SUMIN/HuggingFace_transformer
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Py35 doesn't like inline variable types

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Julien Chaumond
2020-01-13 20:44:33 +00:00
parent b803b067bf
commit 3c86b6f3c5
2 changed files with 4 additions and 2 deletions
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1
setup.cfg
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@@ -20,6 +20,7 @@ known_third_party =
tensorboardX tensorboardX
tensorflow tensorflow
tensorflow_datasets tensorflow_datasets
torch
torchtext torchtext
torchvision torchvision

5
src/transformers/configuration_utils.py
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@@ -38,6 +38,7 @@ class PretrainedConfig(object):
Class attributes (overridden by derived classes): Class attributes (overridden by derived classes):
- ``pretrained_config_archive_map``: a python ``dict`` with `shortcut names` (string) as keys and `url` (string) of associated pretrained model configurations as values. - ``pretrained_config_archive_map``: a python ``dict`` with `shortcut names` (string) as keys and `url` (string) of associated pretrained model configurations as values.
- ``model_type``: a string that identifies the model type, that we serialize into the JSON file, and that we use to recreate the correct object in :class:`~transformers.AutoConfig`.
Parameters: Parameters:
``finetuning_task``: string, default `None`. Name of the task used to fine-tune the model. This can be used when converting from an original (TensorFlow or PyTorch) checkpoint. ``finetuning_task``: string, default `None`. Name of the task used to fine-tune the model. This can be used when converting from an original (TensorFlow or PyTorch) checkpoint.
@@ -46,8 +47,8 @@ class PretrainedConfig(object):
``output_hidden_states``: string, default `False`. Should the model returns all hidden-states. ``output_hidden_states``: string, default `False`. Should the model returns all hidden-states.
``torchscript``: string, default `False`. Is the model used with Torchscript. ``torchscript``: string, default `False`. Is the model used with Torchscript.
""" """
pretrained_config_archive_map: Dict[str, str] = {} pretrained_config_archive_map = {} # type: Dict[str, str]
model_type: str model_type = "" # type: str
def __init__(self, **kwargs): def __init__(self, **kwargs):
# Attributes with defaults # Attributes with defaults