jungokasai / graph_parser Goto Github PK

Hi Jungo,

I'm interested in your work and I'm trying to run your pre-trained model. I followed the procedure as in your readme file, downloaded the GLOVE and PRE-TRAINED model in corresponding directory. However, it gives me this error. It seems like the problem(so far) is the inconsistent shape of word embedding layer.

Full information listed as follow:
Run joint training. Use gold supertags
D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained/Pretrained_Parser
Found 39549 unique lowercased words including -unseen- and <-root->.
Indexing word vectors.
Found 400000 word vectors.
Found 400000 words not in the training set but in the glove data
end glove indexing
Found 80 unique characters including -unseen-. NOT including <-root->.
Found 47 unique POS tags including -unseen- and <-root->.
D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\utils\data_loader\data_process_secsplit.py:159: FutureWarning: arrays to stack must be passed as a "sequence" type suc
h as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.
self.gold_jk = np.hstack(map(lambda x: x[1:], jk_sequences[self.nb_train_samples:]))
Found 4728 unique supertags including -unseen- and <-root->.
D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\utils\data_loader\data_process_secsplit.py:187: FutureWarning: arrays to stack must be passed as a "sequence" type suc
h as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.
self.gold_stags = np.hstack(map(lambda x: x[1:], tag_sequences[self.nb_train_samples:]))
Found 11 unique rels including -unseen-, NOT including <-root->.
D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\utils\data_loader\data_process_secsplit.py:214: FutureWarning: arrays to stack must be passed as a "sequence" type suc
h as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.
self.gold_rels = np.hstack(map(lambda x: x[1:], rel_sequences[self.nb_train_samples:]))
2019-01-18 17:21:22.497084: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
Traceback (most recent call last):
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\client\session.py", line 1334, in _do_call
return fn(*args)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\client\session.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\client\session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [439550,100] rhs shape= [405687,100]
[[{{node save/Assign_443}} = Assign[T=DT_FLOAT, _class=["loc:@word_embedding/word_embedding_mat"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task
:0/device:CPU:0"](word_embedding/word_embedding_mat/Adam, save/RestoreV2:443)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 1546, in restore
{self.saver_def.filename_tensor_name: save_path})
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\client\session.py", line 929, in run
run_metadata_ptr)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\client\session.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\client\session.py", line 1328, in _do_run
run_metadata)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\client\session.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [439550,100] rhs shape= [405687,100]
[[node save/Assign_443 (defined at D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\graph_parser_model.py:60) = Assign[T=DT_FLOAT, _class=["loc:@word_embeddi
ng/word_embedding_mat"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](word_embedding/word_embedding_mat/Adam, save/RestoreV2:443)]]

Caused by op 'save/Assign_443', defined at:
File "D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/graph_parser_main.py", line 134, in
run_model_test(options, opts)
File "D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\graph_parser_model.py", line 60, in run_model_test
saver = tf.train.Saver(max_to_keep=1)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 1102, in init
self.build()
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 1114, in build
self._build(self._filename, build_save=True, build_restore=True)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 1151, in _build
build_save=build_save, build_restore=build_restore)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 795, in _build_internal
restore_sequentially, reshape)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 428, in _AddRestoreOps
assign_ops.append(saveable.restore(saveable_tensors, shapes))
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 119, in restore
self.op.get_shape().is_fully_defined())
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\ops\state_ops.py", line 221, in assign
validate_shape=validate_shape)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\ops\gen_state_ops.py", line 64, in assign
use_locking=use_locking, name=name)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\util\deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\framework\ops.py", line 3274, in create_op
op_def=op_def)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\framework\ops.py", line 1770, in init
self._traceback = tf_stack.extract_stack()

InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [439550,100] rhs shape= [405687,100]
[[node save/Assign_443 (defined at D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\graph_parser_model.py:60) = Assign[T=DT_FLOAT, _class=["loc:@word_embeddi
ng/word_embedding_mat"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](word_embedding/word_embedding_mat/Adam, save/RestoreV2:443)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/graph_parser_main.py", line 134, in
run_model_test(options, opts)
File "D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\graph_parser_model.py", line 63, in run_model_test
saver.restore(session, test_opts.modelname)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 1582, in restore
err, "a mismatch between the current graph and the graph")
tensorflow.python.framework.errors_impl.InvalidArgumentError: Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the ch
eckpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

Assign requires shapes of both tensors to match. lhs shape= [439550,100] rhs shape= [405687,100]
[[node save/Assign_443 (defined at D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\graph_parser_model.py:60) = Assign[T=DT_FLOAT, _class=["loc:@word_embeddi
ng/word_embedding_mat"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](word_embedding/word_embedding_mat/Adam, save/RestoreV2:443)]]

Caused by op 'save/Assign_443', defined at:
File "D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/graph_parser_main.py", line 134, in
run_model_test(options, opts)
File "D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\graph_parser_model.py", line 60, in run_model_test
saver = tf.train.Saver(max_to_keep=1)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 1102, in init
self.build()
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 1114, in build
self._build(self._filename, build_save=True, build_restore=True)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 1151, in _build
build_save=build_save, build_restore=build_restore)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 795, in _build_internal
restore_sequentially, reshape)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 428, in _AddRestoreOps
assign_ops.append(saveable.restore(saveable_tensors, shapes))
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\training\saver.py", line 119, in restore
self.op.get_shape().is_fully_defined())
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\ops\state_ops.py", line 221, in assign
validate_shape=validate_shape)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\ops\gen_state_ops.py", line 64, in assign
use_locking=use_locking, name=name)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\util\deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\framework\ops.py", line 3274, in create_op
op_def=op_def)
File "D:\research\Anaconda3\envs\tf_cpu\lib\site-packages\tensorflow\python\framework\ops.py", line 1770, in init
self._traceback = tf_stack.extract_stack()

InvalidArgumentError (see above for traceback): Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Plea
se ensure that you have not altered the graph expected based on the checkpoint. Original error:

Assign requires shapes of both tensors to match. lhs shape= [439550,100] rhs shape= [405687,100]
[[node save/Assign_443 (defined at D:\Research\PyCharmProject\graph_parser-master\graph_parser-master\graph_parser_model.py:60) = Assign[T=DT_FLOAT, _class=["loc:@word_embeddi
ng/word_embedding_mat"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](word_embedding/word_embedding_mat/Adam, save/RestoreV2:443)]]

Traceback (most recent call last):
File "D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/scripts/run_pretrained.py", line 117, in
nmsl_parser(config_file, best_model, data_types, opts.no_gold, opts.pretrained)
File "D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/scripts/run_pretrained.py", line 105, in nmsl_parser
subprocess.check_call(complete_command, shell=True)
File "D:\Research\Anaconda3\envs\tf_cpu\lib\subprocess.py", line 271, in check_call
raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command 'D:/research/Anaconda3/envs/tf_cpu/python.exe D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/graph_parser_main.py test --base_
dir D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained --pretrained --pretrained --model D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pr
etrained/Pretrained_Parser/best_model --predicted_stags_file D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained\predicted_stag\test.txt --predicted_pos_file D
:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained\predicted_pos\test.txt --predicted_arcs_file D:/Research/PyCharmProject/graph_parser-master/graph_parser-mas
ter/pretrained\predicted_arcs\test.txt --predicted_rels_file D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained\predicted_rels\test.txt --predicted_arcs_file_
greedy D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained\predicted_arcs_greedy\test.txt --predicted_rels_file_greedy D:/Research/PyCharmProject/graph_parser-
master/graph_parser-master/pretrained\predicted_rels_greedy\test.txt --text_test D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained\sents\test.txt --jk_test D
:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained\sents\test.txt --tag_test D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained\sent
s\test.txt --arc_test D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained\sents\test.txt --rel_test D:/Research/PyCharmProject/graph_parser-master/graph_parser
-master/pretrained\sents\test.txt --punc_test D:/Research/PyCharmProject/graph_parser-master/graph_parser-master/pretrained\punc\test.txt --metrics NoPunct_LAS_Both NoPunct_LAS NoPunct_
UAS Stagging POS' returned non-zero exit status 1