mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-31 18:22:34 +06:00
120 lines
6.0 KiB
Python
120 lines
6.0 KiB
Python
__version__ = "1.2.0"
|
|
|
|
# Work around to update TensorFlow's absl.logging threshold which alters the
|
|
# default Python logging output behavior when present.
|
|
# see: https://github.com/abseil/abseil-py/issues/99
|
|
# and: https://github.com/tensorflow/tensorflow/issues/26691#issuecomment-500369493
|
|
try:
|
|
import absl.logging
|
|
absl.logging.set_verbosity('info')
|
|
absl.logging.set_stderrthreshold('info')
|
|
absl.logging._warn_preinit_stderr = False
|
|
except:
|
|
pass
|
|
|
|
import logging
|
|
|
|
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
|
|
|
|
# Tokenizer
|
|
from .tokenization_utils import (PreTrainedTokenizer)
|
|
from .tokenization_auto import AutoTokenizer
|
|
from .tokenization_bert import BertTokenizer, BasicTokenizer, WordpieceTokenizer
|
|
from .tokenization_openai import OpenAIGPTTokenizer
|
|
from .tokenization_transfo_xl import (TransfoXLTokenizer, TransfoXLCorpus)
|
|
from .tokenization_gpt2 import GPT2Tokenizer
|
|
from .tokenization_xlnet import XLNetTokenizer, SPIECE_UNDERLINE
|
|
from .tokenization_xlm import XLMTokenizer
|
|
from .tokenization_roberta import RobertaTokenizer
|
|
from .tokenization_distilbert import DistilBertTokenizer
|
|
|
|
# Configurations
|
|
from .configuration_utils import PretrainedConfig
|
|
from .configuration_auto import AutoConfig
|
|
from .configuration_bert import BertConfig, BERT_PRETRAINED_CONFIG_ARCHIVE_MAP
|
|
from .configuration_openai import OpenAIGPTConfig, OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP
|
|
from .configuration_transfo_xl import TransfoXLConfig, TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP
|
|
from .configuration_gpt2 import GPT2Config, GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP
|
|
from .configuration_xlnet import XLNetConfig, XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP
|
|
from .configuration_xlm import XLMConfig, XLM_PRETRAINED_CONFIG_ARCHIVE_MAP
|
|
from .configuration_roberta import RobertaConfig, ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP
|
|
from .configuration_distilbert import DistilBertConfig, DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
|
|
|
|
# Modeling
|
|
try:
|
|
import torch
|
|
_torch_available = True # pylint: disable=invalid-name
|
|
except ImportError:
|
|
_torch_available = False # pylint: disable=invalid-name
|
|
|
|
if _torch_available:
|
|
logger.info("PyTorch version {} available.".format(torch.__version__))
|
|
|
|
from .modeling_utils import (PreTrainedModel, prune_layer, Conv1D)
|
|
from .modeling_auto import (AutoModel, AutoModelForSequenceClassification, AutoModelForQuestionAnswering,
|
|
AutoModelWithLMHead)
|
|
|
|
from .modeling_bert import (BertPreTrainedModel, BertModel, BertForPreTraining,
|
|
BertForMaskedLM, BertForNextSentencePrediction,
|
|
BertForSequenceClassification, BertForMultipleChoice,
|
|
BertForTokenClassification, BertForQuestionAnswering,
|
|
load_tf_weights_in_bert, BERT_PRETRAINED_MODEL_ARCHIVE_MAP)
|
|
from .modeling_openai import (OpenAIGPTPreTrainedModel, OpenAIGPTModel,
|
|
OpenAIGPTLMHeadModel, OpenAIGPTDoubleHeadsModel,
|
|
load_tf_weights_in_openai_gpt, OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_MAP)
|
|
from .modeling_transfo_xl import (TransfoXLPreTrainedModel, TransfoXLModel, TransfoXLLMHeadModel,
|
|
load_tf_weights_in_transfo_xl, TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP)
|
|
from .modeling_gpt2 import (GPT2PreTrainedModel, GPT2Model,
|
|
GPT2LMHeadModel, GPT2DoubleHeadsModel,
|
|
load_tf_weights_in_gpt2, GPT2_PRETRAINED_MODEL_ARCHIVE_MAP)
|
|
from .modeling_xlnet import (XLNetPreTrainedModel, XLNetModel, XLNetLMHeadModel,
|
|
XLNetForSequenceClassification, XLNetForQuestionAnswering,
|
|
load_tf_weights_in_xlnet, XLNET_PRETRAINED_MODEL_ARCHIVE_MAP)
|
|
from .modeling_xlm import (XLMPreTrainedModel , XLMModel,
|
|
XLMWithLMHeadModel, XLMForSequenceClassification,
|
|
XLMForQuestionAnswering, XLM_PRETRAINED_MODEL_ARCHIVE_MAP)
|
|
from .modeling_roberta import (RobertaForMaskedLM, RobertaModel, RobertaForSequenceClassification,
|
|
ROBERTA_PRETRAINED_MODEL_ARCHIVE_MAP)
|
|
from .modeling_distilbert import (DistilBertForMaskedLM, DistilBertModel,
|
|
DistilBertForSequenceClassification, DistilBertForQuestionAnswering,
|
|
DISTILBERT_PRETRAINED_MODEL_ARCHIVE_MAP)
|
|
|
|
# Optimization
|
|
from .optimization import (AdamW, ConstantLRSchedule, WarmupConstantSchedule, WarmupCosineSchedule,
|
|
WarmupCosineWithHardRestartsSchedule, WarmupLinearSchedule)
|
|
|
|
|
|
# TensorFlow
|
|
try:
|
|
import tensorflow as tf
|
|
assert int(tf.__version__[0]) >= 2
|
|
_tf_available = True # pylint: disable=invalid-name
|
|
except ImportError:
|
|
_tf_available = False # pylint: disable=invalid-name
|
|
|
|
if _tf_available:
|
|
logger.info("TensorFlow version {} available.".format(tf.__version__))
|
|
|
|
from .modeling_tf_utils import TFPreTrainedModel
|
|
from .modeling_tf_auto import (TFAutoModel, TFAutoModelForSequenceClassification, TFAutoModelForQuestionAnswering,
|
|
TFAutoModelWithLMHead)
|
|
|
|
from .modeling_tf_bert import (TFBertPreTrainedModel, TFBertModel, TFBertForPreTraining,
|
|
TFBertForMaskedLM, TFBertForNextSentencePrediction,
|
|
TFBertForSequenceClassification, TFBertForMultipleChoice,
|
|
TFBertForTokenClassification, TFBertForQuestionAnswering,
|
|
load_bert_pt_weights_in_tf,
|
|
TF_BERT_PRETRAINED_MODEL_ARCHIVE_MAP)
|
|
|
|
|
|
# Files and general utilities
|
|
from .file_utils import (PYTORCH_TRANSFORMERS_CACHE, PYTORCH_PRETRAINED_BERT_CACHE,
|
|
cached_path, add_start_docstrings, add_end_docstrings,
|
|
WEIGHTS_NAME, TF_WEIGHTS_NAME, CONFIG_NAME)
|
|
|
|
def is_torch_available():
|
|
return _torch_available
|
|
|
|
def is_tf_available():
|
|
return _tf_available
|