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Fast imports part 3 (#9474)

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* New intermediate inits

* Update template

* Avoid importing torch/tf/flax in tokenization unless necessary

* Styling

* Shutup flake8

* Better python version check
This commit is contained in:
Sylvain Gugger
2021-01-08 07:40:59 -05:00
committed by GitHub
parent 79bbcc5260
commit 1bdf42409c
50 changed files with 3205 additions and 828 deletions
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118
src/transformers/models/mpnet/__init__.py
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@@ -16,37 +16,101 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from ...file_utils import is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available
from .configuration_mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig
from .tokenization_mpnet import MPNetTokenizer
from typing import TYPE_CHECKING
from ...file_utils import (
_BaseLazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_import_structure = {
"configuration_mpnet": ["MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "MPNetConfig"],
"tokenization_mpnet": ["MPNetTokenizer"],
}
if is_tokenizers_available():
from .tokenization_mpnet_fast import MPNetTokenizerFast
_import_structure["tokenization_mpnet_fast"] = ["MPNetTokenizerFast"]
if is_torch_available():
from .modeling_mpnet import (
MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
MPNetForMaskedLM,
MPNetForMultipleChoice,
MPNetForQuestionAnswering,
MPNetForSequenceClassification,
MPNetForTokenClassification,
MPNetLayer,
MPNetModel,
MPNetPreTrainedModel,
)
_import_structure["modeling_mpnet"] = [
"MPNET_PRETRAINED_MODEL_ARCHIVE_LIST",
"MPNetForMaskedLM",
"MPNetForMultipleChoice",
"MPNetForQuestionAnswering",
"MPNetForSequenceClassification",
"MPNetForTokenClassification",
"MPNetLayer",
"MPNetModel",
"MPNetPreTrainedModel",
]
if is_tf_available():
from .modeling_tf_mpnet import (
TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
TFMPNetEmbeddings,
TFMPNetForMaskedLM,
TFMPNetForMultipleChoice,
TFMPNetForQuestionAnswering,
TFMPNetForSequenceClassification,
TFMPNetForTokenClassification,
TFMPNetMainLayer,
TFMPNetModel,
TFMPNetPreTrainedModel,
)
_import_structure["modeling_tf_mpnet"] = [
"TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST",
"TFMPNetEmbeddings",
"TFMPNetForMaskedLM",
"TFMPNetForMultipleChoice",
"TFMPNetForQuestionAnswering",
"TFMPNetForSequenceClassification",
"TFMPNetForTokenClassification",
"TFMPNetMainLayer",
"TFMPNetModel",
"TFMPNetPreTrainedModel",
]
if TYPE_CHECKING:
from .configuration_mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig
from .tokenization_mpnet import MPNetTokenizer
if is_tokenizers_available():
from .tokenization_mpnet_fast import MPNetTokenizerFast
if is_torch_available():
from .modeling_mpnet import (
MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
MPNetForMaskedLM,
MPNetForMultipleChoice,
MPNetForQuestionAnswering,
MPNetForSequenceClassification,
MPNetForTokenClassification,
MPNetLayer,
MPNetModel,
MPNetPreTrainedModel,
)
if is_tf_available():
from .modeling_tf_mpnet import (
TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
TFMPNetEmbeddings,
TFMPNetForMaskedLM,
TFMPNetForMultipleChoice,
TFMPNetForQuestionAnswering,
TFMPNetForSequenceClassification,
TFMPNetForTokenClassification,
TFMPNetMainLayer,
TFMPNetModel,
TFMPNetPreTrainedModel,
)
else:
import importlib
import os
import sys
class _LazyModule(_BaseLazyModule):
"""
Module class that surfaces all objects but only performs associated imports when the objects are requested.
"""
__file__ = globals()["__file__"]
__path__ = [os.path.dirname(__file__)]
def _get_module(self, module_name: str):
return importlib.import_module("." + module_name, self.__name__)
sys.modules[__name__] = _LazyModule(__name__, _import_structure)