Colab VERIFICATION_SCRIPT ModuleNotFoundError: No module named 'tensorflow.python.keras.applications' about tfodcourse HOT 4 OPEN

install 'tf-models-official==2.7.1',

you can also change the script:
Tensorflow/models/research/object_detection/packages/tf2/setup.py

'tf-models-official==2.7.1',

from tfodcourse.

Hi SauBuen,
Thanks but did not work fully. Passes the verification script but now fails at the training script:

python Tensorflow/models/research/object_detection/model_main_tf2.py --model_dir=Tensorflow/workspace/models/Seep_ssd_mobnet --pipeline_config_path=Tensorflow/workspace/models/Seep_ssd_mobnet/pipeline.config --num_train_steps=2000

2022-02-08 10:31:17.000189: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-08 10:31:17.009763: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-08 10:31:17.010590: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-08 10:31:17.011815: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-02-08 10:31:17.012111: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-08 10:31:17.012903: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-08 10:31:17.013704: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-08 10:31:17.570257: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-08 10:31:17.571145: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-08 10:31:17.571903: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-02-08 10:31:17.572642: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.
2022-02-08 10:31:17.572721: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 10663 MB memory: -> device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7
INFO:tensorflow:Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',)
I0208 10:31:17.578470 139906285909888 mirrored_strategy.py:369] Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',)
INFO:tensorflow:Maybe overwriting train_steps: 2000
I0208 10:31:17.583169 139906285909888 config_util.py:552] Maybe overwriting train_steps: 2000
INFO:tensorflow:Maybe overwriting use_bfloat16: False
I0208 10:31:17.583358 139906285909888 config_util.py:552] Maybe overwriting use_bfloat16: False
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py:564: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version.
Instructions for updating:
rename to distribute_datasets_from_function
W0208 10:31:17.613617 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py:564: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version.
Instructions for updating:
rename to distribute_datasets_from_function
INFO:tensorflow:Reading unweighted datasets: ['Tensorflow/workspace/annotations/train.record']
I0208 10:31:17.618627 139906285909888 dataset_builder.py:163] Reading unweighted datasets: ['Tensorflow/workspace/annotations/train.record']
INFO:tensorflow:Reading record datasets for input file: ['Tensorflow/workspace/annotations/train.record']
I0208 10:31:17.618862 139906285909888 dataset_builder.py:80] Reading record datasets for input file: ['Tensorflow/workspace/annotations/train.record']
INFO:tensorflow:Number of filenames to read: 1
I0208 10:31:17.619039 139906285909888 dataset_builder.py:81] Number of filenames to read: 1
WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.
W0208 10:31:17.619182 139906285909888 dataset_builder.py:88] num_readers has been reduced to 1 to match input file shards.
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE) instead. If sloppy execution is desired, use tf.data.Options.experimental_deterministic.
W0208 10:31:17.622419 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE) instead. If sloppy execution is desired, use tf.data.Options.experimental_deterministic.
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.data.Dataset.map() W0208 10:31:17.646344 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.data.Dataset.map()
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Create a tf.sparse.SparseTensor and use tf.sparse.to_dense instead.
W0208 10:31:26.506816 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Create a tf.sparse.SparseTensor and use tf.sparse.to_dense instead.
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version.
Instructions for updating:
seed2 arg is deprecated.Use sample_distorted_bounding_box_v2 instead.
W0208 10:31:30.294101 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version.
Instructions for updating:
seed2 arg is deprecated.Use sample_distorted_bounding_box_v2 instead.
WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py:464: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.cast instead.
W0208 10:31:32.181428 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py:464: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.cast instead.
2022-02-08 10:31:34.971475: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)
/usr/local/lib/python3.7/dist-packages/keras/backend.py:401: UserWarning: tf.keras.backend.set_learning_phase is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the training argument of the __call__ method of your layer or model.
warnings.warn('tf.keras.backend.set_learning_phase is deprecated and '
2022-02-08 10:31:58.458210: E tensorflow/stream_executor/cuda/cuda_dnn.cc:362] Loaded runtime CuDNN library: 8.0.5 but source was compiled with: 8.1.0. CuDNN library needs to have matching major version and equal or higher minor version. If using a binary install, upgrade your CuDNN library. If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.
2022-02-08 10:31:58.461067: E tensorflow/stream_executor/cuda/cuda_dnn.cc:362] Loaded runtime CuDNN library: 8.0.5 but source was compiled with: 8.1.0. CuDNN library needs to have matching major version and equal or higher minor version. If using a binary install, upgrade your CuDNN library. If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.
Traceback (most recent call last):
File "Tensorflow/models/research/object_detection/model_main_tf2.py", line 115, in
tf.compat.v1.app.run()
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/platform/app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "/usr/local/lib/python3.7/dist-packages/absl/app.py", line 312, in run
_run_main(main, args)
File "/usr/local/lib/python3.7/dist-packages/absl/app.py", line 258, in _run_main
sys.exit(main(argv))
File "Tensorflow/models/research/object_detection/model_main_tf2.py", line 112, in main
record_summaries=FLAGS.record_summaries)
File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 609, in train_loop
train_input, unpad_groundtruth_tensors)
File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 400, in load_fine_tune_checkpoint
_ensure_model_is_built(model, input_dataset, unpad_groundtruth_tensors)
File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 178, in _ensure_model_is_built
labels,
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py", line 1286, in run
return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py", line 2849, in call_for_each_replica
return self._call_for_each_replica(fn, args, kwargs)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/mirrored_strategy.py", line 671, in _call_for_each_replica
self._container_strategy(), fn, args, kwargs)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/mirrored_run.py", line 86, in call_for_each_replica
return wrapped(args, kwargs)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/def_function.py", line 885, in call
result = self._call(*args, **kwds)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/def_function.py", line 950, in _call
return self._stateless_fn(*args, **kwds)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/function.py", line 3040, in call
filtered_flat_args, captured_inputs=graph_function.captured_inputs) # pylint: disable=protected-access
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/function.py", line 1964, in _call_flat
ctx, args, cancellation_manager=cancellation_manager))
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/function.py", line 596, in call
ctx=ctx)
File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py", line 60, in quick_execute
inputs, attrs, num_outputs)
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node ssd_mobile_net_v2fpn_keras_feature_extractor/model/Conv1/Conv2D (defined at /usr/local/lib/python3.7/dist-packages/object_detection/models/ssd_mobilenet_v2_fpn_keras_feature_extractor.py:219) ]] [Op:__inference__dummy_computation_fn_15081]

Errors may have originated from an input operation.
Input Source operations connected to node ssd_mobile_net_v2fpn_keras_feature_extractor/model/Conv1/Conv2D:
args_1 (defined at /usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py:178)

Function call stack:
_dummy_computation_fn

from tfodcourse.

Now I am having the same issue, before it was working

from tfodcourse.

I asked this same question in the TensorFlow models guithub issue#10505
I think there it is more probable to get help there

from tfodcourse.