126872599 |	 rpn_total_loss:19.3967571259 |
                                fast_rcnn_loc_loss:0.03605248034 |	 fast_rcnn_cla_loss:0.0864197462797 |	 fast_rcnn_total_loss:0.12247222662 |
                                total_loss:20.2511844635 |	 pre_cost_time:0.511494874954s
 2018-06-14 12:20:40: step60423    image_name:007907.jpg |	
                                rpn_loc_loss:29.0486793518 |	 rpn_cla_loss:0.16169847548 |	 rpn_total_loss:29.2103786469 |
                                fast_rcnn_loc_loss:0.0694024860859 |	 fast_rcnn_cla_loss:0.0653923526406 |	 fast_rcnn_total_loss:0.134794831276 |
                                total_loss:30.0771274567 |	 pre_cost_time:0.531568050385s
 2018-06-14 12:20:45: step60433    image_name:001663.jpg |	
                                rpn_loc_loss:13.3469562531 |	 rpn_cla_loss:0.133825153112 |	 rpn_total_loss:13.4807815552 |
                                fast_rcnn_loc_loss:0.0642159730196 |	 fast_rcnn_cla_loss:0.0958302691579 |	 fast_rcnn_total_loss:0.160046249628 |
                                total_loss:14.3727817535 |	 pre_cost_time:0.455081939697s
 2018-06-14 12:20:50: step60443    image_name:001862.jpg |	
                                rpn_loc_loss:0.353244125843 |	 rpn_cla_loss:0.0793683156371 |	 rpn_total_loss:0.432612448931 |
                                fast_rcnn_loc_loss:0.0735497996211 |	 fast_rcnn_cla_loss:0.066331461072 |	 fast_rcnn_total_loss:0.139881253242 |
                                total_loss:1.30444681644 |	 pre_cost_time:0.485862016678s
 2018-06-14 12:20:55: step60453    image_name:004847.jpg |	
                                rpn_loc_loss:15.3173036575 |	 rpn_cla_loss:0.270304232836 |	 rpn_total_loss:15.5876083374 |
                                fast_rcnn_loc_loss:0.0786234289408 |	 fast_rcnn_cla_loss:0.0949833244085 |	 fast_rcnn_total_loss:0.173606753349 |
                                total_loss:16.4931697845 |	 pre_cost_time:0.465280056s
 2018-06-14 12:20:59: step60463    image_name:008649.jpg |	
                                rpn_loc_loss:11.835559845 |	 rpn_cla_loss:0.0990793630481 |	 rpn_total_loss:11.9346389771 |
                                fast_rcnn_loc_loss:0.0224529933184 |	 fast_rcnn_cla_loss:0.0669757574797 |	 fast_rcnn_total_loss:0.0894287526608 |
                                total_loss:12.756023407 |	 pre_cost_time:0.483344078064s
 2018-06-14 12:21:04: step60473    image_name:001563.jpg |	
                                rpn_loc_loss:2.02798223495 |	 rpn_cla_loss:0.268615990877 |	 rpn_total_loss:2.29659819603 |
                                fast_rcnn_loc_loss:0.122499987483 |	 fast_rcnn_cla_loss:0.214369207621 |	 fast_rcnn_total_loss:0.336869180202 |
                                total_loss:3.36542034149 |	 pre_cost_time:0.507468938828s
 2018-06-14 12:21:10: step60483    image_name:009480.jpg |	
                                rpn_loc_loss:10.0660276413 |	 rpn_cla_loss:0.475047171116 |	 rpn_total_loss:10.5410747528 |
                                fast_rcnn_loc_loss:0.106006294489 |	 fast_rcnn_cla_loss:0.161696076393 |	 fast_rcnn_total_loss:0.267702370882 |
                                total_loss:11.5407314301 |	 pre_cost_time:0.480077028275s
 2018-06-14 12:21:14: step60493    image_name:002549.jpg |	
                                rpn_loc_loss:1.25509309769 |	 rpn_cla_loss:0.556017160416 |	 rpn_total_loss:1.8111102581 |
                                fast_rcnn_loc_loss:0.0191622953862 |	 fast_rcnn_cla_loss:0.0564195141196 |	 fast_rcnn_total_loss:0.0755818113685 |
                                total_loss:2.61864495277 |	 pre_cost_time:0.465098142624s
 2018-06-14 12:21:19: step60503    image_name:007583.jpg |	
                                rpn_loc_loss:0.33879968524 |	 rpn_cla_loss:0.222999542952 |	 rpn_total_loss:0.561799228191 |
                                fast_rcnn_loc_loss:0.0962313115597 |	 fast_rcnn_cla_loss:0.170783832669 |	 fast_rcnn_total_loss:0.26701515913 |
                                total_loss:1.5607676506 |	 pre_cost_time:0.43776011467s
 2018-06-14 12:21:27: step60513    image_name:005022.jpg |	
                                rpn_loc_loss:0.154285207391 |	 rpn_cla_loss:0.265934407711 |	 rpn_total_loss:0.420219600201 |
                                fast_rcnn_loc_loss:0.0 |	 fast_rcnn_cla_loss:0.0173826627433 |	 fast_rcnn_total_loss:0.0173826627433 |
                                total_loss:1.16955566406 |	 pre_cost_time:0.501232147217s
 2018-06-14 12:21:32: step60523    image_name:003551.jpg |	
                                rpn_loc_loss:0.595891058445 |	 rpn_cla_loss:0.174645081162 |	 rpn_total_loss:0.770536124706 |
                                fast_rcnn_loc_loss:0.0125400628895 |	 fast_rcnn_cla_loss:0.0366840735078 |	 fast_rcnn_total_loss:0.0492241382599 |
                                total_loss:1.55171358585 |	 pre_cost_time:0.473511219025s
 2018-06-14 12:21:37: step60533    image_name:002795.jpg |	
                                rpn_loc_loss:0.415669262409 |	 rpn_cla_loss:0.368684262037 |	 rpn_total_loss:0.784353494644 |
                                fast_rcnn_loc_loss:0.0294939801097 |	 fast_rcnn_cla_loss:0.0599008537829 |	 fast_rcnn_total_loss:0.0893948376179 |
                                total_loss:1.60570168495 |	 pre_cost_time:0.462094068527s
 2018-06-14 12:21:42: step60543    image_name:009306.jpg |	
                                rpn_loc_loss:8.61710548401 |	 rpn_cla_loss:0.437390208244 |	 rpn_total_loss:9.05449581146 |
                                fast_rcnn_loc_loss:0.106448456645 |	 fast_rcnn_cla_loss:0.136525779963 |	 fast_rcnn_total_loss:0.242974236608 |
                                total_loss:10.0294246674 |	 pre_cost_time:0.480259895325s
 2018-06-14 12:21:47: step60553    image_name:000403.jpg |	
                                rpn_loc_loss:17.2208366394 |	 rpn_cla_loss:0.108800955117 |	 rpn_total_loss:17.3296375275 |
                                fast_rcnn_loc_loss:0.0871697515249 |	 fast_rcnn_cla_loss:0.105191238225 |	 fast_rcnn_total_loss:0.1923609972 |
                                total_loss:18.2539520264 |	 pre_cost_time:0.4732401371s
 2018-06-14 12:21:52: step60563    image_name:001776.jpg |	
                                rpn_loc_loss:5.62985134125 |	 rpn_cla_loss:0.637479364872 |	 rpn_total_loss:6.26733064651 |
                                fast_rcnn_loc_loss:0.072887763381 |	 fast_rcnn_cla_loss:0.109321445227 |	 fast_rcnn_total_loss:0.182209208608 |
                                total_loss:7.18149423599 |	 pre_cost_time:0.50107383728s
 2018-06-14 12:21:57: step60573    image_name:006702.jpg |	
                                rpn_loc_loss:0.899392724037 |	 rpn_cla_loss:0.555935382843 |	 rpn_total_loss:1.45532810688 |
                                fast_rcnn_loc_loss:0.0513089261949 |	 fast_rcnn_cla_loss:0.0749804228544 |	 fast_rcnn_total_loss:0.126289352775 |
                                total_loss:2.31357073784 |	 pre_cost_time:0.476425170898s
 2018-06-14 12:22:02: step60583    image_name:004071.jpg |	
                                rpn_loc_loss:11.5561742783 |	 rpn_cla_loss:0.101583331823 |	 rpn_total_loss:11.6577577591 |
                                fast_rcnn_loc_loss:0.019030706957 |	 fast_rcnn_cla_loss:0.0453039929271 |	 fast_rcnn_total_loss:0.0643346980214 |
                                total_loss:12.4540472031 |	 pre_cost_time:0.428576946259s
 2018-06-14 12:22:07: step60593    image_name:004482.jpg |	
                                rpn_loc_loss:31.5635948181 |	 rpn_cla_loss:0.172389492393 |	 rpn_total_loss:31.7359848022 |
                                fast_rcnn_loc_loss:0.101848945022 |	 fast_rcnn_cla_loss:0.0788979232311 |	 fast_rcnn_total_loss:0.180746868253 |
                                total_loss:32.64868927 |	 pre_cost_time:0.479720115662s
 2018-06-14 12:22:12: step60603    image_name:004670.jpg |	
                                rpn_loc_loss:0.0734175369143 |	 rpn_cla_loss:0.269607931376 |	 rpn_total_loss:0.34302547574 |
                                fast_rcnn_loc_loss:0.0 |	 fast_rcnn_cla_loss:0.0191261749715 |	 fast_rcnn_total_loss:0.0191261749715 |
                                total_loss:1.09410512447 |	 pre_cost_time:0.509476900101s
 2018-06-14 12:22:18: step60613    image_name:006023.jpg |	
                                rpn_loc_loss:12.7789239883 |	 rpn_cla_loss:0.0952100381255 |	 rpn_total_loss:12.8741340637 |
                                fast_rcnn_loc_loss:0.0278376862407 |	 fast_rcnn_cla_loss:0.0558322630823 |	 fast_rcnn_total_loss:0.0836699455976 |
                                total_loss:13.6897583008 |	 pre_cost_time:0.487910985947s
 2018-06-14 12:22:23: step60623    image_name:001005.jpg |	
                                rpn_loc_loss:0.639028191566 |	 rpn_cla_loss:0.522748112679 |	 rpn_total_loss:1.16177630424 |
                                fast_rcnn_loc_loss:0.000708404520992 |	 fast_rcnn_cla_loss:0.0266169980168 |	 fast_rcnn_total_loss:0.0273254029453 |
                                total_loss:1.92105507851 |	 pre_cost_time:0.486565113068s
 2018-06-14 12:22:28: step60633    image_name:009335.jpg |	
                                rpn_loc_loss:0.282863616943 |	 rpn_cla_loss:0.551841139793 |	 rpn_total_loss:0.834704756737 |
                                fast_rcnn_loc_loss:0.0 |	 fast_rcnn_cla_loss:0.0135724116117 |	 fast_rcnn_total_loss:0.0135724116117 |
                                total_loss:1.58023047447 |	 pre_cost_time:0.482041120529s
 2018-06-14 12:22:34: step60643    image_name:001650.jpg |	
                                rpn_loc_loss:1.28183162212 |	 rpn_cla_loss:0.373366981745 |	 rpn_total_loss:1.65519857407 |
                                fast_rcnn_loc_loss:0.0110192643479 |	 fast_rcnn_cla_loss:0.0356653928757 |	 fast_rcnn_total_loss:0.0466846562922 |
                                total_loss:2.43383646011 |	 pre_cost_time:0.508905887604s
 2018-06-14 12:22:39: step60653    image_name:003087.jpg |	
                                rpn_loc_loss:0.322137057781 |	 rpn_cla_loss:0.134973421693 |	 rpn_total_loss:0.457110464573 |
                                fast_rcnn_loc_loss:0.0702097117901 |	 fast_rcnn_cla_loss:0.176795721054 |	 fast_rcnn_total_loss:0.247005432844 |
                                total_loss:1.43606948853 |	 pre_cost_time:0.467333078384s
 2018-06-14 12:22:44: step60663    image_name:004298.jpg |	
                                rpn_loc_loss:4.05768680573 |	 rpn_cla_loss:0.608667492867 |	 rpn_total_loss:4.66635417938 |
                                fast_rcnn_loc_loss:0.0645890682936 |	 fast_rcnn_cla_loss:0.1116142869 |	 fast_rcnn_total_loss:0.176203355193 |
                                total_loss:5.57451200485 |	 pre_cost_time:0.475219964981s
 2018-06-14 12:22:49: step60673    image_name:005889.jpg |	
                                rpn_loc_loss:6.49503231049 |	 rpn_cla_loss:0.119138218462 |	 rpn_total_loss:6.6141705513 |
                                fast_rcnn_loc_loss:0.162173375487 |	 fast_rcnn_cla_loss:0.170419067144 |	 fast_rcnn_total_loss:0.332592427731 |
                                total_loss:7.67871713638 |	 pre_cost_time:0.486320972443s
 2018-06-14 12:22:53: step60683    image_name:004984.jpg |	
                                rpn_loc_loss:37.5337257385 |	 rpn_cla_loss:0.104520298541 |	 rpn_total_loss:37.6382446289 |
                                fast_rcnn_loc_loss:0.0563882887363 |	 fast_rcnn_cla_loss:0.0821540281177 |	 fast_rcnn_total_loss:0.138542324305 |
                                total_loss:38.5087394714 |	 pre_cost_time:0.47732591629s
 2018-06-14 12:22:58: step60693    image_name:003655.jpg |	
                                rpn_loc_loss:17.961019516 |	 rpn_cla_loss:0.250774890184 |	 rpn_total_loss:18.2117938995 |
                                fast_rcnn_loc_loss:0.0939721092582 |	 fast_rcnn_cla_loss:0.0833453536034 |	 fast_rcnn_total_loss:0.177317470312 |
                                total_loss:19.1210651398 |	 pre_cost_time:0.470115184784s
 2018-06-14 12:23:04: step60703    image_name:008504.jpg |	
                                rpn_loc_loss:0.65000295639 |	 rpn_cla_loss:0.365115880966 |	 rpn_total_loss:1.01511883736 |
                                fast_rcnn_loc_loss:0.0546052791178 |	 fast_rcnn_cla_loss:0.130576968193 |	 fast_rcnn_total_loss:0.185182243586 |
                                total_loss:1.93225443363 |	 pre_cost_time:0.505920886993s

anchor error!

你好！请问一下
BASE_ANCHOR_SIZE_LIST = [15, 25, 40, 60, 80]
LEVEL = ['P2', 'P3', 'P4', 'P5', "P6"]
STRIDE = [4, 8, 16, 32, 64]
ANCHOR_SCALES = [1.]
ANCHOR_RATIOS = [1, 0.5, 2, 1 / 3., 3., 1.5, 1 / 1.5]
SCALE_FACTORS = [10., 10., 5., 5.]
OUTPUT_STRIDE = 16

请问一下这几个参数的意义是什么？

Support for Different Batch Sizes

The code works only if the BATCH_SIZE is set to 1. Are you planning to add larger batch size capability ?
Thanks

test.py

ERROR: tools.test.test

Traceback (most recent call last):
File "/.conda/envs/tensorflow/lib/python3.5/site-packages/nose/case.py", line 198, in runTest
self.test(*self.arg)
TypeError: test() missing 1 required positional argument: 'img_num'
-------------------- >> begin captured logging << --------------------
tensorflow: Level 1: Registering FakeQuantWithMinMaxArgs (<function _FakeQuantWithMinMaxArgsGradient at 0x7fa80df94ea0>) in gradient.
tensorflow: Level 1: Registering FakeQuantWithMinMaxVars (<function _FakeQuantWithMinMaxVarsGradient at 0x7fa80de70d90>) in gradient.
tensorflow: Level 1: Registering FakeQuantWithMinMaxVarsPerChannel (<function _FakeQuantWithMinMaxVarsPerChannelGradient at 0x7fa80deae488>) in gradient.
tensorflow: Level 1: Registering MatMul,flops (<function _calc_mat_mul_flops at 0x7fa80dc73598>) in statistical functions.
tensorflow: Level 1: Registering AccumulateNV2 (<function _accumulate_n_grad at 0x7fa80dc750d0>) in gradient.
tensorflow: Level 1: Registering cond_context ((<class 'tensorflow.core.protobuf.control_flow_pb2.CondContextDef'>, <function CondContext.to_proto at 0x7fa80dbc7950>, <function CondContext.from_proto at 0x7fa80dbc79d8>)) in proto functions.
tensorflow: Level 1: Registering while_context ((<class 'tensorflow.core.protobuf.control_flow_pb2.WhileContextDef'>, <function WhileContext.to_proto at 0x7fa80dbc97b8>, <function WhileContext.from_proto at 0x7fa80dbc98c8>)) in proto functions.
tensorflow: Level 1: Registering ReadVariableOp (<function _ReadGrad at 0x7fa80dafc0d0>) in gradient.
tensorflow: Level 1: Registering ResourceGather (<function _GatherGrad at 0x7fa80dafc2f0>) in gradient.
tensorflow: Level 1: Registering variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering trainable_variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering moving_average_variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering local_variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering model_variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering global_step ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering RandomStandardNormal (None) in gradient.
tensorflow: Level 1: Registering ParameterizedTruncatedNormal (None) in gradient.
tensorflow: Level 1: Registering TruncatedNormal (None) in gradient.
tensorflow: Level 1: Registering RandomUniform (None) in gradient.
tensorflow: Level 1: Registering Multinomial (None) in gradient.
tensorflow: Level 1: Registering RandomGamma (None) in gradient.
tensorflow: Level 1: Registering Pack (<function _PackGrad at 0x7fa8a5e22158>) in gradient.
tensorflow: Level 1: Registering Unpack (<function _UnpackGrad at 0x7fa8a5dda950>) in gradient.
tensorflow: Level 1: Registering Concat (<function _ConcatGrad at 0x7fa8a5ddaa60>) in gradient.
tensorflow: Level 1: Registering ConcatV2 (<function _ConcatGradV2 at 0x7fa8a5ddaae8>) in gradient.
tensorflow: Level 1: Registering ConcatOffset (None) in gradient.
tensorflow: Level 1: Registering Slice (<function _SliceGrad at 0x7fa8a5ddab70>) in gradient.
tensorflow: Level 1: Registering StridedSlice (<function _StridedSliceGrad at 0x7fa8a5ddabf8>) in gradient.
tensorflow: Level 1: Registering StridedSliceGrad (<function _StridedSliceGradGrad at 0x7fa8a5ddac80>) in gradient.
tensorflow: Level 1: Registering Split (<function _SplitGrad at 0x7fa8a5ddad08>) in gradient.
tensorflow: Level 1: Registering SplitV (<function _SplitVGrad at 0x7fa8a5ddad90>) in gradient.
tensorflow: Level 1: Registering Const (None) in gradient.
tensorflow: Level 1: Registering Diag (<function _DiagGrad at 0x7fa8a5ddae18>) in gradient.
tensorflow: Level 1: Registering DiagPart (<function _DiagPartGrad at 0x7fa8a5ddaea0>) in gradient.
tensorflow: Level 1: Registering MatrixDiag (<function _MatrixDiagGrad at 0x7fa8a5ddaf28>) in gradient.
tensorflow: Level 1: Registering MatrixDiagPart (<function _MatrixDiagPartGrad at 0x7fa8a5df2048>) in gradient.
tensorflow: Level 1: Registering MatrixSetDiag (<function _MatrixSetDiagGrad at 0x7fa8a5df20d0>) in gradient.
tensorflow: Level 1: Registering MatrixBandPart (<function _MatrixBandPartGrad at 0x7fa8a5df2158>) in gradient.
tensorflow: Level 1: Registering EditDistance (None) in gradient.
tensorflow: Level 1: Registering Fill (<function _FillGrad at 0x7fa8a5df21e0>) in gradient.
tensorflow: Level 1: Registering ZerosLike (None) in gradient.
tensorflow: Level 1: Registering OnesLike (None) in gradient.
tensorflow: Level 1: Registering PreventGradient (<function _PreventGradientGrad at 0x7fa8a5df2268>) in gradient.
tensorflow: Level 1: Registering Gather (<function _GatherGrad at 0x7fa8a5df22f0>) in gradient.
tensorflow: Level 1: Registering GatherV2 (<function _GatherV2Grad at 0x7fa8a5df2378>) in gradient.
tensorflow: Level 1: Registering GatherNd (<function _GatherNdGrad at 0x7fa8a5df2400>) in gradient.
tensorflow: Level 1: Registering CheckNumerics (<function _CheckNumericsGrad at 0x7fa8a5df2488>) in gradient.
tensorflow: Level 1: Registering Identity (<function _IdGrad at 0x7fa8a5df2510>) in gradient.
tensorflow: Level 1: Registering PlaceholderWithDefault (<function _IdGrad at 0x7fa8a5df2510>) in gradient.
tensorflow: Level 1: Registering RefIdentity (<function _RefIdGrad at 0x7fa8a5df2598>) in gradient.
tensorflow: Level 1: Registering IdentityN (<function _IdNGrad at 0x7fa8a5df2620>) in gradient.
tensorflow: Level 1: Registering StopGradient (None) in gradient.
tensorflow: Level 1: Registering Reshape (<function _ReshapeGrad at 0x7fa8a5df26a8>) in gradient.
tensorflow: Level 1: Registering InvertPermutation (None) in gradient.
tensorflow: Level 1: Registering ExpandDims (<function _ExpandDimsGrad at 0x7fa8a5df27b8>) in gradient.
tensorflow: Level 1: Registering Squeeze (<function _SqueezeGrad at 0x7fa8a5df2840>) in gradient.
tensorflow: Level 1: Registering Transpose (<function _TransposeGrad at 0x7fa8a5df28c8>) in gradient.
tensorflow: Level 1: Registering ConjugateTranspose (<function _ConjugateTransposeGrad at 0x7fa8a5df2950>) in gradient.
tensorflow: Level 1: Registering Shape (None) in gradient.
tensorflow: Level 1: Registering ShapeN (None) in gradient.
tensorflow: Level 1: Registering Rank (None) in gradient.
tensorflow: Level 1: Registering Size (None) in gradient.
tensorflow: Level 1: Registering Tile (<function _TileGrad at 0x7fa8a5df29d8>) in gradient.
tensorflow: Level 1: Registering BroadcastGradientArgs (None) in gradient.
tensorflow: Level 1: Registering Pad (<function _PadGrad at 0x7fa8a5df2a60>) in gradient.
tensorflow: Level 1: Registering PadV2 (<function _PadGrad at 0x7fa8a5df2a60>) in gradient.
tensorflow: Level 1: Registering ReverseSequence (<function _ReverseSequenceGrad at 0x7fa8a5df2ae8>) in gradient.
tensorflow: Level 1: Registering Reverse (<function _ReverseGrad at 0x7fa8a5df2b70>) in gradient.
tensorflow: Level 1: Registering ReverseV2 (<function _ReverseV2Grad at 0x7fa8a5df2bf8>) in gradient.
tensorflow: Level 1: Registering SpaceToBatch (<function _SpaceToBatchGrad at 0x7fa8a5df2c80>) in gradient.
tensorflow: Level 1: Registering SpaceToBatchND (<function _SpaceToBatchNDGrad at 0x7fa8a5df2d08>) in gradient.
tensorflow: Level 1: Registering BatchToSpace (<function _BatchToSpaceGrad at 0x7fa8a5df2d90>) in gradient.
tensorflow: Level 1: Registering BatchToSpaceND (<function _BatchToSpaceNDGrad at 0x7fa8a5df2e18>) in gradient.
tensorflow: Level 1: Registering SpaceToDepth (<function _SpaceToDepthGrad at 0x7fa8a5df2ea0>) in gradient.
tensorflow: Level 1: Registering DepthToSpace (<function _DepthToSpaceGrad at 0x7fa8a5df2f28>) in gradient.
tensorflow: Level 1: Registering OneHot (None) in gradient.
tensorflow: Level 1: Registering MirrorPad (<function _MirrorPadGrad at 0x7fa8a5df7048>) in gradient.
tensorflow: Level 1: Registering MirrorPadGrad (<function _MirrorPadGradGrad at 0x7fa8a5df70d0>) in gradient.
tensorflow: Level 1: Registering QuantizeAndDequantize (<function _QuantizeAndDequantizeGrad at 0x7fa8a5df7158>) in gradient.
tensorflow: Level 1: Registering QuantizeAndDequantizeV2 (<function _QuantizeAndDequantizeV2Grad at 0x7fa8a5df71e0>) in gradient.
tensorflow: Level 1: Registering QuantizeAndDequantizeV3 (<function _QuantizeAndDequantizeV3Grad at 0x7fa8a5df7268>) in gradient.
tensorflow: Level 1: Registering ExtractImagePatches (<function _ExtractImagePatchesGrad at 0x7fa8a5df72f0>) in gradient.
tensorflow: Level 1: Registering ScatterNd (<function _ScatterNdGrad at 0x7fa8a5df7378>) in gradient.
tensorflow: Level 1: Registering ScatterNdNonAliasingAdd (<function _ScatterNdNonAliasingAddGrad at 0x7fa8a5df7400>) in gradient.
tensorflow: Level 1: Registering DynamicPartition (<function _DynamicPartitionGrads at 0x7fa8a5df7510>) in gradient.
tensorflow: Level 1: Registering ParallelDynamicStitch (<function _DynamicStitchGrads at 0x7fa8a5d99bf8>) in gradient.
tensorflow: Level 1: Registering DynamicStitch (<function _DynamicStitchGrads at 0x7fa8a5d99bf8>) in gradient.
tensorflow: Level 1: Registering Queue (None) in gradient.
tensorflow: Level 1: Registering QueueEnqueue (None) in gradient.
tensorflow: Level 1: Registering QueueEnqueueMany (None) in gradient.
tensorflow: Level 1: Registering QueueDequeue (None) in gradient.
tensorflow: Level 1: Registering QueueDequeueMany (None) in gradient.
tensorflow: Level 1: Registering QueueDequeueUpTo (None) in gradient.
tensorflow: Level 1: Registering QueueClose (None) in gradient.
tensorflow: Level 1: Registering QueueSize (None) in gradient.
tensorflow: Level 1: Registering Stack (None) in gradient.
tensorflow: Level 1: Registering StackPush (None) in gradient.
tensorflow: Level 1: Registering StackPop (None) in gradient.
tensorflow: Level 1: Registering StackClose (None) in gradient.
tensorflow: Level 1: Registering GetSessionHandle (None) in gradient.
tensorflow: Level 1: Registering GetSessionHandleV2 (None) in gradient.
tensorflow: Level 1: Registering GetSessionTensor (None) in gradient.
tensorflow: Level 1: Registering DeleteSessionTensor (None) in gradient.
tensorflow: Level 1: Registering Roll (<function _RollGrad at 0x7fa8a5d99c80>) in gradient.
tensorflow: Level 1: Registering ArgMax (<function _ArgMaxGrad at 0x7fa8a5da8598>) in gradient.
tensorflow: Level 1: Registering ArgMin (<function _ArgMinGrad at 0x7fa8a5da8c80>) in gradient.
tensorflow: Level 1: Registering Sum (<function _SumGrad at 0x7fa8a5da8d08>) in gradient.
tensorflow: Level 1: Registering Max (<function _MaxGrad at 0x7fa8a5da8e18>) in gradient.
tensorflow: Level 1: Registering Min (<function _MinGrad at 0x7fa8a5da8ea0>) in gradient.
tensorflow: Level 1: Registering Mean (<function _MeanGrad at 0x7fa8a5da8f28>) in gradient.
tensorflow: Level 1: Registering Prod (<function _ProdGrad at 0x7fa8a5d4f048>) in gradient.
tensorflow: Level 1: Registering SegmentSum (<function _SegmentSumGrad at 0x7fa8a5d4f0d0>) in gradient.
tensorflow: Level 1: Registering SegmentMean (<function _SegmentMeanGrad at 0x7fa8a5d4f158>) in gradient.
tensorflow: Level 1: Registering SparseSegmentSum (<function _SparseSegmentSumGrad at 0x7fa8a5d4f1e0>) in gradient.
tensorflow: Level 1: Registering SparseSegmentSumWithNumSegments (<function _SparseSegmentSumWithNumSegmentsGrad at 0x7fa8a5d4f268>) in gradient.
tensorflow: Level 1: Registering SparseSegmentMean (<function _SparseSegmentMeanGrad at 0x7fa8a5d4f2f0>) in gradient.
tensorflow: Level 1: Registering SparseSegmentMeanWithNumSegments (<function _SparseSegmentMeanWithNumSegmentsGrad at 0x7fa8a5d4f378>) in gradient.
tensorflow: Level 1: Registering SparseSegmentSqrtN (<function _SparseSegmentSqrtNGrad at 0x7fa8a5d4f400>) in gradient.
tensorflow: Level 1: Registering SparseSegmentSqrtNWithNumSegments (<function _SparseSegmentSqrtNWithNumSegmentsGrad at 0x7fa8a5d4f488>) in gradient.
tensorflow: Level 1: Registering SegmentMin (<function _SegmentMinGrad at 0x7fa8a5d4f598>) in gradient.
tensorflow: Level 1: Registering SegmentMax (<function _SegmentMaxGrad at 0x7fa8a5d4f620>) in gradient.
tensorflow: Level 1: Registering UnsortedSegmentSum (<function _UnsortedSegmentSumGrad at 0x7fa8a5d4f7b8>) in gradient.
tensorflow: Level 1: Registering UnsortedSegmentMax (<function _UnsortedSegmentMaxGrad at 0x7fa8a5d4f840>) in gradient.
tensorflow: Level 1: Registering UnsortedSegmentMin (<function _UnsortedSegmentMinGrad at 0x7fa8a5d4f8c8>) in gradient.
tensorflow: Level 1: Registering UnsortedSegmentProd (<function _UnsortedSegmentProdGrad at 0x7fa8a5d4f950>) in gradient.
tensorflow: Level 1: Registering Abs (<function _AbsGrad at 0x7fa8a5d4f9d8>) in gradient.
tensorflow: Level 1: Registering Neg (<function _NegGrad at 0x7fa8a5d4fa60>) in gradient.
tensorflow: Level 1: Registering Inv (<function _InvGrad at 0x7fa8a5d4fae8>) in gradient.
tensorflow: Level 1: Registering Reciprocal (<function _ReciprocalGrad at 0x7fa8a5d4fb70>) in gradient.
tensorflow: Level 1: Registering InvGrad (<function _InvGradGrad at 0x7fa8a5d4fbf8>) in gradient.
tensorflow: Level 1: Registering ReciprocalGrad (<function _ReciprocalGradGrad at 0x7fa8a5d4fc80>) in gradient.
tensorflow: Level 1: Registering Square (<function _SquareGrad at 0x7fa8a5d4fd08>) in gradient.
tensorflow: Level 1: Registering Sqrt (<function _SqrtGrad at 0x7fa8a5d4fd90>) in gradient.
tensorflow: Level 1: Registering SqrtGrad (<function _SqrtGradGrad at 0x7fa8a5d4fe18>) in gradient.
tensorflow: Level 1: Registering Rsqrt (<function _RsqrtGrad at 0x7fa8a5d4fea0>) in gradient.
tensorflow: Level 1: Registering RsqrtGrad (<function _RsqrtGradGrad at 0x7fa8a5d4ff28>) in gradient.
tensorflow: Level 1: Registering Exp (<function _ExpGrad at 0x7fa8a5d51048>) in gradient.
tensorflow: Level 1: Registering Expm1 (<function _Expm1Grad at 0x7fa8a5d510d0>) in gradient.
tensorflow: Level 1: Registering Log (<function _LogGrad at 0x7fa8a5d51158>) in gradient.
tensorflow: Level 1: Registering Log1p (<function _Log1pGrad at 0x7fa8a5d511e0>) in gradient.
tensorflow: Level 1: Registering Sinh (<function _SinhGrad at 0x7fa8a5d51268>) in gradient.
tensorflow: Level 1: Registering Cosh (<function _CoshGrad at 0x7fa8a5d512f0>) in gradient.
tensorflow: Level 1: Registering Tanh (<function _TanhGrad at 0x7fa8a5d51378>) in gradient.
tensorflow: Level 1: Registering Asinh (<function _AsinhGrad at 0x7fa8a5d51400>) in gradient.
tensorflow: Level 1: Registering Acosh (<function _AcoshGrad at 0x7fa8a5d51488>) in gradient.
tensorflow: Level 1: Registering Atanh (<function _AtanhGrad at 0x7fa8a5d51510>) in gradient.
tensorflow: Level 1: Registering TanhGrad (<function _TanhGradGrad at 0x7fa8a5d51598>) in gradient.
tensorflow: Level 1: Registering Erf (<function _ErfGrad at 0x7fa8a5d51620>) in gradient.
tensorflow: Level 1: Registering Erfc (<function _ErfcGrad at 0x7fa8a5d516a8>) in gradient.
tensorflow: Level 1: Registering Lgamma (<function _LgammaGrad at 0x7fa8a5d51730>) in gradient.
tensorflow: Level 1: Registering Digamma (<function _DigammaGrad at 0x7fa8a5d517b8>) in gradient.
tensorflow: Level 1: Registering Igamma (<function _IgammaGrad at 0x7fa8a5d51840>) in gradient.
tensorflow: Level 1: Registering Igammac (<function _IgammacGrad at 0x7fa8a5d518c8>) in gradient.
tensorflow: Level 1: Registering Betainc (<function _BetaincGrad at 0x7fa8a5d51950>) in gradient.
tensorflow: Level 1: Registering Zeta (<function _ZetaGrad at 0x7fa8a5d519d8>) in gradient.
tensorflow: Level 1: Registering Polygamma (<function _PolygammaGrad at 0x7fa8a5d51a60>) in gradient.
tensorflow: Level 1: Registering Sigmoid (<function _SigmoidGrad at 0x7fa8a5d51ae8>) in gradient.
tensorflow: Level 1: Registering SigmoidGrad (<function _SigmoidGradGrad at 0x7fa8a5d51b70>) in gradient.
tensorflow: Level 1: Registering Sign (<function _SignGrad at 0x7fa8a5d51bf8>) in gradient.
tensorflow: Level 1: Registering Sin (<function _SinGrad at 0x7fa8a5d51c80>) in gradient.
tensorflow: Level 1: Registering Cos (<function _CosGrad at 0x7fa8a5d51d08>) in gradient.

Error
Traceback (most recent call last):
File "/home/qzhang/.conda/envs/tensorflow/lib/python3.5/unittest/case.py", line 59, in testPartExecutor
yield
File "/home/qzhang/.conda/envs/tensorflow/lib/python3.5/unittest/case.py", line 601, in run
testMethod()
File "/home/qzhang/.conda/envs/tensorflow/lib/python3.5/site-packages/nose/case.py", line 198, in runTest
self.test(*self.arg)
Exception: test() missing 1 required positional argument: 'img_num'
-------------------- >> begin captured logging << --------------------
tensorflow: Level 1: Registering FakeQuantWithMinMaxArgs (<function _FakeQuantWithMinMaxArgsGradient at 0x7fa80df94ea0>) in gradient.
tensorflow: Level 1: Registering FakeQuantWithMinMaxVars (<function _FakeQuantWithMinMaxVarsGradient at 0x7fa80de70d90>) in gradient.
tensorflow: Level 1: Registering FakeQuantWithMinMaxVarsPerChannel (<function _FakeQuantWithMinMaxVarsPerChannelGradient at 0x7fa80deae488>) in gradient.
tensorflow: Level 1: Registering MatMul,flops (<function _calc_mat_mul_flops at 0x7fa80dc73598>) in statistical functions.
tensorflow: Level 1: Registering AccumulateNV2 (<function _accumulate_n_grad at 0x7fa80dc750d0>) in gradient.
tensorflow: Level 1: Registering cond_context ((<class 'tensorflow.core.protobuf.control_flow_pb2.CondContextDef'>, <function CondContext.to_proto at 0x7fa80dbc7950>, <function CondContext.from_proto at 0x7fa80dbc79d8>)) in proto functions.
tensorflow: Level 1: Registering while_context ((<class 'tensorflow.core.protobuf.control_flow_pb2.WhileContextDef'>, <function WhileContext.to_proto at 0x7fa80dbc97b8>, <function WhileContext.from_proto at 0x7fa80dbc98c8>)) in proto functions.
tensorflow: Level 1: Registering ReadVariableOp (<function _ReadGrad at 0x7fa80dafc0d0>) in gradient.
tensorflow: Level 1: Registering ResourceGather (<function _GatherGrad at 0x7fa80dafc2f0>) in gradient.
tensorflow: Level 1: Registering variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering trainable_variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering moving_average_variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering local_variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering model_variables ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering global_step ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa80dafc400>)) in proto functions.
tensorflow: Level 1: Registering RandomStandardNormal (None) in gradient.
tensorflow: Level 1: Registering ParameterizedTruncatedNormal (None) in gradient.
tensorflow: Level 1: Registering TruncatedNormal (None) in gradient.
tensorflow: Level 1: Registering RandomUniform (None) in gradient.
tensorflow: Level 1: Registering Multinomial (None) in gradient.
tensorflow: Level 1: Registering RandomGamma (None) in gradient.
tensorflow: Level 1: Registering Pack (<function _PackGrad at 0x7fa8a5e22158>) in gradient.
tensorflow: Level 1: Registering Unpack (<function _UnpackGrad at 0x7fa8a5dda950>) in gradient.
tensorflow: Level 1: Registering Concat (<function _ConcatGrad at 0x7fa8a5ddaa60>) in gradient.
tensorflow: Level 1: Registering ConcatV2 (<function _ConcatGradV2 at 0x7fa8a5ddaae8>) in gradient.
tensorflow: Level 1: Registering ConcatOffset (None) in gradient.
tensorflow: Level 1: Registering Slice (<function _SliceGrad at 0x7fa8a5ddab70>) in gradient.
tensorflow: Level 1: Registering StridedSlice (<function _StridedSliceGrad at 0x7fa8a5ddabf8>) in gradient.
tensorflow: Level 1: Registering StridedSliceGrad (<function _StridedSliceGradGrad at 0x7fa8a5ddac80>) in gradient.
tensorflow: Level 1: Registering Split (<function _SplitGrad at 0x7fa8a5ddad08>) in gradient.
tensorflow: Level 1: Registering SplitV (<function _SplitVGrad at 0x7fa8a5ddad90>) in gradient.
tensorflow: Level 1: Registering Const (None) in gradient.
tensorflow: Level 1: Registering Diag (<function _DiagGrad at 0x7fa8a5ddae18>) in gradient.
tensorflow: Level 1: Registering DiagPart (<function _DiagPartGrad at 0x7fa8a5ddaea0>) in gradient.
tensorflow: Level 1: Registering MatrixDiag (<function _MatrixDiagGrad at 0x7fa8a5ddaf28>) in gradient.
tensorflow: Level 1: Registering MatrixDiagPart (<function _MatrixDiagPartGrad at 0x7fa8a5df2048>) in gradient.
tensorflow: Level 1: Registering MatrixSetDiag (<function _MatrixSetDiagGrad at 0x7fa8a5df20d0>) in gradient.
tensorflow: Level 1: Registering MatrixBandPart (<function _MatrixBandPartGrad at 0x7fa8a5df2158>) in gradient.
tensorflow: Level 1: Registering EditDistance (None) in gradient.
tensorflow: Level 1: Registering Fill (<function _FillGrad at 0x7fa8a5df21e0>) in gradient.
tensorflow: Level 1: Registering ZerosLike (None) in gradient.
tensorflow: Level 1: Registering OnesLike (None) in gradient.
tensorflow: Level 1: Registering PreventGradient (<function _PreventGradientGrad at 0x7fa8a5df2268>) in gradient.
tensorflow: Level 1: Registering Gather (<function _GatherGrad at 0x7fa8a5df22f0>) in gradient.
tensorflow: Level 1: Registering GatherV2 (<function _GatherV2Grad at 0x7fa8a5df2378>) in gradient.
tensorflow: Level 1: Registering GatherNd (<function _GatherNdGrad at 0x7fa8a5df2400>) in gradient.
tensorflow: Level 1: Registering CheckNumerics (<function _CheckNumericsGrad at 0x7fa8a5df2488>) in gradient.
tensorflow: Level 1: Registering Identity (<function _IdGrad at 0x7fa8a5df2510>) in gradient.
tensorflow: Level 1: Registering PlaceholderWithDefault (<function _IdGrad at 0x7fa8a5df2510>) in gradient.
tensorflow: Level 1: Registering RefIdentity (<function _RefIdGrad at 0x7fa8a5df2598>) in gradient.
tensorflow: Level 1: Registering IdentityN (<function _IdNGrad at 0x7fa8a5df2620>) in gradient.
tensorflow: Level 1: Registering StopGradient (None) in gradient.
tensorflow: Level 1: Registering Reshape (<function _ReshapeGrad at 0x7fa8a5df26a8>) in gradient.
tensorflow: Level 1: Registering InvertPermutation (None) in gradient.
tensorflow: Level 1: Registering ExpandDims (<function _ExpandDimsGrad at 0x7fa8a5df27b8>) in gradient.
tensorflow: Level 1: Registering Squeeze (<function _SqueezeGrad at 0x7fa8a5df2840>) in gradient.
tensorflow: Level 1: Registering Transpose (<function _TransposeGrad at 0x7fa8a5df28c8>) in gradient.
tensorflow: Level 1: Registering ConjugateTranspose (<function _ConjugateTransposeGrad at 0x7fa8a5df2950>) in gradient.
tensorflow: Level 1: Registering Shape (None) in gradient.
tensorflow: Level 1: Registering ShapeN (None) in gradient.
tensorflow: Level 1: Registering Rank (None) in gradient.
tensorflow: Level 1: Registering Size (None) in gradient.
tensorflow: Level 1: Registering Tile (<function _TileGrad at 0x7fa8a5df29d8>) in gradient.
tensorflow: Level 1: Registering BroadcastGradientArgs (None) in gradient.
tensorflow: Level 1: Registering Pad (<function _PadGrad at 0x7fa8a5df2a60>) in gradient.
tensorflow: Level 1: Registering PadV2 (<function _PadGrad at 0x7fa8a5df2a60>) in gradient.
tensorflow: Level 1: Registering ReverseSequence (<function _ReverseSequenceGrad at 0x7fa8a5df2ae8>) in gradient.
tensorflow: Level 1: Registering Reverse (<function _ReverseGrad at 0x7fa8a5df2b70>) in gradient.
tensorflow: Level 1: Registering ReverseV2 (<function _ReverseV2Grad at 0x7fa8a5df2bf8>) in gradient.
tensorflow: Level 1: Registering SpaceToBatch (<function _SpaceToBatchGrad at 0x7fa8a5df2c80>) in gradient.
tensorflow: Level 1: Registering SpaceToBatchND (<function _SpaceToBatchNDGrad at 0x7fa8a5df2d08>) in gradient.
tensorflow: Level 1: Registering BatchToSpace (<function _BatchToSpaceGrad at 0x7fa8a5df2d90>) in gradient.
tensorflow: Level 1: Registering BatchToSpaceND (<function _BatchToSpaceNDGrad at 0x7fa8a5df2e18>) in gradient.
tensorflow: Level 1: Registering SpaceToDepth (<function _SpaceToDepthGrad at 0x7fa8a5df2ea0>) in gradient.
tensorflow: Level 1: Registering DepthToSpace (<function _DepthToSpaceGrad at 0x7fa8a5df2f28>) in gradient.
tensorflow: Level 1: Registering OneHot (None) in gradient.
tensorflow: Level 1: Registering MirrorPad (<function _MirrorPadGrad at 0x7fa8a5df7048>) in gradient.
tensorflow: Level 1: Registering MirrorPadGrad (<function _MirrorPadGradGrad at 0x7fa8a5df70d0>) in gradient.
tensorflow: Level 1: Registering QuantizeAndDequantize (<function _QuantizeAndDequantizeGrad at 0x7fa8a5df7158>) in gradient.
tensorflow: Level 1: Registering QuantizeAndDequantizeV2 (<function _QuantizeAndDequantizeV2Grad at 0x7fa8a5df71e0>) in gradient.
tensorflow: Level 1: Registering QuantizeAndDequantizeV3 (<function _QuantizeAndDequantizeV3Grad at 0x7fa8a5df7268>) in gradient.
tensorflow: Level 1: Registering ExtractImagePatches (<function _ExtractImagePatchesGrad at 0x7fa8a5df72f0>) in gradient.
tensorflow: Level 1: Registering ScatterNd (<function _ScatterNdGrad at 0x7fa8a5df7378>) in gradient.
tensorflow: Level 1: Registering ScatterNdNonAliasingAdd (<function _ScatterNdNonAliasingAddGrad at 0x7fa8a5df7400>) in gradient.
tensorflow: Level 1: Registering DynamicPartition (<function _DynamicPartitionGrads at 0x7fa8a5df7510>) in gradient.
tensorflow: Level 1: Registering ParallelDynamicStitch (<function _DynamicStitchGrads at 0x7fa8a5d99bf8>) in gradient.
tensorflow: Level 1: Registering DynamicStitch (<function _DynamicStitchGrads at 0x7fa8a5d99bf8>) in gradient.
tensorflow: Level 1: Registering Queue (None) in gradient.
tensorflow: Level 1: Registering QueueEnqueue (None) in gradient.
tensorflow: Level 1: Registering QueueEnqueueMany (None) in gradient.
tensorflow: Level 1: Registering QueueDequeue (None) in gradient.
tensorflow: Level 1: Registering QueueDequeueMany (None) in gradient.
tensorflow: Level 1: Registering QueueDequeueUpTo (None) in gradient.
tensorflow: Level 1: Registering QueueClose (None) in gradient.
tensorflow: Level 1: Registering QueueSize (None) in gradient.
tensorflow: Level 1: Registering Stack (None) in gradient.
tensorflow: Level 1: Registering StackPush (None) in gradient.
tensorflow: Level 1: Registering StackPop (None) in gradient.
tensorflow: Level 1: Registering StackClose (None) in gradient.
tensorflow: Level 1: Registering GetSessionHandle (None) in gradient.
tensorflow: Level 1: Registering GetSessionHandleV2 (None) in gradient.
tensorflow: Level 1: Registering GetSessionTensor (None) in gradient.
tensorflow: Level 1: Registering DeleteSessionTensor (None) in gradient.
tensorflow: Level 1: Registering Roll (<function _RollGrad at 0x7fa8a5d99c80>) in gradient.
tensorflow: Level 1: Registering ArgMax (<function _ArgMaxGrad at 0x7fa8a5da8598>) in gradient.
tensorflow: Level 1: Registering ArgMin (<function _ArgMinGrad at 0x7fa8a5da8c80>) in gradient.
tensorflow: Level 1: Registering Sum (<function _SumGrad at 0x7fa8a5da8d08>) in gradient.
tensorflow: Level 1: Registering Max (<function _MaxGrad at 0x7fa8a5da8e18>) in gradient.
tensorflow: Level 1: Registering Min (<function _MinGrad at 0x7fa8a5da8ea0>) in gradient.
tensorflow: Level 1: Registering Mean (<function _MeanGrad at 0x7fa8a5da8f28>) in gradient.
tensorflow: Level 1: Registering Prod (<function _ProdGrad at 0x7fa8a5d4f048>) in gradient.
tensorflow: Level 1: Registering SegmentSum (<function _SegmentSumGrad at 0x7fa8a5d4f0d0>) in gradient.
tensorflow: Level 1: Registering SegmentMean (<function _SegmentMeanGrad at 0x7fa8a5d4f158>) in gradient.
tensorflow: Level 1: Registering SparseSegmentSum (<function _SparseSegmentSumGrad at 0x7fa8a5d4f1e0>) in gradient.
tensorflow: Level 1: Registering SparseSegmentSumWithNumSegments (<function _SparseSegmentSumWithNumSegmentsGrad at 0x7fa8a5d4f268>) in gradient.
tensorflow: Level 1: Registering SparseSegmentMean (<function _SparseSegmentMeanGrad at 0x7fa8a5d4f2f0>) in gradient.
tensorflow: Level 1: Registering SparseSegmentMeanWithNumSegments (<function _SparseSegmentMeanWithNumSegmentsGrad at 0x7fa8a5d4f378>) in gradient.
tensorflow: Level 1: Registering SparseSegmentSqrtN (<function _SparseSegmentSqrtNGrad at 0x7fa8a5d4f400>) in gradient.
tensorflow: Level 1: Registering SparseSegmentSqrtNWithNumSegments (<function _SparseSegmentSqrtNWithNumSegmentsGrad at 0x7fa8a5d4f488>) in gradient.
tensorflow: Level 1: Registering SegmentMin (<function _SegmentMinGrad at 0x7fa8a5d4f598>) in gradient.
tensorflow: Level 1: Registering SegmentMax (<function _SegmentMaxGrad at 0x7fa8a5d4f620>) in gradient.
tensorflow: Level 1: Registering UnsortedSegmentSum (<function _UnsortedSegmentSumGrad at 0x7fa8a5d4f7b8>) in gradient.
tensorflow: Level 1: Registering UnsortedSegmentMax (<function _UnsortedSegmentMaxGrad at 0x7fa8a5d4f840>) in gradient.
tensorflow: Level 1: Registering UnsortedSegmentMin (<function _UnsortedSegmentMinGrad at 0x7fa8a5d4f8c8>) in gradient.
tensorflow: Level 1: Registering UnsortedSegmentProd (<function _UnsortedSegmentProdGrad at 0x7fa8a5d4f950>) in gradient.
tensorflow: Level 1: Registering Abs (<function _AbsGrad at 0x7fa8a5d4f9d8>) in gradient.
tensorflow: Level 1: Registering Neg (<function _NegGrad at 0x7fa8a5d4fa60>) in gradient.
tensorflow: Level 1: Registering Inv (<function _InvGrad at 0x7fa8a5d4fae8>) in gradient.
tensorflow: Level 1: Registering Reciprocal (<function _ReciprocalGrad at 0x7fa8a5d4fb70>) in gradient.
tensorflow: Level 1: Registering InvGrad (<function _InvGradGrad at 0x7fa8a5d4fbf8>) in gradient.
tensorflow: Level 1: Registering ReciprocalGrad (<function _ReciprocalGradGrad at 0x7fa8a5d4fc80>) in gradient.
tensorflow: Level 1: Registering Square (<function _SquareGrad at 0x7fa8a5d4fd08>) in gradient.
tensorflow: Level 1: Registering Sqrt (<function _SqrtGrad at 0x7fa8a5d4fd90>) in gradient.
tensorflow: Level 1: Registering SqrtGrad (<function _SqrtGradGrad at 0x7fa8a5d4fe18>) in gradient.
tensorflow: Level 1: Registering Rsqrt (<function _RsqrtGrad at 0x7fa8a5d4fea0>) in gradient.
tensorflow: Level 1: Registering RsqrtGrad (<function _RsqrtGradGrad at 0x7fa8a5d4ff28>) in gradient.
tensorflow: Level 1: Registering Exp (<function _ExpGrad at 0x7fa8a5d51048>) in gradient.
tensorflow: Level 1: Registering Expm1 (<function _Expm1Grad at 0x7fa8a5d510d0>) in gradient.
tensorflow: Level 1: Registering Log (<function _LogGrad at 0x7fa8a5d51158>) in gradient.
tensorflow: Level 1: Registering Log1p (<function _Log1pGrad at 0x7fa8a5d511e0>) in gradient.
tensorflow: Level 1: Registering Sinh (<function _SinhGrad at 0x7fa8a5d51268>) in gradient.
tensorflow: Level 1: Registering Cosh (<function _CoshGrad at 0x7fa8a5d512f0>) in gradient.
tensorflow: Level 1: Registering Tanh (<function _TanhGrad at 0x7fa8a5d51378>) in gradient.
tensorflow: Level 1: Registering Asinh (<function _AsinhGrad at 0x7fa8a5d51400>) in gradient.
tensorflow: Level 1: Registering Acosh (<function _AcoshGrad at 0x7fa8a5d51488>) in gradient.
tensorflow: Level 1: Registering Atanh (<function _AtanhGrad at 0x7fa8a5d51510>) in gradient.
tensorflow: Level 1: Registering TanhGrad (<function _TanhGradGrad at 0x7fa8a5d51598>) in gradient.
tensorflow: Level 1: Registering Erf (<function _ErfGrad at 0x7fa8a5d51620>) in gradient.
tensorflow: Level 1: Registering Erfc (<function _ErfcGrad at 0x7fa8a5d516a8>) in gradient.
tensorflow: Level 1: Registering Lgamma (<function _LgammaGrad at 0x7fa8a5d51730>) in gradient.
tensorflow: Level 1: Registering Digamma (<function _DigammaGrad at 0x7fa8a5d517b8>) in gradient.
tensorflow: Level 1: Registering Igamma (<function _IgammaGrad at 0x7fa8a5d51840>) in gradient.
tensorflow: Level 1: Registering Igammac (<function _IgammacGrad at 0x7fa8a5d518c8>) in gradient.
tensorflow: Level 1: Registering Betainc (<function _BetaincGrad at 0x7fa8a5d51950>) in gradient.
tensorflow: Level 1: Registering Zeta (<function _ZetaGrad at 0x7fa8a5d519d8>) in gradient.
tensorflow: Level 1: Registering Polygamma (<function _PolygammaGrad at 0x7fa8a5d51a60>) in gradient.
tensorflow: Level 1: Registering Sigmoid (<function _SigmoidGrad at 0x7fa8a5d51ae8>) in gradient.
tensorflow: Level 1: Registering SigmoidGrad (<function _SigmoidGradGrad at 0x7fa8a5d51b70>) in gradient.
tensorflow: Level 1: Registering Sign (<function _SignGrad at 0x7fa8a5d51bf8>) in gradient.
tensorflow: Level 1: Registering Sin (<function _SinGrad at 0x7fa8a5d51c80>) in gradient.
tensorflow: Level 1: Registering Cos (<function _CosGrad at 0x7fa8a5d51d08>) in gradient.
tensorflow: Level 1: Registering Tan (<function _TanGrad at 0x7fa8a5d51d90>) in gradient.
tensorflow: Level 1: Registering Asin (<function _AsinGrad at 0x7fa8a5d51e18>) in gradient.
tensorflow: Level 1: Registering Acos (<function _AcosGrad at 0x7fa8a5d51ea0>) in gradient.
tensorflow: Level 1: Registering Atan (<function _AtanGrad at 0x7fa8a5d51f28>) in gradient.
tensorflow: Level 1: Registering Atan2 (<function _Atan2Grad at 0x7fa8a5d56048>) in gradient.
tensorflow: Level 1: Registering AddN (<function _AddNGrad at 0x7fa8a5d560d0>) in gradient.
tensorflow: Level 1: Registering Add (<function _AddGrad at 0x7fa8a5d561e0>) in gradient.
tensorflow: Level 1: Registering Sub (<function _SubGrad at 0x7fa8a5d56268>) in gradient.
tensorflow: Level 1: Registering Mul (<function _MulGrad at 0x7fa8a5d562f0>) in gradient.
tensorflow: Level 1: Registering Div (<function _DivGrad at 0x7fa8a5d56378>) in gradient.
tensorflow: Level 1: Registering FloorDiv (<function _FloorDivGrad at 0x7fa8a5d56400>) in gradient.
tensorflow: Level 1: Registering FloorMod (<function _FloorModGrad at 0x7fa8a5d56488>) in gradient.
tensorflow: Level 1: Registering TruncateDiv (<function _TruncateDivGrad at 0x7fa8a5d56510>) in gradient.
tensorflow: Level 1: Registering RealDiv (<function _RealDivGrad at 0x7fa8a5d56598>) in gradient.
tensorflow: Level 1: Registering Pow (<function _PowGrad at 0x7fa8a5d56620>) in gradient.
tensorflow: Level 1: Registering Maximum (<function _MaximumGrad at 0x7fa8a5d56730>) in gradient.
tensorflow: Level 1: Registering Minimum (<function _MinimumGrad at 0x7fa8a5d567b8>) in gradient.
tensorflow: Level 1: Registering SquaredDifference (<function _SquaredDifferenceGrad at 0x7fa8a5d56840>) in gradient.
tensorflow: Level 1: Registering Less (None) in gradient.
tensorflow: Level 1: Registering LessEqual (None) in gradient.
tensorflow: Level 1: Registering Greater (None) in gradient.
tensorflow: Level 1: Registering GreaterEqual (None) in gradient.
tensorflow: Level 1: Registering Equal (None) in gradient.
tensorflow: Level 1: Registering ApproximateEqual (None) in gradient.
tensorflow: Level 1: Registering NotEqual (None) in gradient.
tensorflow: Level 1: Registering LogicalAnd (None) in gradient.
tensorflow: Level 1: Registering LogicalOr (None) in gradient.
tensorflow: Level 1: Registering LogicalNot (None) in gradient.
tensorflow: Level 1: Registering Select (<function _SelectGrad at 0x7fa8a5d568c8>) in gradient.
tensorflow: Level 1: Registering MatMul (<function _MatMulGrad at 0x7fa8a5d56950>) in gradient.
tensorflow: Level 1: Registering SparseMatMul (<function _SparseMatMulGrad at 0x7fa8a5d569d8>) in gradient.
tensorflow: Level 1: Registering Floor (<function _FloorGrad at 0x7fa8a5d56a60>) in gradient.
tensorflow: Level 1: Registering Ceil (<function _CeilGrad at 0x7fa8a5d56ae8>) in gradient.
tensorflow: Level 1: Registering Round (<function _RoundGrad at 0x7fa8a5d56b70>) in gradient.
tensorflow: Level 1: Registering Rint (<function _RintGrad at 0x7fa8a5d56bf8>) in gradient.
tensorflow: Level 1: Registering BatchMatMul (<function _BatchMatMul at 0x7fa8a5d56c80>) in gradient.
tensorflow: Level 1: Registering Range (None) in gradient.
tensorflow: Level 1: Registering LinSpace (None) in gradient.
tensorflow: Level 1: Registering Complex (<function _ComplexGrad at 0x7fa8a5d56d08>) in gradient.
tensorflow: Level 1: Registering Real (<function _RealGrad at 0x7fa8a5d56d90>) in gradient.
tensorflow: Level 1: Registering Imag (<function _ImagGrad at 0x7fa8a5d56e18>) in gradient.
tensorflow: Level 1: Registering Angle (<function _AngleGrad at 0x7fa8a5d56ea0>) in gradient.
tensorflow: Level 1: Registering Conj (<function _ConjGrad at 0x7fa8a5d56f28>) in gradient.
tensorflow: Level 1: Registering ComplexAbs (<function _ComplexAbsGrad at 0x7fa8a5d58048>) in gradient.
tensorflow: Level 1: Registering Cast (<function _CastGrad at 0x7fa8a5d580d0>) in gradient.
tensorflow: Level 1: Registering Cross (<function _CrossGrad at 0x7fa8a5d58158>) in gradient.
tensorflow: Level 1: Registering Cumsum (<function _CumsumGrad at 0x7fa8a5d581e0>) in gradient.
tensorflow: Level 1: Registering Cumprod (<function _CumprodGrad at 0x7fa8a5d58268>) in gradient.
tensorflow: Level 1: Registering SparseAddGrad (None) in gradient.
tensorflow: Level 1: Registering SparseConcat (None) in gradient.
tensorflow: Level 1: Registering SparseToDense (None) in gradient.
tensorflow: Level 1: Registering SparseReorder (<function _SparseReorderGrad at 0x7fa8a5d58a60>) in gradient.
tensorflow: Level 1: Registering SparseAdd (<function _SparseAddGrad at 0x7fa8a5d58ae8>) in gradient.
tensorflow: Level 1: Registering SparseTensorDenseAdd (<function _SparseTensorDenseAddGrad at 0x7fa8a5d58b70>) in gradient.
tensorflow: Level 1: Registering SparseReduceSum (<function _SparseReduceSumGrad at 0x7fa8a5d58bf8>) in gradient.
tensorflow: Level 1: Registering SparseTensorDenseMatMul (<function _SparseTensorDenseMatMulGrad at 0x7fa8a5d58c80>) in gradient.
tensorflow: Level 1: Registering SparseDenseCwiseAdd (<function _SparseDenseCwiseAddGrad at 0x7fa8a5d58d08>) in gradient.
tensorflow: Level 1: Registering SparseDenseCwiseMul (<function _SparseDenseCwiseMulGrad at 0x7fa8a5d58e18>) in gradient.
tensorflow: Level 1: Registering SparseDenseCwiseDiv (<function _SparseDenseCwiseDivGrad at 0x7fa8a5d58ea0>) in gradient.
tensorflow: Level 1: Registering SparseSoftmax (<function _SparseSoftmaxGrad at 0x7fa8a5d58f28>) in gradient.
tensorflow: Level 1: Registering SparseSparseMaximum (<function _SparseSparseMaximumGrad at 0x7fa8a5d63048>) in gradient.
tensorflow: Level 1: Registering SparseSparseMinimum (<function _SparseSparseMinimumGrad at 0x7fa8a5d630d0>) in gradient.
tensorflow: Level 1: Registering SparseFillEmptyRows (<function _SparseFillEmptyRowsGrad at 0x7fa8a5d63158>) in gradient.
tensorflow: Level 1: Registering FFT (<function _FFTGrad at 0x7fa8a5d639d8>) in gradient.
tensorflow: Level 1: Registering IFFT (<function _IFFTGrad at 0x7fa8a5d6f048>) in gradient.
tensorflow: Level 1: Registering FFT2D (<function _FFT2DGrad at 0x7fa8a5d6f0d0>) in gradient.
tensorflow: Level 1: Registering IFFT2D (<function _IFFT2DGrad at 0x7fa8a5d6f158>) in gradient.
tensorflow: Level 1: Registering FFT3D (<function _FFT3DGrad at 0x7fa8a5d6f1e0>) in gradient.
tensorflow: Level 1: Registering IFFT3D (<function _IFFT3DGrad at 0x7fa8a5d6f268>) in gradient.
tensorflow: Level 1: Registering RFFT (<function _RFFTGradHelper.._Grad at 0x7fa8a5d6f400>) in gradient.
tensorflow: Level 1: Registering IRFFT (<function _IRFFTGradHelper.._Grad at 0x7fa8a5d6f488>) in gradient.
tensorflow: Level 1: Registering RFFT2D (<function _RFFTGradHelper.._Grad at 0x7fa8a5d6f510>) in gradient.
tensorflow: Level 1: Registering IRFFT2D (<function _IRFFTGradHelper.._Grad at 0x7fa8a5d6f598>) in gradient.
tensorflow: Level 1: Registering Assign (None) in gradient.
tensorflow: Level 1: Registering AssignAdd (None) in gradient.
tensorflow: Level 1: Registering AssignSub (None) in gradient.
tensorflow: Level 1: Registering ScatterAdd (None) in gradient.
tensorflow: Level 1: Registering ScatterSub (None) in gradient.
tensorflow: Level 1: Registering ScatterMul (None) in gradient.
tensorflow: Level 1: Registering ScatterDiv (None) in gradient.
tensorflow: Level 1: Registering ScatterNdUpdate (None) in gradient.
tensorflow: Level 1: Registering ScatterNdAdd (None) in gradient.
tensorflow: Level 1: Registering ScatterNdSub (None) in gradient.
tensorflow: Level 1: Registering ScatterNdMul (None) in gradient.
tensorflow: Level 1: Registering ScatterNdDiv (None) in gradient.
tensorflow: Level 1: Registering TensorArray (None) in gradient.
tensorflow: Level 1: Registering TensorArrayGrad (None) in gradient.
tensorflow: Level 1: Registering TensorArraySize (None) in gradient.
tensorflow: Level 1: Registering TensorArrayClose (None) in gradient.
tensorflow: Level 1: Registering TensorArrayV2 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayGradV2 (None) in gradient.
tensorflow: Level 1: Registering TensorArraySizeV2 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayCloseV2 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayV3 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayGradV3 (None) in gradient.
tensorflow: Level 1: Registering TensorArraySizeV3 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayCloseV3 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayReadV3 (<function _TensorArrayReadGrad at 0x7fa8a5d6fbf8>) in gradient.
tensorflow: Level 1: Registering TensorArrayReadV2 (<function _TensorArrayReadGrad at 0x7fa8a5d6fbf8>) in gradient.
tensorflow: Level 1: Registering TensorArrayRead (<function _TensorArrayReadGrad at 0x7fa8a5d6fbf8>) in gradient.
tensorflow: Level 1: Registering TensorArrayWriteV3 (<function _TensorArrayWriteGrad at 0x7fa8a5d6fc80>) in gradient.
tensorflow: Level 1: Registering TensorArrayWriteV2 (<function _TensorArrayWriteGrad at 0x7fa8a5d6fc80>) in gradient.
tensorflow: Level 1: Registering TensorArrayWrite (<function _TensorArrayWriteGrad at 0x7fa8a5d6fc80>) in gradient.
tensorflow: Level 1: Registering TensorArrayGatherV3 (<function _TensorArrayGatherGrad at 0x7fa8a5d6fd08>) in gradient.
tensorflow: Level 1: Registering TensorArrayGatherV2 (<function _TensorArrayGatherGrad at 0x7fa8a5d6fd08>) in gradient.
tensorflow: Level 1: Registering TensorArrayGather (<function _TensorArrayGatherGrad at 0x7fa8a5d6fd08>) in gradient.
tensorflow: Level 1: Registering TensorArrayScatterV3 (<function _TensorArrayScatterGrad at 0x7fa8a5d6fd90>) in gradient.
tensorflow: Level 1: Registering TensorArrayScatterV2 (<function _TensorArrayScatterGrad at 0x7fa8a5d6fd90>) in gradient.
tensorflow: Level 1: Registering TensorArrayScatter (<function _TensorArrayScatterGrad at 0x7fa8a5d6fd90>) in gradient.
tensorflow: Level 1: Registering TensorArrayConcatV3 (<function _TensorArrayConcatGrad at 0x7fa8a5d6fe18>) in gradient.
tensorflow: Level 1: Registering TensorArrayConcatV2 (<function _TensorArrayConcatGrad at 0x7fa8a5d6fe18>) in gradient.
tensorflow: Level 1: Registering TensorArrayConcat (<function _TensorArrayConcatGrad at 0x7fa8a5d6fe18>) in gradient.
tensorflow: Level 1: Registering TensorArraySplitV3 (<function _TensorArraySplitGrad at 0x7fa8a5d6fea0>) in gradient.
tensorflow: Level 1: Registering TensorArraySplitV2 (<function _TensorArraySplitGrad at 0x7fa8a5d6fea0>) in gradient.
tensorflow: Level 1: Registering TensorArraySplit (<function _TensorArraySplitGrad at 0x7fa8a5d6fea0>) in gradient.
tensorflow: Level 1: Registering ClipByValue (<function _ClipByValueGrad at 0x7fa8a5cfd158>) in gradient.
tensorflow: Level 1: Registering Switch (<function _SwitchGrad at 0x7fa8a5d27400>) in gradient.
tensorflow: Level 1: Registering RefSwitch (<function _SwitchGrad at 0x7fa8a5d27400>) in gradient.
tensorflow: Level 1: Registering Merge (<function _MergeGrad at 0x7fa8a5cca7b8>) in gradient.
tensorflow: Level 1: Registering RefMerge (<function _RefMergeGrad at 0x7fa8a5cca950>) in gradient.
tensorflow: Level 1: Registering Exit (<function _ExitGrad at 0x7fa8a5cca9d8>) in gradient.
tensorflow: Level 1: Registering RefExit (<function _ExitGrad at 0x7fa8a5cca9d8>) in gradient.
tensorflow: Level 1: Registering NextIteration (<function _NextIterationGrad at 0x7fa8a5cca840>) in gradient.
tensorflow: Level 1: Registering RefNextIteration (<function _RefNextIterationGrad at 0x7fa8a5ccaae8>) in gradient.
tensorflow: Level 1: Registering Enter (<function _EnterGrad at 0x7fa8a5ccab70>) in gradient.
tensorflow: Level 1: Registering RefEnter (<function _RefEnterGrad at 0x7fa8a5ccabf8>) in gradient.
tensorflow: Level 1: Registering LoopCond (<function _LoopCondGrad at 0x7fa8a5ccac80>) in gradient.
tensorflow: Level 1: Registering ResizeNearestNeighbor (<function _ResizeNearestNeighborGrad at 0x7fa8a5ccaa60>) in gradient.
tensorflow: Level 1: Registering ResizeBilinear (<function _ResizeBilinearGrad at 0x7fa8a5cf98c8>) in gradient.
tensorflow: Level 1: Registering ResizeBicubic (<function _ResizeBicubicGrad at 0x7fa8a5cf99d8>) in gradient.
tensorflow: Level 1: Registering CropAndResize (<function _CropAndResizeGrad at 0x7fa8a5cf9a60>) in gradient.
tensorflow: Level 1: Registering MatrixInverse (<function _MatrixInverseGrad at 0x7fa8a5cf9c80>) in gradient.
tensorflow: Level 1: Registering MatrixDeterminant (<function _MatrixDeterminantGrad at 0x7fa8a5c95488>) in gradient.
tensorflow: Level 1: Registering Cholesky (<function _CholeskyGrad at 0x7fa8a5c95510>) in gradient.
tensorflow: Level 1: Registering Qr (<function _QrGrad at 0x7fa8a5c95598>) in gradient.
tensorflow: Level 1: Registering MatrixSolve (<function _MatrixSolveGrad at 0x7fa8a5c956a8>) in gradient.
tensorflow: Level 1: Registering MatrixSolveLs (<function _MatrixSolveLsGrad at 0x7fa8a5c95730>) in gradient.
tensorflow: Level 1: Registering MatrixTriangularSolve (<function _MatrixTriangularSolveGrad at 0x7fa8a5c957b8>) in gradient.
tensorflow: Level 1: Registering SelfAdjointEigV2 (<function _SelfAdjointEigV2Grad at 0x7fa8a5c95840>) in gradient.
tensorflow: Level 1: Registering Svd (<function _SvdGrad at 0x7fa8a5c958c8>) in gradient.
tensorflow: Level 1: Registering Print (<function _PrintGrad at 0x7fa8a5c95b70>) in gradient.
tensorflow: Level 1: Registering HistogramSummary (None) in gradient.
tensorflow: Level 1: Registering ImageSummary (None) in gradient.
tensorflow: Level 1: Registering AudioSummary (None) in gradient.
tensorflow: Level 1: Registering AudioSummaryV2 (None) in gradient.
tensorflow: Level 1: Registering MergeSummary (None) in gradient.
tensorflow: Level 1: Registering ScalarSummary (None) in gradient.
tensorflow: Level 1: Registering Timestamp (None) in gradient.
tensorflow: Level 1: Registering ReaderRead (None) in gradient.
tensorflow: Level 1: Registering ReaderReadUpTo (None) in gradient.
tensorflow: Level 1: Registering ReaderNumRecordsProduced (None) in gradient.
tensorflow: Level 1: Registering ReaderNumWorkUnitsCompleted (None) in gradient.
tensorflow: Level 1: Registering ReaderSerializeState (None) in gradient.
tensorflow: Level 1: Registering ReaderRestoreState (None) in gradient.
tensorflow: Level 1: Registering ReaderReset (None) in gradient.
tensorflow: Level 1: Registering WholeFileReader (None) in gradient.
tensorflow: Level 1: Registering TextLineReader (None) in gradient.
tensorflow: Level 1: Registering FixedLengthRecordReader (None) in gradient.
tensorflow: Level 1: Registering TFRecordReader (None) in gradient.
tensorflow: Level 1: Registering LMDBReader (None) in gradient.
tensorflow: Level 1: Registering IdentityReader (None) in gradient.
tensorflow: Level 1: Registering RegexReplace (None) in gradient.
tensorflow: Level 1: Registering StringToHashBucket (None) in gradient.
tensorflow: Level 1: Registering StringToHashBucketFast (None) in gradient.
tensorflow: Level 1: Registering StringToHashBucketStrong (None) in gradient.
tensorflow: Level 1: Registering ReduceJoin (None) in gradient.
tensorflow: Level 1: Registering StringJoin (None) in gradient.
tensorflow: Level 1: Registering StringSplit (None) in gradient.
tensorflow: Level 1: Registering AsString (None) in gradient.
tensorflow: Level 1: Registering EncodeBase64 (None) in gradient.
tensorflow: Level 1: Registering DecodeBase64 (None) in gradient.
tensorflow: Level 1: Registering LookupTableFind (None) in gradient.
tensorflow: Level 1: Registering LookupTableFindV2 (None) in gradient.
tensorflow: Level 1: Registering LookupTableInsert (None) in gradient.
tensorflow: Level 1: Registering LookupTableInsertV2 (None) in gradient.
tensorflow: Level 1: Registering LookupTableSize (None) in gradient.
tensorflow: Level 1: Registering LookupTableSizeV2 (None) in gradient.
tensorflow: Level 1: Registering HashTable (None) in gradient.
tensorflow: Level 1: Registering HashTableV2 (None) in gradient.
tensorflow: Level 1: Registering InitializeTable (None) in gradient.
tensorflow: Level 1: Registering InitializeTableV2 (None) in gradient.
tensorflow: Level 1: Registering InitializeTableFromTextFile (None) in gradient.
tensorflow: Level 1: Registering InitializeTableFromTextFileV2 (None) in gradient.
tensorflow: Level 1: Registering MutableDenseHashTable (None) in gradient.
tensorflow: Level 1: Registering MutableDenseHashTableV2 (None) in gradient.
tensorflow: Level 1: Registering MutableHashTable (None) in gradient.
tensorflow: Level 1: Registering MutableHashTableV2 (None) in gradient.
tensorflow: Level 1: Registering MutableHashTableOfTensors (None) in gradient.
tensorflow: Level 1: Registering MutableHashTableOfTensorsV2 (None) in gradient.
tensorflow: Level 1: Registering DecodeRaw (None) in gradient.
tensorflow: Level 1: Registering ParseTensor (None) in gradient.
tensorflow: Level 1: Registering SerializeTensor (None) in gradient.
tensorflow: Level 1: Registering StringToNumber (None) in gradient.
tensorflow: Level 1: Registering PyFunc (None) in gradient.
tensorflow: Level 1: Registering PyFuncStateless (None) in gradient.
tensorflow: Level 1: Registering Conv2D,flops (<function _calc_conv_flops at 0x7fa8a5831f28>) in statistical functions.
tensorflow: Level 1: Registering DepthwiseConv2dNative,flops (<function _calc_depthwise_conv_flops at 0x7fa8a5824b70>) in statistical functions.
tensorflow: Level 1: Registering BiasAdd,flops (<function _calc_bias_add_flops at 0x7fa8a5824bf8>) in statistical functions.
tensorflow: Level 1: Registering Dilation2D,flops (<function _calc_dilation2d_flops at 0x7fa8a57e5268>) in statistical functions.
tensorflow: Level 1: Registering Conv2DBackpropInput (<function _Conv2DBackpropInputGrad at 0x7fa8a58a52f0>) in gradient.
tensorflow: Level 1: Registering Conv2DBackpropFilter (<function _Conv2DBackpropFilterGrad at 0x7fa8a57e5400>) in gradient.
tensorflow: Level 1: Registering Conv3D (<function _Conv3DGrad at 0x7fa8a57e5488>) in gradient.
tensorflow: Level 1: Registering Conv3DBackpropInputV2 (<function _Conv3DBackpropInputGrad at 0x7fa8a57e5510>) in gradient.
tensorflow: Level 1: Registering Conv3DBackpropFilterV2 (<function _Conv3DBackpropFilterGrad at 0x7fa8a57e5598>) in gradient.
tensorflow: Level 1: Registering AvgPool3D (<function _AvgPool3DGrad at 0x7fa8a57e5620>) in gradient.
tensorflow: Level 1: Registering AvgPool3DGrad (<function _AvgPool3DGradGrad at 0x7fa8a57e56a8>) in gradient.
tensorflow: Level 1: Registering MaxPool3D (<function _MaxPool3DGrad at 0x7fa8a57e5730>) in gradient.
tensorflow: Level 1: Registering MaxPool3DGrad (<function _MaxPool3DGradGrad at 0x7fa8a57e57b8>) in gradient.
tensorflow: Level 1: Registering MaxPool3DGradGrad (<function _MaxPool3DGradGradGrad at 0x7fa8a57e5840>) in gradient.
tensorflow: Level 1: Registering Softmax (<function _SoftmaxGrad at 0x7fa8a57e58c8>) in gradient.
tensorflow: Level 1: Registering LogSoftmax (<function _LogSoftmaxGrad at 0x7fa8a57e5950>) in gradient.
tensorflow: Level 1: Registering BiasAdd (<function _BiasAddGrad at 0x7fa8a57e59d8>) in gradient.
tensorflow: Level 1: Registering BiasAddGrad (<function _BiasAddGradGrad at 0x7fa8a57e5a60>) in gradient.
tensorflow: Level 1: Registering BiasAddV1 (<function _BiasAddGradV1 at 0x7fa8a57e5ae8>) in gradient.
tensorflow: Level 1: Registering Relu (<function _ReluGrad at 0x7fa8a57e5b70>) in gradient.
tensorflow: Level 1: Registering EluGrad (<function _EluGradGrad at 0x7fa8a57e5bf8>) in gradient.
tensorflow: Level 1: Registering SeluGrad (<function _SeluGradGrad at 0x7fa8a57e5c80>) in gradient.
tensorflow: Level 1: Registering Relu6 (<function _Relu6Grad at 0x7fa8a57e5d08>) in gradient.
tensorflow: Level 1: Registering Relu6Grad (<function _Relu6GradGrad at 0x7fa8a57e5d90>) in gradient.
tensorflow: Level 1: Registering Elu (<function _EluGrad at 0x7fa8a57e5e18>) in gradient.
tensorflow: Level 1: Registering Selu (<function _SeluGrad at 0x7fa8a57e5ea0>) in gradient.
tensorflow: Level 1: Registering Softplus (<function _SoftplusGrad at 0x7fa8a57e5f28>) in gradient.
tensorflow: Level 1: Registering SoftplusGrad (<function _SoftplusGradGrad at 0x7fa8a57e8048>) in gradient.
tensorflow: Level 1: Registering Softsign (<function _SoftsignGrad at 0x7fa8a57e80d0>) in gradient.
tensorflow: Level 1: Registering ReluGrad (<function _ReluGradGrad at 0x7fa8a57e8158>) in gradient.
tensorflow: Level 1: Registering SoftmaxCrossEntropyWithLogits (<function _SoftmaxCrossEntropyWithLogitsGrad at 0x7fa8a57e8268>) in gradient.
tensorflow: Level 1: Registering SparseSoftmaxCrossEntropyWithLogits (<function _SparseSoftmaxCrossEntropyWithLogitsGrad at 0x7fa8a57e82f0>) in gradient.
tensorflow: Level 1: Registering Conv2D (<function _Conv2DGrad at 0x7fa8a57e8378>) in gradient.
tensorflow: Level 1: Registering DepthwiseConv2dNative (<function _DepthwiseConv2dNativeGrad at 0x7fa8a57e8400>) in gradient.
tensorflow: Level 1: Registering Dilation2D (<function _Dilation2DGrad at 0x7fa8a57e8488>) in gradient.
tensorflow: Level 1: Registering LRN (<function _LRNGrad at 0x7fa8a57e8510>) in gradient.
tensorflow: Level 1: Registering AvgPool (<function _AvgPoolGrad at 0x7fa8a57e8598>) in gradient.
tensorflow: Level 1: Registering AvgPoolGrad (<function _AvgPoolGradGrad at 0x7fa8a57e8620>) in gradient.
tensorflow: Level 1: Registering MaxPool (<function _MaxPoolGrad at 0x7fa8a57e86a8>) in gradient.
tensorflow: Level 1: Registering MaxPoolV2 (<function _MaxPoolGradV2 at 0x7fa8a57e8730>) in gradient.
tensorflow: Level 1: Registering MaxPoolWithArgmax (<function _MaxPoolGradWithArgmax at 0x7fa8a57e87b8>) in gradient.
tensorflow: Level 1: Registering MaxPoolGrad (<function _MaxPoolGradGrad at 0x7fa8a57e8840>) in gradient.
tensorflow: Level 1: Registering MaxPoolGradV2 (<function _MaxPoolGradGradV2 at 0x7fa8a57e88c8>) in gradient.
tensorflow: Level 1: Registering MaxPoolGradGrad (<function _MaxPoolGradGradGrad at 0x7fa8a57e8950>) in gradient.
tensorflow: Level 1: Registering FractionalMaxPool (<function _FractionalMaxPoolGrad at 0x7fa8a57e89d8>) in gradient.
tensorflow: Level 1: Registering FractionalAvgPool (<function _FractionalAvgPoolGrad at 0x7fa8a57e8a60>) in gradient.
tensorflow: Level 1: Registering BatchNormWithGlobalNormalization (<function _BatchNormWithGlobalNormalizationGrad at 0x7fa8a57e8ae8>) in gradient.
tensorflow: Level 1: Registering FusedBatchNorm (<function _FusedBatchNormGrad at 0x7fa8a57e8bf8>) in gradient.
tensorflow: Level 1: Registering FusedBatchNormV2 (<function _FusedBatchNormV2Grad at 0x7fa8a57e8c80>) in gradient.
tensorflow: Level 1: Registering FusedBatchNormGrad (<function _FusedBatchNormGradGrad at 0x7fa8a57e8d90>) in gradient.
tensorflow: Level 1: Registering FusedBatchNormGradV2 (<function _FusedBatchNormGradGradV2 at 0x7fa8a57e8e18>) in gradient.
tensorflow: Level 1: Registering L2Loss (<function _L2LossGrad at 0x7fa8a57e8ea0>) in gradient.
tensorflow: Level 1: Registering TopKV2 (<function _TopKGrad at 0x7fa8a57e8f28>) in gradient.
tensorflow: Level 1: Registering TopK (<function _TopKGrad at 0x7fa8a57e8f28>) in gradient.
tensorflow: Level 1: Registering NthElement (<function _NthElementGrad at 0x7fa8a57ec048>) in gradient.
tensorflow: Level 1: Registering CTCLoss (<function _CTCLossGrad at 0x7fa8a57ec0d0>) in gradient.
tensorflow: Level 1: Registering CTCGreedyDecoder (None) in gradient.
tensorflow: Level 1: Registering CTCBeamSearchDecoder (None) in gradient.
tensorflow: Level 1: Registering RandomCrop (None) in gradient.
tensorflow: Level 1: Registering RGBToHSV (None) in gradient.
tensorflow: Level 1: Registering HSVToRGB (None) in gradient.
tensorflow: Level 1: Registering DrawBoundingBoxes (None) in gradient.
tensorflow: Level 1: Registering SampleDistortedBoundingBox (None) in gradient.
tensorflow: Level 1: Registering SampleDistortedBoundingBoxV2 (None) in gradient.
tensorflow: Level 1: Registering ExtractGlimpse (None) in gradient.
tensorflow: Level 1: Registering NonMaxSuppression (None) in gradient.
tensorflow: Level 1: Registering NonMaxSuppressionV2 (None) in gradient.
tensorflow: Level 1: Registering SetSize (None) in gradient.
tensorflow: Level 1: Registering DenseToDenseSetOperation (None) in gradient.
tensorflow: Level 1: Registering DenseToSparseSetOperation (None) in gradient.
tensorflow: Level 1: Registering SparseToSparseSetOperation (None) in gradient.
tensorflow: Level 1: Registering TensorSummary (None) in gradient.
tensorflow: Level 1: Registering queue_runners ((<class 'tensorflow.core.protobuf.queue_runner_pb2.QueueRunnerDef'>, <function QueueRunner.to_proto at 0x7fa88c13ce18>, <function QueueRunner.from_proto at 0x7fa88c13cea0>)) in proto functions.
tensorflow: Level 1: Registering savers ((<class 'tensorflow.core.protobuf.saver_pb2.SaverDef'>, <function Saver.to_proto at 0x7fa88c0bd2f0>, <function Saver.from_proto at 0x7fa88c0bd378>)) in proto functions.
tensorflow: Level 1: Registering SdcaFprint (None) in gradient.
tensorflow: Level 1: Registering SdcaOptimizer (None) in gradient.
tensorflow: Level 1: Registering SdcaShrinkL1 (None) in gradient.
tensorflow: Level 1: Registering GenerateVocabRemapping (None) in gradient.
tensorflow: Level 1: Registering LoadAndRemapMatrix (None) in gradient.
tensorflow: Level 1: Registering BitwiseAnd (None) in gradient.
tensorflow: Level 1: Registering BitwiseOr (None) in gradient.
tensorflow: Level 1: Registering BitwiseXor (None) in gradient.
tensorflow: Level 1: Registering Invert (None) in gradient.
tensorflow: Level 1: Registering PopulationCount (None) in gradient.
tensorflow: Level 1: Registering LeftShift (None) in gradient.
tensorflow: Level 1: Registering RightShift (None) in gradient.
tensorflow: Level 1: Registering Reciprocal,flops (<function _reciprocal_flops at 0x7fa801717e18>) in statistical functions.
tensorflow: Level 1: Registering Square,flops (<function _square_flops at 0x7fa8016c0c80>) in statistical functions.
tensorflow: Level 1: Registering Rsqrt,flops (<function _rsqrt_flops at 0x7fa8016c0d90>) in statistical functions.
tensorflow: Level 1: Registering Log,flops (<function _log_flops at 0x7fa8016c0e18>) in statistical functions.
tensorflow: Level 1: Registering Neg,flops (<function _neg_flops at 0x7fa8016c0ea0>) in statistical functions.
tensorflow: Level 1: Registering AssignSub,flops (<function _assign_sub_flops at 0x7fa8016c0f28>) in statistical functions.
tensorflow: Level 1: Registering AssignAdd,flops (<function _assign_add_flops at 0x7fa80165e048>) in statistical functions.
tensorflow: Level 1: Registering L2Loss,flops (<function _l2_loss_flops at 0x7fa80165e0d0>) in statistical functions.
tensorflow: Level 1: Registering Softmax,flops (<function _softmax_flops at 0x7fa80165e158>) in statistical functions.
tensorflow: Level 1: Registering Add,flops (<function _add_flops at 0x7fa80165e268>) in statistical functions.
tensorflow: Level 1: Registering Sub,flops (<function _sub_flops at 0x7fa80165e2f0>) in statistical functions.
tensorflow: Level 1: Registering Mul,flops (<function _mul_flops at 0x7fa80165e378>) in statistical functions.
tensorflow: Level 1: Registering RealDiv,flops (<function _real_div_flops at 0x7fa80165e400>) in statistical functions.
tensorflow: Level 1: Registering Maximum,flops (<function _maximum_flops at 0x7fa80165e488>) in statistical functions.
tensorflow: Level 1: Registering Minimum,flops (<function _minimum_flops at 0x7fa80165e510>) in statistical functions.
tensorflow: Level 1: Registering Pow,flops (<function _pow_flops at 0x7fa80165e598>) in statistical functions.
tensorflow: Level 1: Registering RsqrtGrad,flops (<function _rsqrt_grad_flops at 0x7fa80165e620>) in statistical functions.
tensorflow: Level 1: Registering GreaterEqual,flops (<function _greater_equal_flops at 0x7fa80165e6a8>) in statistical functions.
tensorflow: Level 1: Registering Greater,flops (<function _greater_flops at 0x7fa80165e730>) in statistical functions.
tensorflow: Level 1: Registering LessEqual,flops (<function _less_equal_flops at 0x7fa80165e7b8>) in statistical functions.
tensorflow: Level 1: Registering Less,flops (<function _less_flops at 0x7fa80165e840>) in statistical functions.
tensorflow: Level 1: Registering Equal,flops (<function _equal_flops at 0x7fa80165e8c8>) in statistical functions.
tensorflow: Level 1: Registering NotEqual,flops (<function _not_equal_flops at 0x7fa80165e950>) in statistical functions.
tensorflow: Level 1: Registering SquaredDifference,flops (<function _squared_difference_flops at 0x7fa80165e9d8>) in statistical functions.
tensorflow: Level 1: Registering Mean,flops (<function _mean_flops at 0x7fa80165eae8>) in statistical functions.
tensorflow: Level 1: Registering Sum,flops (<function _sum_flops at 0x7fa80165eb70>) in statistical functions.
tensorflow: Level 1: Registering ArgMax,flops (<function _arg_max_flops at 0x7fa80165ebf8>) in statistical functions.
tensorflow: Level 1: Registering ArgMin,flops (<function _arg_min_flops at 0x7fa80165ec80>) in statistical functions.
tensorflow: Level 1: Registering BiasAddGrad,flops (<function _bias_add_grad_flops at 0x7fa80165ed08>) in statistical functions.
tensorflow: Level 1: Registering AvgPool,flops (<function _avg_pool_flops at 0x7fa80165eea0>) in statistical functions.
tensorflow: Level 1: Registering MaxPool,flops (<function _max_pool_flops at 0x7fa80165ef28>) in statistical functions.
tensorflow: Level 1: Registering AvgPoolGrad,flops (<function _avg_pool_grad_flops at 0x7fa801663048>) in statistical functions.
tensorflow: Level 1: Registering MaxPoolGrad,flops (<function _max_pool_grad_flops at 0x7fa8016630d0>) in statistical functions.
tensorflow: Level 1: Registering Conv2DBackpropInput,flops (<function _conv_2d_backprop_input_flops at 0x7fa801663158>) in statistical functions.
tensorflow: Level 1: Registering Conv2DBackpropFilter,flops (<function _conv_2d_backprop_filter_flops at 0x7fa8016631e0>) in statistical functions.
tensorflow: Level 1: Registering AddN,flops (<function _add_n_flops at 0x7fa801663268>) in statistical functions.
tensorflow: Level 1: Registering Fact (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering Batch (<function _BatchGrad at 0x7fa8016192f0>) in gradient.
tensorflow: Level 1: Registering Unbatch (<function _UnbatchGrad at 0x7fa8015a8488>) in gradient.
tensorflow: Level 1: Registering BigQueryReader (None) in gradient.
tensorflow: Level 1: Registering RangeDecode (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering RangeEncode (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering GRUBlockCell (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering GRUBlockCellGrad (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering GRUBlockCell (<function _GRUBlockCellGrad at 0x7fa801264950>) in gradient.
tensorflow: Level 1: Registering BlockLSTM (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering BlockLSTMGrad (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering LSTMBlockCell (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering LSTMBlockCellGrad (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering LSTMBlockCell (<function _LSTMBlockCellGrad at 0x7fa801294f28>) in gradient.
tensorflow: Level 1: Registering BlockLSTM (<function _BlockLSTMGrad at 0x7fa801231048>) in gradient.
tensorflow: Level 1: Registering ZeroInitializer (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SparseFeatureCross (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SparseFeatureCrossV2 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SparseFeatureCross (None) in gradient.
tensorflow: Level 1: Registering SparseFeatureCrossV2 (None) in gradient.
tensorflow: Level 1: Registering GDNLowerBound (<function GDN._lower_bound_grad at 0x7fa8004d7e18>) in gradient.
tensorflow: Level 1: Registering CudnnRNN (<function _cudnn_rnn_backward at 0x7fa7fe5ecbf8>) in gradient.
tensorflow: Level 1: Registering CudnnRNNParamsSize (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering CudnnRNNParamsToCanonical (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering CudnnRNNCanonicalToParams (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering CudnnRNN (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering CudnnRNNBackprop (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering IgnoreErrorsDataset (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering UniqueDataset (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering IteratorGetDevice (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FunctionBufferingResource (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FunctionBufferingResourceGetNext (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FunctionBufferingResourceReset (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ThreadPoolDataset (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ThreadPoolHandle (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NcclAllReduce (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NcclBroadcast (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NcclReduce (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _NcclReduceSend (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _NcclReduceRecv (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _NcclBroadcastSend (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _NcclBroadcastRecv (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NcclAllReduce (<function _all_sum_grad at 0x7fa7fe2d5158>) in gradient.
tensorflow: Level 1: Registering NcclReduce (<function _reduce_sum_grad at 0x7fa7fe2d5400>) in gradient.
tensorflow: Level 1: Registering NcclBroadcast (<function _broadcast_grad at 0x7fa7fe2d5510>) in gradient.
tensorflow: Level 1: Registering ObtainNext (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering hparams ((<class 'tensorflow.contrib.training.python.training.hparam_pb2.HParamDef'>, <function HParams.to_proto at 0x7fa7fb42e510>, <function HParams.from_proto at 0x7fa7fb42e598>)) in proto functions.
tensorflow: Level 1: Registering KMC2ChainInitialization (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering KmeansPlusPlusInitialization (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NearestNeighbors (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering MaskedMatmul (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering WALSComputePartialLhsAndRhs (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ConfigureDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering CrossReplicaSum (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering InfeedDequeue (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering InfeedDequeueTuple (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering InfeedEnqueue (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering InfeedEnqueueTuple (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering OutfeedDequeue (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering OutfeedDequeueTuple (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering OutfeedEnqueue (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering OutfeedEnqueueTuple (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SessionStatus (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ShutdownDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingActivations (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingEnqueueSparseBatch (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingLoadAdagradParameters (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingLoadGradientDescentParameters (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingReceiveActivations (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingRetrieveAdagradParameters (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingRetrieveGradientDescentParameters (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingSendGradients (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUReplicate (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUReplicateMetadata (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUReplicatedInput (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUReplicatedOutput (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _XlaSendFromHost (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _XlaRecvAtHost (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _ConfigureDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _WaitForDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _SetGlobalTPUArray (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _ShutdownDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _InitializeHostForDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _DisconnectHostFromDistributedTPUSystem (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering CrossReplicaSum (<function _cross_replica_sum_grad at 0x7fa7fadcc400>) in gradient.
tensorflow: Level 1: Registering tpu_estimator_iterations_per_loop ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa8a5695e18>)) in proto functions.
tensorflow: Level 1: Registering AdjustHsvInYiq (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering BipartiteMatch (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ImageConnectedComponents (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ImageProjectiveTransform (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ImageConnectedComponents (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering ImageProjectiveTransform (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering ImageProjectiveTransform (<function _image_projective_transform_grad at 0x7fa7fa8a1b70>) in gradient.
tensorflow: Level 1: Registering BipartiteMatch (None) in gradient.
tensorflow: Level 1: Registering ImageConnectedComponents (None) in gradient.
tensorflow: Level 1: Registering SingleImageRandomDotStereograms (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SingleImageRandomDotStereograms (None) in gradient.
tensorflow: Level 1: Registering BytesInUse (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering BytesLimit (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering MaxBytesInUse (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering PeriodicResample (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering DecodeProtoV2 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering DecodeProtoV2 (None) in gradient.
tensorflow: Level 1: Registering EncodeProto (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering EncodeProto (None) in gradient.
tensorflow: Level 1: Registering FoldFusedBatchNormGrad (<function _FoldFusedBatchNormGrad at 0x7fa7f99bebf8>) in gradient.
tensorflow: Level 1: Registering Resampler (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ResamplerGrad (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering Resampler (<function _resampler_grad at 0x7fa7f96ead90>) in gradient.
tensorflow: Level 1: Registering ResamplerGrad (None) in gradient.
tensorflow: Level 1: Registering Rpc (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TryRpc (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering Rpc (None) in gradient.
tensorflow: Level 1: Registering TryRpc (None) in gradient.
tensorflow: Level 1: Registering GatherTree (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering StatelessRandomNormal (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering StatelessRandomUniform (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering StatelessTruncatedNormal (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering StatelessRandomNormal (None) in gradient.
tensorflow: Level 1: Registering StatelessRandomUniform (None) in gradient.
tensorflow: Level 1: Registering StatelessTruncatedNormal (None) in gradient.
tensorflow: Level 1: Registering ReinterpretStringToFloat (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ScatterAddNdim (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering CreateTreeVariable (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering DecisionTreeResourceHandleOp (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FeatureUsageCounts (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TraverseTreeV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeDeserialize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeIsInitializedOp (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreePredictionsV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeSerialize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeSize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering UpdateModelV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeVariable (None) in gradient.
tensorflow: Level 1: Registering TreeSerialize (None) in gradient.
tensorflow: Level 1: Registering TreeDeserialize (None) in gradient.
tensorflow: Level 1: Registering TreeSize (None) in gradient.
tensorflow: Level 1: Registering TreePredictionsV4 (None) in gradient.
tensorflow: Level 1: Registering FeatureUsageCounts (None) in gradient.
tensorflow: Level 1: Registering CreateFertileStatsVariable (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsDeserialize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsIsInitializedOp (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsResourceHandleOp (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsSerialize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FinalizeTree (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering GrowTreeV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ProcessInputV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsVariable (None) in gradient.
tensorflow: Level 1: Registering FertileStatsSerialize (None) in gradient.
tensorflow: Level 1: Registering FertileStatsDeserialize (None) in gradient.
tensorflow: Level 1: Registering GrowTreeV4 (None) in gradient.
tensorflow: Level 1: Registering ProcessInputV4 (None) in gradient.
tensorflow: Level 1: Registering FinalizeTree (None) in gradient.
tensorflow: Level 1: Registering RemoteFusedGraphExecute (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering RemoteFusedGraphExecute (None) in gradient.
--------------------- >> end captured logging << ---------------------

tensorflow: Level 1: Registering Tan (<function _TanGrad at 0x7fa8a5d51d90>) in gradient.
tensorflow: Level 1: Registering Asin (<function _AsinGrad at 0x7fa8a5d51e18>) in gradient.
tensorflow: Level 1: Registering Acos (<function _AcosGrad at 0x7fa8a5d51ea0>) in gradient.
tensorflow: Level 1: Registering Atan (<function _AtanGrad at 0x7fa8a5d51f28>) in gradient.
tensorflow: Level 1: Registering Atan2 (<function _Atan2Grad at 0x7fa8a5d56048>) in gradient.
tensorflow: Level 1: Registering AddN (<function _AddNGrad at 0x7fa8a5d560d0>) in gradient.
tensorflow: Level 1: Registering Add (<function _AddGrad at 0x7fa8a5d561e0>) in gradient.
tensorflow: Level 1: Registering Sub (<function _SubGrad at 0x7fa8a5d56268>) in gradient.
tensorflow: Level 1: Registering Mul (<function _MulGrad at 0x7fa8a5d562f0>) in gradient.
tensorflow: Level 1: Registering Div (<function _DivGrad at 0x7fa8a5d56378>) in gradient.
tensorflow: Level 1: Registering FloorDiv (<function _FloorDivGrad at 0x7fa8a5d56400>) in gradient.
tensorflow: Level 1: Registering FloorMod (<function _FloorModGrad at 0x7fa8a5d56488>) in gradient.
tensorflow: Level 1: Registering TruncateDiv (<function _TruncateDivGrad at 0x7fa8a5d56510>) in gradient.
tensorflow: Level 1: Registering RealDiv (<function _RealDivGrad at 0x7fa8a5d56598>) in gradient.
tensorflow: Level 1: Registering Pow (<function _PowGrad at 0x7fa8a5d56620>) in gradient.
tensorflow: Level 1: Registering Maximum (<function _MaximumGrad at 0x7fa8a5d56730>) in gradient.
tensorflow: Level 1: Registering Minimum (<function _MinimumGrad at 0x7fa8a5d567b8>) in gradient.
tensorflow: Level 1: Registering SquaredDifference (<function _SquaredDifferenceGrad at 0x7fa8a5d56840>) in gradient.
tensorflow: Level 1: Registering Less (None) in gradient.
tensorflow: Level 1: Registering LessEqual (None) in gradient.
tensorflow: Level 1: Registering Greater (None) in gradient.
tensorflow: Level 1: Registering GreaterEqual (None) in gradient.
tensorflow: Level 1: Registering Equal (None) in gradient.
tensorflow: Level 1: Registering ApproximateEqual (None) in gradient.
tensorflow: Level 1: Registering NotEqual (None) in gradient.
tensorflow: Level 1: Registering LogicalAnd (None) in gradient.
tensorflow: Level 1: Registering LogicalOr (None) in gradient.
tensorflow: Level 1: Registering LogicalNot (None) in gradient.
tensorflow: Level 1: Registering Select (<function _SelectGrad at 0x7fa8a5d568c8>) in gradient.
tensorflow: Level 1: Registering MatMul (<function _MatMulGrad at 0x7fa8a5d56950>) in gradient.
tensorflow: Level 1: Registering SparseMatMul (<function _SparseMatMulGrad at 0x7fa8a5d569d8>) in gradient.
tensorflow: Level 1: Registering Floor (<function _FloorGrad at 0x7fa8a5d56a60>) in gradient.
tensorflow: Level 1: Registering Ceil (<function _CeilGrad at 0x7fa8a5d56ae8>) in gradient.
tensorflow: Level 1: Registering Round (<function _RoundGrad at 0x7fa8a5d56b70>) in gradient.
tensorflow: Level 1: Registering Rint (<function _RintGrad at 0x7fa8a5d56bf8>) in gradient.
tensorflow: Level 1: Registering BatchMatMul (<function _BatchMatMul at 0x7fa8a5d56c80>) in gradient.
tensorflow: Level 1: Registering Range (None) in gradient.
tensorflow: Level 1: Registering LinSpace (None) in gradient.
tensorflow: Level 1: Registering Complex (<function _ComplexGrad at 0x7fa8a5d56d08>) in gradient.
tensorflow: Level 1: Registering Real (<function _RealGrad at 0x7fa8a5d56d90>) in gradient.
tensorflow: Level 1: Registering Imag (<function _ImagGrad at 0x7fa8a5d56e18>) in gradient.
tensorflow: Level 1: Registering Angle (<function _AngleGrad at 0x7fa8a5d56ea0>) in gradient.
tensorflow: Level 1: Registering Conj (<function _ConjGrad at 0x7fa8a5d56f28>) in gradient.
tensorflow: Level 1: Registering ComplexAbs (<function _ComplexAbsGrad at 0x7fa8a5d58048>) in gradient.
tensorflow: Level 1: Registering Cast (<function _CastGrad at 0x7fa8a5d580d0>) in gradient.
tensorflow: Level 1: Registering Cross (<function _CrossGrad at 0x7fa8a5d58158>) in gradient.
tensorflow: Level 1: Registering Cumsum (<function _CumsumGrad at 0x7fa8a5d581e0>) in gradient.
tensorflow: Level 1: Registering Cumprod (<function _CumprodGrad at 0x7fa8a5d58268>) in gradient.
tensorflow: Level 1: Registering SparseAddGrad (None) in gradient.
tensorflow: Level 1: Registering SparseConcat (None) in gradient.
tensorflow: Level 1: Registering SparseToDense (None) in gradient.
tensorflow: Level 1: Registering SparseReorder (<function _SparseReorderGrad at 0x7fa8a5d58a60>) in gradient.
tensorflow: Level 1: Registering SparseAdd (<function _SparseAddGrad at 0x7fa8a5d58ae8>) in gradient.
tensorflow: Level 1: Registering SparseTensorDenseAdd (<function _SparseTensorDenseAddGrad at 0x7fa8a5d58b70>) in gradient.
tensorflow: Level 1: Registering SparseReduceSum (<function _SparseReduceSumGrad at 0x7fa8a5d58bf8>) in gradient.
tensorflow: Level 1: Registering SparseTensorDenseMatMul (<function _SparseTensorDenseMatMulGrad at 0x7fa8a5d58c80>) in gradient.
tensorflow: Level 1: Registering SparseDenseCwiseAdd (<function _SparseDenseCwiseAddGrad at 0x7fa8a5d58d08>) in gradient.
tensorflow: Level 1: Registering SparseDenseCwiseMul (<function _SparseDenseCwiseMulGrad at 0x7fa8a5d58e18>) in gradient.
tensorflow: Level 1: Registering SparseDenseCwiseDiv (<function _SparseDenseCwiseDivGrad at 0x7fa8a5d58ea0>) in gradient.
tensorflow: Level 1: Registering SparseSoftmax (<function _SparseSoftmaxGrad at 0x7fa8a5d58f28>) in gradient.
tensorflow: Level 1: Registering SparseSparseMaximum (<function _SparseSparseMaximumGrad at 0x7fa8a5d63048>) in gradient.
tensorflow: Level 1: Registering SparseSparseMinimum (<function _SparseSparseMinimumGrad at 0x7fa8a5d630d0>) in gradient.
tensorflow: Level 1: Registering SparseFillEmptyRows (<function _SparseFillEmptyRowsGrad at 0x7fa8a5d63158>) in gradient.
tensorflow: Level 1: Registering FFT (<function _FFTGrad at 0x7fa8a5d639d8>) in gradient.
tensorflow: Level 1: Registering IFFT (<function _IFFTGrad at 0x7fa8a5d6f048>) in gradient.
tensorflow: Level 1: Registering FFT2D (<function _FFT2DGrad at 0x7fa8a5d6f0d0>) in gradient.
tensorflow: Level 1: Registering IFFT2D (<function _IFFT2DGrad at 0x7fa8a5d6f158>) in gradient.
tensorflow: Level 1: Registering FFT3D (<function _FFT3DGrad at 0x7fa8a5d6f1e0>) in gradient.
tensorflow: Level 1: Registering IFFT3D (<function _IFFT3DGrad at 0x7fa8a5d6f268>) in gradient.
tensorflow: Level 1: Registering RFFT (<function _RFFTGradHelper.._Grad at 0x7fa8a5d6f400>) in gradient.
tensorflow: Level 1: Registering IRFFT (<function _IRFFTGradHelper.._Grad at 0x7fa8a5d6f488>) in gradient.
tensorflow: Level 1: Registering RFFT2D (<function _RFFTGradHelper.._Grad at 0x7fa8a5d6f510>) in gradient.
tensorflow: Level 1: Registering IRFFT2D (<function _IRFFTGradHelper.._Grad at 0x7fa8a5d6f598>) in gradient.
tensorflow: Level 1: Registering Assign (None) in gradient.
tensorflow: Level 1: Registering AssignAdd (None) in gradient.
tensorflow: Level 1: Registering AssignSub (None) in gradient.
tensorflow: Level 1: Registering ScatterAdd (None) in gradient.
tensorflow: Level 1: Registering ScatterSub (None) in gradient.
tensorflow: Level 1: Registering ScatterMul (None) in gradient.
tensorflow: Level 1: Registering ScatterDiv (None) in gradient.
tensorflow: Level 1: Registering ScatterNdUpdate (None) in gradient.
tensorflow: Level 1: Registering ScatterNdAdd (None) in gradient.
tensorflow: Level 1: Registering ScatterNdSub (None) in gradient.
tensorflow: Level 1: Registering ScatterNdMul (None) in gradient.
tensorflow: Level 1: Registering ScatterNdDiv (None) in gradient.
tensorflow: Level 1: Registering TensorArray (None) in gradient.
tensorflow: Level 1: Registering TensorArrayGrad (None) in gradient.
tensorflow: Level 1: Registering TensorArraySize (None) in gradient.
tensorflow: Level 1: Registering TensorArrayClose (None) in gradient.
tensorflow: Level 1: Registering TensorArrayV2 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayGradV2 (None) in gradient.
tensorflow: Level 1: Registering TensorArraySizeV2 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayCloseV2 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayV3 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayGradV3 (None) in gradient.
tensorflow: Level 1: Registering TensorArraySizeV3 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayCloseV3 (None) in gradient.
tensorflow: Level 1: Registering TensorArrayReadV3 (<function _TensorArrayReadGrad at 0x7fa8a5d6fbf8>) in gradient.
tensorflow: Level 1: Registering TensorArrayReadV2 (<function _TensorArrayReadGrad at 0x7fa8a5d6fbf8>) in gradient.
tensorflow: Level 1: Registering TensorArrayRead (<function _TensorArrayReadGrad at 0x7fa8a5d6fbf8>) in gradient.
tensorflow: Level 1: Registering TensorArrayWriteV3 (<function _TensorArrayWriteGrad at 0x7fa8a5d6fc80>) in gradient.
tensorflow: Level 1: Registering TensorArrayWriteV2 (<function _TensorArrayWriteGrad at 0x7fa8a5d6fc80>) in gradient.
tensorflow: Level 1: Registering TensorArrayWrite (<function _TensorArrayWriteGrad at 0x7fa8a5d6fc80>) in gradient.
tensorflow: Level 1: Registering TensorArrayGatherV3 (<function _TensorArrayGatherGrad at 0x7fa8a5d6fd08>) in gradient.
tensorflow: Level 1: Registering TensorArrayGatherV2 (<function _TensorArrayGatherGrad at 0x7fa8a5d6fd08>) in gradient.
tensorflow: Level 1: Registering TensorArrayGather (<function _TensorArrayGatherGrad at 0x7fa8a5d6fd08>) in gradient.
tensorflow: Level 1: Registering TensorArrayScatterV3 (<function _TensorArrayScatterGrad at 0x7fa8a5d6fd90>) in gradient.
tensorflow: Level 1: Registering TensorArrayScatterV2 (<function _TensorArrayScatterGrad at 0x7fa8a5d6fd90>) in gradient.
tensorflow: Level 1: Registering TensorArrayScatter (<function _TensorArrayScatterGrad at 0x7fa8a5d6fd90>) in gradient.
tensorflow: Level 1: Registering TensorArrayConcatV3 (<function _TensorArrayConcatGrad at 0x7fa8a5d6fe18>) in gradient.
tensorflow: Level 1: Registering TensorArrayConcatV2 (<function _TensorArrayConcatGrad at 0x7fa8a5d6fe18>) in gradient.
tensorflow: Level 1: Registering TensorArrayConcat (<function _TensorArrayConcatGrad at 0x7fa8a5d6fe18>) in gradient.
tensorflow: Level 1: Registering TensorArraySplitV3 (<function _TensorArraySplitGrad at 0x7fa8a5d6fea0>) in gradient.
tensorflow: Level 1: Registering TensorArraySplitV2 (<function _TensorArraySplitGrad at 0x7fa8a5d6fea0>) in gradient.
tensorflow: Level 1: Registering TensorArraySplit (<function _TensorArraySplitGrad at 0x7fa8a5d6fea0>) in gradient.
tensorflow: Level 1: Registering ClipByValue (<function _ClipByValueGrad at 0x7fa8a5cfd158>) in gradient.
tensorflow: Level 1: Registering Switch (<function _SwitchGrad at 0x7fa8a5d27400>) in gradient.
tensorflow: Level 1: Registering RefSwitch (<function _SwitchGrad at 0x7fa8a5d27400>) in gradient.
tensorflow: Level 1: Registering Merge (<function _MergeGrad at 0x7fa8a5cca7b8>) in gradient.
tensorflow: Level 1: Registering RefMerge (<function _RefMergeGrad at 0x7fa8a5cca950>) in gradient.
tensorflow: Level 1: Registering Exit (<function _ExitGrad at 0x7fa8a5cca9d8>) in gradient.
tensorflow: Level 1: Registering RefExit (<function _ExitGrad at 0x7fa8a5cca9d8>) in gradient.
tensorflow: Level 1: Registering NextIteration (<function _NextIterationGrad at 0x7fa8a5cca840>) in gradient.
tensorflow: Level 1: Registering RefNextIteration (<function _RefNextIterationGrad at 0x7fa8a5ccaae8>) in gradient.
tensorflow: Level 1: Registering Enter (<function _EnterGrad at 0x7fa8a5ccab70>) in gradient.
tensorflow: Level 1: Registering RefEnter (<function _RefEnterGrad at 0x7fa8a5ccabf8>) in gradient.
tensorflow: Level 1: Registering LoopCond (<function _LoopCondGrad at 0x7fa8a5ccac80>) in gradient.
tensorflow: Level 1: Registering ResizeNearestNeighbor (<function _ResizeNearestNeighborGrad at 0x7fa8a5ccaa60>) in gradient.
tensorflow: Level 1: Registering ResizeBilinear (<function _ResizeBilinearGrad at 0x7fa8a5cf98c8>) in gradient.
tensorflow: Level 1: Registering ResizeBicubic (<function _ResizeBicubicGrad at 0x7fa8a5cf99d8>) in gradient.
tensorflow: Level 1: Registering CropAndResize (<function _CropAndResizeGrad at 0x7fa8a5cf9a60>) in gradient.
tensorflow: Level 1: Registering MatrixInverse (<function _MatrixInverseGrad at 0x7fa8a5cf9c80>) in gradient.
tensorflow: Level 1: Registering MatrixDeterminant (<function _MatrixDeterminantGrad at 0x7fa8a5c95488>) in gradient.
tensorflow: Level 1: Registering Cholesky (<function _CholeskyGrad at 0x7fa8a5c95510>) in gradient.
tensorflow: Level 1: Registering Qr (<function _QrGrad at 0x7fa8a5c95598>) in gradient.
tensorflow: Level 1: Registering MatrixSolve (<function _MatrixSolveGrad at 0x7fa8a5c956a8>) in gradient.
tensorflow: Level 1: Registering MatrixSolveLs (<function _MatrixSolveLsGrad at 0x7fa8a5c95730>) in gradient.
tensorflow: Level 1: Registering MatrixTriangularSolve (<function _MatrixTriangularSolveGrad at 0x7fa8a5c957b8>) in gradient.
tensorflow: Level 1: Registering SelfAdjointEigV2 (<function _SelfAdjointEigV2Grad at 0x7fa8a5c95840>) in gradient.
tensorflow: Level 1: Registering Svd (<function _SvdGrad at 0x7fa8a5c958c8>) in gradient.
tensorflow: Level 1: Registering Print (<function _PrintGrad at 0x7fa8a5c95b70>) in gradient.
tensorflow: Level 1: Registering HistogramSummary (None) in gradient.
tensorflow: Level 1: Registering ImageSummary (None) in gradient.
tensorflow: Level 1: Registering AudioSummary (None) in gradient.
tensorflow: Level 1: Registering AudioSummaryV2 (None) in gradient.
tensorflow: Level 1: Registering MergeSummary (None) in gradient.
tensorflow: Level 1: Registering ScalarSummary (None) in gradient.
tensorflow: Level 1: Registering Timestamp (None) in gradient.
tensorflow: Level 1: Registering ReaderRead (None) in gradient.
tensorflow: Level 1: Registering ReaderReadUpTo (None) in gradient.
tensorflow: Level 1: Registering ReaderNumRecordsProduced (None) in gradient.
tensorflow: Level 1: Registering ReaderNumWorkUnitsCompleted (None) in gradient.
tensorflow: Level 1: Registering ReaderSerializeState (None) in gradient.
tensorflow: Level 1: Registering ReaderRestoreState (None) in gradient.
tensorflow: Level 1: Registering ReaderReset (None) in gradient.
tensorflow: Level 1: Registering WholeFileReader (None) in gradient.
tensorflow: Level 1: Registering TextLineReader (None) in gradient.
tensorflow: Level 1: Registering FixedLengthRecordReader (None) in gradient.
tensorflow: Level 1: Registering TFRecordReader (None) in gradient.
tensorflow: Level 1: Registering LMDBReader (None) in gradient.
tensorflow: Level 1: Registering IdentityReader (None) in gradient.
tensorflow: Level 1: Registering RegexReplace (None) in gradient.
tensorflow: Level 1: Registering StringToHashBucket (None) in gradient.
tensorflow: Level 1: Registering StringToHashBucketFast (None) in gradient.
tensorflow: Level 1: Registering StringToHashBucketStrong (None) in gradient.
tensorflow: Level 1: Registering ReduceJoin (None) in gradient.
tensorflow: Level 1: Registering StringJoin (None) in gradient.
tensorflow: Level 1: Registering StringSplit (None) in gradient.
tensorflow: Level 1: Registering AsString (None) in gradient.
tensorflow: Level 1: Registering EncodeBase64 (None) in gradient.
tensorflow: Level 1: Registering DecodeBase64 (None) in gradient.
tensorflow: Level 1: Registering LookupTableFind (None) in gradient.
tensorflow: Level 1: Registering LookupTableFindV2 (None) in gradient.
tensorflow: Level 1: Registering LookupTableInsert (None) in gradient.
tensorflow: Level 1: Registering LookupTableInsertV2 (None) in gradient.
tensorflow: Level 1: Registering LookupTableSize (None) in gradient.
tensorflow: Level 1: Registering LookupTableSizeV2 (None) in gradient.
tensorflow: Level 1: Registering HashTable (None) in gradient.
tensorflow: Level 1: Registering HashTableV2 (None) in gradient.
tensorflow: Level 1: Registering InitializeTable (None) in gradient.
tensorflow: Level 1: Registering InitializeTableV2 (None) in gradient.
tensorflow: Level 1: Registering InitializeTableFromTextFile (None) in gradient.
tensorflow: Level 1: Registering InitializeTableFromTextFileV2 (None) in gradient.
tensorflow: Level 1: Registering MutableDenseHashTable (None) in gradient.
tensorflow: Level 1: Registering MutableDenseHashTableV2 (None) in gradient.
tensorflow: Level 1: Registering MutableHashTable (None) in gradient.
tensorflow: Level 1: Registering MutableHashTableV2 (None) in gradient.
tensorflow: Level 1: Registering MutableHashTableOfTensors (None) in gradient.
tensorflow: Level 1: Registering MutableHashTableOfTensorsV2 (None) in gradient.
tensorflow: Level 1: Registering DecodeRaw (None) in gradient.
tensorflow: Level 1: Registering ParseTensor (None) in gradient.
tensorflow: Level 1: Registering SerializeTensor (None) in gradient.
tensorflow: Level 1: Registering StringToNumber (None) in gradient.
tensorflow: Level 1: Registering PyFunc (None) in gradient.
tensorflow: Level 1: Registering PyFuncStateless (None) in gradient.
tensorflow: Level 1: Registering Conv2D,flops (<function _calc_conv_flops at 0x7fa8a5831f28>) in statistical functions.
tensorflow: Level 1: Registering DepthwiseConv2dNative,flops (<function _calc_depthwise_conv_flops at 0x7fa8a5824b70>) in statistical functions.
tensorflow: Level 1: Registering BiasAdd,flops (<function _calc_bias_add_flops at 0x7fa8a5824bf8>) in statistical functions.
tensorflow: Level 1: Registering Dilation2D,flops (<function _calc_dilation2d_flops at 0x7fa8a57e5268>) in statistical functions.
tensorflow: Level 1: Registering Conv2DBackpropInput (<function _Conv2DBackpropInputGrad at 0x7fa8a58a52f0>) in gradient.
tensorflow: Level 1: Registering Conv2DBackpropFilter (<function _Conv2DBackpropFilterGrad at 0x7fa8a57e5400>) in gradient.
tensorflow: Level 1: Registering Conv3D (<function _Conv3DGrad at 0x7fa8a57e5488>) in gradient.
tensorflow: Level 1: Registering Conv3DBackpropInputV2 (<function _Conv3DBackpropInputGrad at 0x7fa8a57e5510>) in gradient.
tensorflow: Level 1: Registering Conv3DBackpropFilterV2 (<function _Conv3DBackpropFilterGrad at 0x7fa8a57e5598>) in gradient.
tensorflow: Level 1: Registering AvgPool3D (<function _AvgPool3DGrad at 0x7fa8a57e5620>) in gradient.
tensorflow: Level 1: Registering AvgPool3DGrad (<function _AvgPool3DGradGrad at 0x7fa8a57e56a8>) in gradient.
tensorflow: Level 1: Registering MaxPool3D (<function _MaxPool3DGrad at 0x7fa8a57e5730>) in gradient.
tensorflow: Level 1: Registering MaxPool3DGrad (<function _MaxPool3DGradGrad at 0x7fa8a57e57b8>) in gradient.
tensorflow: Level 1: Registering MaxPool3DGradGrad (<function _MaxPool3DGradGradGrad at 0x7fa8a57e5840>) in gradient.
tensorflow: Level 1: Registering Softmax (<function _SoftmaxGrad at 0x7fa8a57e58c8>) in gradient.
tensorflow: Level 1: Registering LogSoftmax (<function _LogSoftmaxGrad at 0x7fa8a57e5950>) in gradient.
tensorflow: Level 1: Registering BiasAdd (<function _BiasAddGrad at 0x7fa8a57e59d8>) in gradient.
tensorflow: Level 1: Registering BiasAddGrad (<function _BiasAddGradGrad at 0x7fa8a57e5a60>) in gradient.
tensorflow: Level 1: Registering BiasAddV1 (<function _BiasAddGradV1 at 0x7fa8a57e5ae8>) in gradient.
tensorflow: Level 1: Registering Relu (<function _ReluGrad at 0x7fa8a57e5b70>) in gradient.
tensorflow: Level 1: Registering EluGrad (<function _EluGradGrad at 0x7fa8a57e5bf8>) in gradient.
tensorflow: Level 1: Registering SeluGrad (<function _SeluGradGrad at 0x7fa8a57e5c80>) in gradient.
tensorflow: Level 1: Registering Relu6 (<function _Relu6Grad at 0x7fa8a57e5d08>) in gradient.
tensorflow: Level 1: Registering Relu6Grad (<function _Relu6GradGrad at 0x7fa8a57e5d90>) in gradient.
tensorflow: Level 1: Registering Elu (<function _EluGrad at 0x7fa8a57e5e18>) in gradient.
tensorflow: Level 1: Registering Selu (<function _SeluGrad at 0x7fa8a57e5ea0>) in gradient.
tensorflow: Level 1: Registering Softplus (<function _SoftplusGrad at 0x7fa8a57e5f28>) in gradient.
tensorflow: Level 1: Registering SoftplusGrad (<function _SoftplusGradGrad at 0x7fa8a57e8048>) in gradient.
tensorflow: Level 1: Registering Softsign (<function _SoftsignGrad at 0x7fa8a57e80d0>) in gradient.
tensorflow: Level 1: Registering ReluGrad (<function _ReluGradGrad at 0x7fa8a57e8158>) in gradient.
tensorflow: Level 1: Registering SoftmaxCrossEntropyWithLogits (<function _SoftmaxCrossEntropyWithLogitsGrad at 0x7fa8a57e8268>) in gradient.
tensorflow: Level 1: Registering SparseSoftmaxCrossEntropyWithLogits (<function _SparseSoftmaxCrossEntropyWithLogitsGrad at 0x7fa8a57e82f0>) in gradient.
tensorflow: Level 1: Registering Conv2D (<function _Conv2DGrad at 0x7fa8a57e8378>) in gradient.
tensorflow: Level 1: Registering DepthwiseConv2dNative (<function _DepthwiseConv2dNativeGrad at 0x7fa8a57e8400>) in gradient.
tensorflow: Level 1: Registering Dilation2D (<function _Dilation2DGrad at 0x7fa8a57e8488>) in gradient.
tensorflow: Level 1: Registering LRN (<function _LRNGrad at 0x7fa8a57e8510>) in gradient.
tensorflow: Level 1: Registering AvgPool (<function _AvgPoolGrad at 0x7fa8a57e8598>) in gradient.
tensorflow: Level 1: Registering AvgPoolGrad (<function _AvgPoolGradGrad at 0x7fa8a57e8620>) in gradient.
tensorflow: Level 1: Registering MaxPool (<function _MaxPoolGrad at 0x7fa8a57e86a8>) in gradient.
tensorflow: Level 1: Registering MaxPoolV2 (<function _MaxPoolGradV2 at 0x7fa8a57e8730>) in gradient.
tensorflow: Level 1: Registering MaxPoolWithArgmax (<function _MaxPoolGradWithArgmax at 0x7fa8a57e87b8>) in gradient.
tensorflow: Level 1: Registering MaxPoolGrad (<function _MaxPoolGradGrad at 0x7fa8a57e8840>) in gradient.
tensorflow: Level 1: Registering MaxPoolGradV2 (<function _MaxPoolGradGradV2 at 0x7fa8a57e88c8>) in gradient.
tensorflow: Level 1: Registering MaxPoolGradGrad (<function _MaxPoolGradGradGrad at 0x7fa8a57e8950>) in gradient.
tensorflow: Level 1: Registering FractionalMaxPool (<function _FractionalMaxPoolGrad at 0x7fa8a57e89d8>) in gradient.
tensorflow: Level 1: Registering FractionalAvgPool (<function _FractionalAvgPoolGrad at 0x7fa8a57e8a60>) in gradient.
tensorflow: Level 1: Registering BatchNormWithGlobalNormalization (<function _BatchNormWithGlobalNormalizationGrad at 0x7fa8a57e8ae8>) in gradient.
tensorflow: Level 1: Registering FusedBatchNorm (<function _FusedBatchNormGrad at 0x7fa8a57e8bf8>) in gradient.
tensorflow: Level 1: Registering FusedBatchNormV2 (<function _FusedBatchNormV2Grad at 0x7fa8a57e8c80>) in gradient.
tensorflow: Level 1: Registering FusedBatchNormGrad (<function _FusedBatchNormGradGrad at 0x7fa8a57e8d90>) in gradient.
tensorflow: Level 1: Registering FusedBatchNormGradV2 (<function _FusedBatchNormGradGradV2 at 0x7fa8a57e8e18>) in gradient.
tensorflow: Level 1: Registering L2Loss (<function _L2LossGrad at 0x7fa8a57e8ea0>) in gradient.
tensorflow: Level 1: Registering TopKV2 (<function _TopKGrad at 0x7fa8a57e8f28>) in gradient.
tensorflow: Level 1: Registering TopK (<function _TopKGrad at 0x7fa8a57e8f28>) in gradient.
tensorflow: Level 1: Registering NthElement (<function _NthElementGrad at 0x7fa8a57ec048>) in gradient.
tensorflow: Level 1: Registering CTCLoss (<function _CTCLossGrad at 0x7fa8a57ec0d0>) in gradient.
tensorflow: Level 1: Registering CTCGreedyDecoder (None) in gradient.
tensorflow: Level 1: Registering CTCBeamSearchDecoder (None) in gradient.
tensorflow: Level 1: Registering RandomCrop (None) in gradient.
tensorflow: Level 1: Registering RGBToHSV (None) in gradient.
tensorflow: Level 1: Registering HSVToRGB (None) in gradient.
tensorflow: Level 1: Registering DrawBoundingBoxes (None) in gradient.
tensorflow: Level 1: Registering SampleDistortedBoundingBox (None) in gradient.
tensorflow: Level 1: Registering SampleDistortedBoundingBoxV2 (None) in gradient.
tensorflow: Level 1: Registering ExtractGlimpse (None) in gradient.
tensorflow: Level 1: Registering NonMaxSuppression (None) in gradient.
tensorflow: Level 1: Registering NonMaxSuppressionV2 (None) in gradient.
tensorflow: Level 1: Registering SetSize (None) in gradient.
tensorflow: Level 1: Registering DenseToDenseSetOperation (None) in gradient.
tensorflow: Level 1: Registering DenseToSparseSetOperation (None) in gradient.
tensorflow: Level 1: Registering SparseToSparseSetOperation (None) in gradient.
tensorflow: Level 1: Registering TensorSummary (None) in gradient.
tensorflow: Level 1: Registering queue_runners ((<class 'tensorflow.core.protobuf.queue_runner_pb2.QueueRunnerDef'>, <function QueueRunner.to_proto at 0x7fa88c13ce18>, <function QueueRunner.from_proto at 0x7fa88c13cea0>)) in proto functions.
tensorflow: Level 1: Registering savers ((<class 'tensorflow.core.protobuf.saver_pb2.SaverDef'>, <function Saver.to_proto at 0x7fa88c0bd2f0>, <function Saver.from_proto at 0x7fa88c0bd378>)) in proto functions.
tensorflow: Level 1: Registering SdcaFprint (None) in gradient.
tensorflow: Level 1: Registering SdcaOptimizer (None) in gradient.
tensorflow: Level 1: Registering SdcaShrinkL1 (None) in gradient.
tensorflow: Level 1: Registering GenerateVocabRemapping (None) in gradient.
tensorflow: Level 1: Registering LoadAndRemapMatrix (None) in gradient.
tensorflow: Level 1: Registering BitwiseAnd (None) in gradient.
tensorflow: Level 1: Registering BitwiseOr (None) in gradient.
tensorflow: Level 1: Registering BitwiseXor (None) in gradient.
tensorflow: Level 1: Registering Invert (None) in gradient.
tensorflow: Level 1: Registering PopulationCount (None) in gradient.
tensorflow: Level 1: Registering LeftShift (None) in gradient.
tensorflow: Level 1: Registering RightShift (None) in gradient.
tensorflow: Level 1: Registering Reciprocal,flops (<function _reciprocal_flops at 0x7fa801717e18>) in statistical functions.
tensorflow: Level 1: Registering Square,flops (<function _square_flops at 0x7fa8016c0c80>) in statistical functions.
tensorflow: Level 1: Registering Rsqrt,flops (<function _rsqrt_flops at 0x7fa8016c0d90>) in statistical functions.
tensorflow: Level 1: Registering Log,flops (<function _log_flops at 0x7fa8016c0e18>) in statistical functions.
tensorflow: Level 1: Registering Neg,flops (<function _neg_flops at 0x7fa8016c0ea0>) in statistical functions.
tensorflow: Level 1: Registering AssignSub,flops (<function _assign_sub_flops at 0x7fa8016c0f28>) in statistical functions.
tensorflow: Level 1: Registering AssignAdd,flops (<function _assign_add_flops at 0x7fa80165e048>) in statistical functions.
tensorflow: Level 1: Registering L2Loss,flops (<function _l2_loss_flops at 0x7fa80165e0d0>) in statistical functions.
tensorflow: Level 1: Registering Softmax,flops (<function _softmax_flops at 0x7fa80165e158>) in statistical functions.
tensorflow: Level 1: Registering Add,flops (<function _add_flops at 0x7fa80165e268>) in statistical functions.
tensorflow: Level 1: Registering Sub,flops (<function _sub_flops at 0x7fa80165e2f0>) in statistical functions.
tensorflow: Level 1: Registering Mul,flops (<function _mul_flops at 0x7fa80165e378>) in statistical functions.
tensorflow: Level 1: Registering RealDiv,flops (<function _real_div_flops at 0x7fa80165e400>) in statistical functions.
tensorflow: Level 1: Registering Maximum,flops (<function _maximum_flops at 0x7fa80165e488>) in statistical functions.
tensorflow: Level 1: Registering Minimum,flops (<function _minimum_flops at 0x7fa80165e510>) in statistical functions.
tensorflow: Level 1: Registering Pow,flops (<function _pow_flops at 0x7fa80165e598>) in statistical functions.
tensorflow: Level 1: Registering RsqrtGrad,flops (<function _rsqrt_grad_flops at 0x7fa80165e620>) in statistical functions.
tensorflow: Level 1: Registering GreaterEqual,flops (<function _greater_equal_flops at 0x7fa80165e6a8>) in statistical functions.
tensorflow: Level 1: Registering Greater,flops (<function _greater_flops at 0x7fa80165e730>) in statistical functions.
tensorflow: Level 1: Registering LessEqual,flops (<function _less_equal_flops at 0x7fa80165e7b8>) in statistical functions.
tensorflow: Level 1: Registering Less,flops (<function _less_flops at 0x7fa80165e840>) in statistical functions.
tensorflow: Level 1: Registering Equal,flops (<function _equal_flops at 0x7fa80165e8c8>) in statistical functions.
tensorflow: Level 1: Registering NotEqual,flops (<function _not_equal_flops at 0x7fa80165e950>) in statistical functions.
tensorflow: Level 1: Registering SquaredDifference,flops (<function _squared_difference_flops at 0x7fa80165e9d8>) in statistical functions.
tensorflow: Level 1: Registering Mean,flops (<function _mean_flops at 0x7fa80165eae8>) in statistical functions.
tensorflow: Level 1: Registering Sum,flops (<function _sum_flops at 0x7fa80165eb70>) in statistical functions.
tensorflow: Level 1: Registering ArgMax,flops (<function _arg_max_flops at 0x7fa80165ebf8>) in statistical functions.
tensorflow: Level 1: Registering ArgMin,flops (<function _arg_min_flops at 0x7fa80165ec80>) in statistical functions.
tensorflow: Level 1: Registering BiasAddGrad,flops (<function _bias_add_grad_flops at 0x7fa80165ed08>) in statistical functions.
tensorflow: Level 1: Registering AvgPool,flops (<function _avg_pool_flops at 0x7fa80165eea0>) in statistical functions.
tensorflow: Level 1: Registering MaxPool,flops (<function _max_pool_flops at 0x7fa80165ef28>) in statistical functions.
tensorflow: Level 1: Registering AvgPoolGrad,flops (<function _avg_pool_grad_flops at 0x7fa801663048>) in statistical functions.
tensorflow: Level 1: Registering MaxPoolGrad,flops (<function _max_pool_grad_flops at 0x7fa8016630d0>) in statistical functions.
tensorflow: Level 1: Registering Conv2DBackpropInput,flops (<function _conv_2d_backprop_input_flops at 0x7fa801663158>) in statistical functions.
tensorflow: Level 1: Registering Conv2DBackpropFilter,flops (<function _conv_2d_backprop_filter_flops at 0x7fa8016631e0>) in statistical functions.
tensorflow: Level 1: Registering AddN,flops (<function _add_n_flops at 0x7fa801663268>) in statistical functions.
tensorflow: Level 1: Registering Fact (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering Batch (<function _BatchGrad at 0x7fa8016192f0>) in gradient.
tensorflow: Level 1: Registering Unbatch (<function _UnbatchGrad at 0x7fa8015a8488>) in gradient.
tensorflow: Level 1: Registering BigQueryReader (None) in gradient.
tensorflow: Level 1: Registering RangeDecode (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering RangeEncode (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering GRUBlockCell (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering GRUBlockCellGrad (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering GRUBlockCell (<function _GRUBlockCellGrad at 0x7fa801264950>) in gradient.
tensorflow: Level 1: Registering BlockLSTM (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering BlockLSTMGrad (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering LSTMBlockCell (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering LSTMBlockCellGrad (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering LSTMBlockCell (<function _LSTMBlockCellGrad at 0x7fa801294f28>) in gradient.
tensorflow: Level 1: Registering BlockLSTM (<function _BlockLSTMGrad at 0x7fa801231048>) in gradient.
tensorflow: Level 1: Registering ZeroInitializer (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SparseFeatureCross (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SparseFeatureCrossV2 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SparseFeatureCross (None) in gradient.
tensorflow: Level 1: Registering SparseFeatureCrossV2 (None) in gradient.
tensorflow: Level 1: Registering GDNLowerBound (<function GDN._lower_bound_grad at 0x7fa8004d7e18>) in gradient.
tensorflow: Level 1: Registering CudnnRNN (<function _cudnn_rnn_backward at 0x7fa7fe5ecbf8>) in gradient.
tensorflow: Level 1: Registering CudnnRNNParamsSize (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering CudnnRNNParamsToCanonical (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering CudnnRNNCanonicalToParams (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering CudnnRNN (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering CudnnRNNBackprop (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering IgnoreErrorsDataset (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering UniqueDataset (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering IteratorGetDevice (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FunctionBufferingResource (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FunctionBufferingResourceGetNext (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FunctionBufferingResourceReset (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ThreadPoolDataset (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ThreadPoolHandle (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NcclAllReduce (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NcclBroadcast (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NcclReduce (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _NcclReduceSend (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _NcclReduceRecv (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _NcclBroadcastSend (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _NcclBroadcastRecv (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NcclAllReduce (<function _all_sum_grad at 0x7fa7fe2d5158>) in gradient.
tensorflow: Level 1: Registering NcclReduce (<function _reduce_sum_grad at 0x7fa7fe2d5400>) in gradient.
tensorflow: Level 1: Registering NcclBroadcast (<function _broadcast_grad at 0x7fa7fe2d5510>) in gradient.
tensorflow: Level 1: Registering ObtainNext (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering hparams ((<class 'tensorflow.contrib.training.python.training.hparam_pb2.HParamDef'>, <function HParams.to_proto at 0x7fa7fb42e510>, <function HParams.from_proto at 0x7fa7fb42e598>)) in proto functions.
tensorflow: Level 1: Registering KMC2ChainInitialization (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering KmeansPlusPlusInitialization (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering NearestNeighbors (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering MaskedMatmul (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering WALSComputePartialLhsAndRhs (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ConfigureDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering CrossReplicaSum (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering InfeedDequeue (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering InfeedDequeueTuple (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering InfeedEnqueue (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering InfeedEnqueueTuple (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering OutfeedDequeue (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering OutfeedDequeueTuple (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering OutfeedEnqueue (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering OutfeedEnqueueTuple (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SessionStatus (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ShutdownDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingActivations (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingEnqueueSparseBatch (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingLoadAdagradParameters (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingLoadGradientDescentParameters (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingReceiveActivations (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingRetrieveAdagradParameters (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingRetrieveGradientDescentParameters (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUEmbeddingSendGradients (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUReplicate (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUReplicateMetadata (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUReplicatedInput (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TPUReplicatedOutput (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _XlaSendFromHost (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _XlaRecvAtHost (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _ConfigureDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _WaitForDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _SetGlobalTPUArray (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _ShutdownDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _InitializeHostForDistributedTPU (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering _DisconnectHostFromDistributedTPUSystem (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering CrossReplicaSum (<function _cross_replica_sum_grad at 0x7fa7fadcc400>) in gradient.
tensorflow: Level 1: Registering tpu_estimator_iterations_per_loop ((<class 'tensorflow.core.framework.variable_pb2.VariableDef'>, <function _to_proto_fn at 0x7fa80dafc378>, <function _from_proto_fn at 0x7fa8a5695e18>)) in proto functions.
tensorflow: Level 1: Registering AdjustHsvInYiq (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering BipartiteMatch (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ImageConnectedComponents (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ImageProjectiveTransform (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ImageConnectedComponents (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering ImageProjectiveTransform (<function call_cpp_shape_fn at 0x7fa80e11cd08>) in shape functions.
tensorflow: Level 1: Registering ImageProjectiveTransform (<function _image_projective_transform_grad at 0x7fa7fa8a1b70>) in gradient.
tensorflow: Level 1: Registering BipartiteMatch (None) in gradient.
tensorflow: Level 1: Registering ImageConnectedComponents (None) in gradient.
tensorflow: Level 1: Registering SingleImageRandomDotStereograms (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering SingleImageRandomDotStereograms (None) in gradient.
tensorflow: Level 1: Registering BytesInUse (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering BytesLimit (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering MaxBytesInUse (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering PeriodicResample (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering DecodeProtoV2 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering DecodeProtoV2 (None) in gradient.
tensorflow: Level 1: Registering EncodeProto (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering EncodeProto (None) in gradient.
tensorflow: Level 1: Registering FoldFusedBatchNormGrad (<function _FoldFusedBatchNormGrad at 0x7fa7f99bebf8>) in gradient.
tensorflow: Level 1: Registering Resampler (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ResamplerGrad (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering Resampler (<function _resampler_grad at 0x7fa7f96ead90>) in gradient.
tensorflow: Level 1: Registering ResamplerGrad (None) in gradient.
tensorflow: Level 1: Registering Rpc (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TryRpc (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering Rpc (None) in gradient.
tensorflow: Level 1: Registering TryRpc (None) in gradient.
tensorflow: Level 1: Registering GatherTree (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering StatelessRandomNormal (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering StatelessRandomUniform (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering StatelessTruncatedNormal (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering StatelessRandomNormal (None) in gradient.
tensorflow: Level 1: Registering StatelessRandomUniform (None) in gradient.
tensorflow: Level 1: Registering StatelessTruncatedNormal (None) in gradient.
tensorflow: Level 1: Registering ReinterpretStringToFloat (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ScatterAddNdim (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering CreateTreeVariable (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering DecisionTreeResourceHandleOp (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FeatureUsageCounts (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TraverseTreeV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeDeserialize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeIsInitializedOp (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreePredictionsV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeSerialize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeSize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering UpdateModelV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering TreeVariable (None) in gradient.
tensorflow: Level 1: Registering TreeSerialize (None) in gradient.
tensorflow: Level 1: Registering TreeDeserialize (None) in gradient.
tensorflow: Level 1: Registering TreeSize (None) in gradient.
tensorflow: Level 1: Registering TreePredictionsV4 (None) in gradient.
tensorflow: Level 1: Registering FeatureUsageCounts (None) in gradient.
tensorflow: Level 1: Registering CreateFertileStatsVariable (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsDeserialize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsIsInitializedOp (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsResourceHandleOp (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsSerialize (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FinalizeTree (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering GrowTreeV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering ProcessInputV4 (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering FertileStatsVariable (None) in gradient.
tensorflow: Level 1: Registering FertileStatsSerialize (None) in gradient.
tensorflow: Level 1: Registering FertileStatsDeserialize (None) in gradient.
tensorflow: Level 1: Registering GrowTreeV4 (None) in gradient.
tensorflow: Level 1: Registering ProcessInputV4 (None) in gradient.
tensorflow: Level 1: Registering FinalizeTree (None) in gradient.
tensorflow: Level 1: Registering RemoteFusedGraphExecute (<function _set_call_cpp_shape_fn..call_without_requiring at 0x7fa80e11ce18>) in default shape functions.
tensorflow: Level 1: Registering RemoteFusedGraphExecute (None) in gradient.
--------------------- >> end captured logging << ---------------------

Ran 1 test in 0.017s

FAILED (errors=1)

Results are not good for dota dataset

The dataset is dota of whu
These images are cropped into (1200 x 1200) by step 900, about 8000 images.
1.The total mAP is about 0.38 when the global step is 80000, and some classes can not be detected, such as basketball_court, ground_track_field, soccer_ball_field
2.Total loss is declining from 8 to 0.4 when the global step is 260000(it seems to be the limit of this code?). But the mAP is 0.34 and some classes that can be detected in step 80000 can not be detected in step 260000.
I do some changes in the train.py for multi_gpus_train, and I have met the same problem when I use the origin code of one gpu.

楼主求助，这个错误是为什么啊

Traceback (most recent call last):
File "train.py", line 229, in
train()
File "train.py", line 211, in train
summary_str = sess.run(summary_op)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 789, in run
run_metadata_ptr)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 997, in _run
feed_dict_string, options, run_metadata)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1132, in _do_run
target_list, options, run_metadata)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1152, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.UnknownError: exceptions.KeyError: 2
[[Node: draw_boxes_with_categories/PyFunc = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT64, DT_FLOAT], Tout=[DT_UINT8], token="pyfunc_8", _device="/job:localhost/replica:0/task:0/cpu:0"](draw_boxes_with_categories/Squeeze/_2703, fast_rcnn_predict/fast_rcnn_proposals/Gather_6/_2705, fast_rcnn_predict/fast_rcnn_proposals/Gather_8, fast_rcnn_predict/fast_rcnn_proposals/Gather_7/_2707)]]
[[Node: draw_boxes_with_categories/Reshape/tensor/_2709 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_4969_draw_boxes_with_categories/Reshape/tensor", tensor_type=DT_UINT8, _device="/job:localhost/replica:0/task:0/gpu:0"]]

Caused by op u'draw_boxes_with_categories/PyFunc', defined at:
File "train.py", line 229, in
train()
File "train.py", line 125, in train
scores=fast_rcnn_score)
File "../libs/box_utils/show_box_in_tensor.py", line 167, in draw_boxes_with_categories
Tout=[tf.uint8])
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/ops/script_ops.py", line 198, in py_func
input=inp, token=token, Tout=Tout, name=name)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/ops/gen_script_ops.py", line 38, in _py_func
name=name)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2506, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/yin/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1269, in init
self._traceback = _extract_stack()

UnknownError (see above for traceback): exceptions.KeyError: 2
[[Node: draw_boxes_with_categories/PyFunc = PyFunc[Tin=[DT_FLOAT, DT_FLOAT, DT_INT64, DT_FLOAT], Tout=[DT_UINT8], token="pyfunc_8", _device="/job:localhost/replica:0/task:0/cpu:0"](draw_boxes_with_categories/Squeeze/_2703, fast_rcnn_predict/fast_rcnn_proposals/Gather_6/_2705, fast_rcnn_predict/fast_rcnn_proposals/Gather_8, fast_rcnn_predict/fast_rcnn_proposals/Gather_7/_2707)]]
[[Node: draw_boxes_with_categories/Reshape/tensor/_2709 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_4969_draw_boxes_with_categories/Reshape/tensor", tensor_type=DT_UINT8, _device="/job:localhost/replica:0/task:0/gpu:0"]]

it occurs that next problem when i fix above. it seems tfrecord data problem. And first items data seems no problem. Thank you for your any help!

restore model
2018-07-23 20:56:06: step0 image_name:b'38bdd525-f626-4554-92ca-7ec4f95e5b2b.jpg' |
rpn_loc_loss:0.2607109546661377 | rpn_cla_loss:1.163469672203064 | rpn_total_loss:1.4241806268692017 |
fast_rcnn_loc_loss:0.2614363431930542 | fast_rcnn_cla_loss:0.8251640796661377 | fast_rcnn_total_loss:1.086600422859192 |
total_loss:3.1513068675994873 | pre_cost_time:9.237893342971802s
Traceback (most recent call last):
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1327, in _do_call
return fn(*args)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1312, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1420, in _call_tf_sessionrun
status, run_metadata)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 516, in exit
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.OutOfRangeError: PaddingFIFOQueue '_1_get_batch/batch/padding_fifo_queue' is closed and has insufficient elements (requested 1, current size 0)
[[Node: get_batch/batch = QueueDequeueManyV2[component_types=[DT_STRING, DT_FLOAT, DT_INT32, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](get_batch/batch/padding_fifo_queue, get_batch/batch/n)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "train.py", line 229, in
train()
File "train.py", line 211, in train
summary_str = sess.run(summary_op)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 905, in run
run_metadata_ptr)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1140, in _run
feed_dict_tensor, options, run_metadata)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1321, in _do_run
run_metadata)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1340, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: PaddingFIFOQueue '_1_get_batch/batch/padding_fifo_queue' is closed and has insufficient elements (requested 1, current size 0)
[[Node: get_batch/batch = QueueDequeueManyV2[component_types=[DT_STRING, DT_FLOAT, DT_INT32, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](get_batch/batch/padding_fifo_queue, get_batch/batch/n)]]

Caused by op 'get_batch/batch', defined at:
File "train.py", line 229, in
train()
File "train.py", line 34, in train
is_training=True)
File "../data/io/read_tfrecord.py", line 89, in next_batch
dynamic_pad=True)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/training/input.py", line 989, in batch
name=name)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/training/input.py", line 763, in _batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/ops/data_flow_ops.py", line 483, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 3476, in queue_dequeue_many_v2
component_types=component_types, timeout_ms=timeout_ms, name=name)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3290, in create_op
op_def=op_def)
File "/vol/venvs/tf1.7/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1654, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

eval question

This project is only detecting one class?

how to detect three classess ,change the --dataset='1 2 3'?????

restore model 问题

Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2018-10-09 10:11:06.422871: E tensorflow/stream_executor/cuda/cuda_driver.cc:406] failed call to cuInit: CUDA_ERROR_NO_DEVICE
2018-10-09 10:11:06.422917: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:158] retrieving CUDA diagnostic information for host: omnisky
2018-10-09 10:11:06.422927: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:165] hostname: omnisky
2018-10-09 10:11:06.422956: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:189] libcuda reported version is: 390.48.0
2018-10-09 10:11:06.422976: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:369] driver version file contents: """NVRM version: NVIDIA UNIX x86_64 Kernel Module 390.48 Thu Mar 22 00:42:57 PDT 2018
GCC version: gcc version 5.4.0 20160609 (Ubuntu 5.4.0-6ubuntu1~16.04.9)
"""
2018-10-09 10:11:06.422993: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:193] kernel reported version is: 390.48.0
2018-10-09 10:11:06.423002: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:300] kernel version seems to match DSO: 390.48.0
restore model
it is stop.请问是哪里出现错误导致的？
thank you very much !

What should I do if I want to train the VGG network?

Does this code have a corresponding Windows version?

loss不收敛

为什么我训练时loss一直在上下波动，而且什么都检测不出来

Docker images doesn't work

Hi, just wanna tell you that your docker images is for python3 tensorflow but not python2. You can check it by using "pip show tensorflow", then you will find that actually your tensorflow are installed under py35.

I only have py2_tensor1.1 and py3_tensor1.3 images, I will really appreciate it if you can re-upload the docker images. I tried using py3 but get error in many funcs -- not work ... Then I decide to change the code in py2_tensor1.1, and get error from "tf.cond()", even I change the "true/false_fn" to "fn1/fn2". It says that the variable "target_shortside_len" doesn't have variable name, like the following shows:

=============================================================================
Traceback (most recent call last):
File "train.py", line 229, in
train()
File "train.py", line 34, in train
is_training=True)
File "../data/io/read_tfrecord.py", line 81, in next_batch
is_training=is_training)
File "../data/io/read_tfrecord.py", line 56, in read_and_prepocess_single_img
target_shortside_len=shortside_len)
File "../data/io/image_preprocess.py", line 27, in short_side_resize
fn2=lambda: (target_shortside_len * h//w, target_shortside_len))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 1741, in cond
orig_res, res_t = context_t.BuildCondBranch(fn1)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 1668, in BuildCondBranch
real_v = self._ProcessOutputTensor(v)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 1626, in _ProcessOutputTensor
if val.name not in self._values:
AttributeError: 'int' object has no attribute 'name'

Thank you so much!

tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[326704,1203] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc

Had anyone meet this question ?

the batch_size=1 , how would this happen ?

TypeError: cond() got an unexpected keyword argument 'true_fn', i am puzzled with this problem, do you meet this problem before, can you help me?

I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcurand.so locally
tfrecord path is --> /home/hley/software/FPN_Tensorflow/data/tfrecords/pascal_train*
Traceback (most recent call last):
File "train.py", line 229, in
train()
File "train.py", line 34, in train
is_training=True)
File "../data/io/read_tfrecord.py", line 82, in next_batch
is_training=is_training)
File "../data/io/read_tfrecord.py", line 57, in read_and_prepocess_single_img
target_shortside_len=shortside_len)
File "../data/io/image_preprocess.py", line 26, in short_side_resize
false_fn=lambda: (target_shortside_len * h//w, target_shortside_len))
TypeError: cond() got an unexpected keyword argument 'true_fn'

convert_data_to_tfrecord.py error!

Hello,i run convert_data_to_tfrecord.py in python 3.6!
Traceback (most recent call last):
File "convert_data_to_tfrecord.py", line 159, in
convert_pascal_to_tfrecord()
File "convert_data_to_tfrecord.py", line 140, in convert_pascal_to_tfrecord
'img_name': _bytes_feature(img_name),
File "convert_data_to_tfrecord.py", line 28, in _bytes_feature
return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
TypeError: '11222.jpg' has type str, but expected one of: bytes

batchsize=1？大目标效果不太好？

你好，感谢你的代码。我有两个问题，第一，batchsize=1是不是只能增加迭代次数才能使训练的效果好?如果是那至少应该迭代多少次呢?第二，我迭代50000次训练完以后进行inference，发现小目标还能检测出一些，而大目标一个都检测不到，请问这是怎么回事，增加迭代次数能使检测大目标效果提升吗？

Where did the predict_dict.pkl and gtboxes_dict.pkl come from and how to generate them?

It seems that 'predict_dict.pkl' and 'gtboxes_dict.pkl' are required to run eval.py to evaluate the model. Could you please tell me where are the two files from or how to generate the two files?
Thank you. @yangxue0827

直接用作者提供的权重模型无法得到正确的result的图片

我直接使用作者在output里面的模型运行程序，生成的result图片的检测

基本没有准确的，请问这是怎么回事？

Is this Resnet+FPN?

Thanks for your work, it's amazing! I am totally a new guy in DL area, i want to know this code is about Resnet + FPN? I'm not clear about this.

What i know now is that FPN is based on some backbone network such as ResNet, VGG, or other networks.

Thanks for your any help!

How can i use multi_gpu to train and change the BatchSize?

1.It seems that FPN_Tensorflow doesn't support multi-gpu-train mode.
2.When i change the BatchSize from 1 to 64, i get that error:
Traceback (most recent call last):
File "./tools/train.py", line 229, in
train()
File "./tools/train.py", line 38, in train
text=tf.shape(gtboxes_and_label_batch)[1])
File "./tools/../libs/box_utils/show_box_in_tensor.py", line 59, in draw_box_with_color
img_tensor = tf.squeeze(img_batch, 0)
File "/home/rf/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 2630, in squeeze
return gen_array_ops.squeeze(input, axis, name)
File "/home/rf/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 7862, in squeeze
"Squeeze", input=input, squeeze_dims=axis, name=name)
File "/home/rf/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3392, in create_op
op_def=op_def)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1734, in init
control_input_ops)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1570, in _create_c_op
raise ValueError(str(e))
ValueError: Can not squeeze dim[0], expected a dimension of 1, got 64 for 'draw_gtboxes/Squeeze' (op: 'Squeeze') with input shapes: [64,?,?,3].

how can i solve these two problem？

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