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update sequencesummary module

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This commit is contained in:
thomwolf
2019-07-09 15:46:43 +02:00
parent d5481cbe1b
commit d0efbd3cd1
5 changed files with 15 additions and 2 deletions
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1
.coveragerc
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@@ -3,6 +3,7 @@ source=pytorch_transformers
omit = omit =
# skip convertion scripts from testing for now # skip convertion scripts from testing for now
*/convert_* */convert_*
*/__main__.py
[report] [report]
exclude_lines = exclude_lines =
pragma: no cover pragma: no cover

2
examples/test_examples.py
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@@ -48,7 +48,7 @@ class ExamplesTests(unittest.TestCase):
testargs = ["run_glue.py", "--data_dir=./examples/tests_samples/MRPC/", testargs = ["run_glue.py", "--data_dir=./examples/tests_samples/MRPC/",
"--task_name=mrpc", "--do_train", "--do_eval", "--output_dir=./examples/tests_samples/temp_dir", "--task_name=mrpc", "--do_train", "--do_eval", "--output_dir=./examples/tests_samples/temp_dir",
"--train_batch_size=4", "--eval_batch_size=2", "--num_train_epochs=2.0", "--overwrite_output_dir"] "--train_batch_size=4", "--eval_batch_size=2", "--num_train_epochs=2.0", "--overwrite_output_dir"]
model_name = "--model_name=xlnet-large-cased" model_name = "--model_name=bert-base-uncased"
with patch.object(sys, 'argv', testargs + [model_name]): with patch.object(sys, 'argv', testargs + [model_name]):
result = run_glue.main() result = run_glue.main()
for value in result.values(): for value in result.values():

6
pytorch_transformers/modeling_gpt2.py
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@@ -119,9 +119,12 @@ class GPT2Config(PretrainedConfig):
layer_norm_epsilon=1e-5, layer_norm_epsilon=1e-5,
initializer_range=0.02, initializer_range=0.02,
predict_special_tokens=True, predict_special_tokens=True,
num_labels=1,
summary_type='token_ids', summary_type='token_ids',
summary_use_proj=True, summary_use_proj=True,
summary_activation=None, summary_activation=None,
summary_proj_to_labels=True,
summary_first_dropout=0.1, summary_first_dropout=0.1,
**kwargs **kwargs
): ):
@@ -168,10 +171,13 @@ class GPT2Config(PretrainedConfig):
self.layer_norm_epsilon = layer_norm_epsilon self.layer_norm_epsilon = layer_norm_epsilon
self.initializer_range = initializer_range self.initializer_range = initializer_range
self.predict_special_tokens = predict_special_tokens self.predict_special_tokens = predict_special_tokens
self.num_labels = num_labels
self.summary_type = summary_type self.summary_type = summary_type
self.summary_use_proj = summary_use_proj self.summary_use_proj = summary_use_proj
self.summary_activation = summary_activation self.summary_activation = summary_activation
self.summary_first_dropout = summary_first_dropout self.summary_first_dropout = summary_first_dropout
self.summary_proj_to_labels = summary_proj_to_labels
else: else:
raise ValueError( raise ValueError(
"First argument must be either a vocabulary size (int)" "First argument must be either a vocabulary size (int)"

6
pytorch_transformers/modeling_openai.py
View File

@@ -147,9 +147,12 @@ class OpenAIGPTConfig(PretrainedConfig):
layer_norm_epsilon=1e-5, layer_norm_epsilon=1e-5,
initializer_range=0.02, initializer_range=0.02,
predict_special_tokens=True, predict_special_tokens=True,
num_labels=1,
summary_type='token_ids', summary_type='token_ids',
summary_use_proj=True, summary_use_proj=True,
summary_activation=None, summary_activation=None,
summary_proj_to_labels=True,
summary_first_dropout=0.1, summary_first_dropout=0.1,
**kwargs **kwargs
): ):
@@ -199,10 +202,13 @@ class OpenAIGPTConfig(PretrainedConfig):
self.layer_norm_epsilon = layer_norm_epsilon self.layer_norm_epsilon = layer_norm_epsilon
self.initializer_range = initializer_range self.initializer_range = initializer_range
self.predict_special_tokens = predict_special_tokens self.predict_special_tokens = predict_special_tokens
self.num_labels = num_labels
self.summary_type = summary_type self.summary_type = summary_type
self.summary_use_proj = summary_use_proj self.summary_use_proj = summary_use_proj
self.summary_activation = summary_activation self.summary_activation = summary_activation
self.summary_first_dropout = summary_first_dropout self.summary_first_dropout = summary_first_dropout
self.summary_proj_to_labels = summary_proj_to_labels
else: else:
raise ValueError( raise ValueError(
"First argument must be either a vocabulary size (int)" "First argument must be either a vocabulary size (int)"