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fix test when tf is not here

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thomwolf
2019-09-05 02:53:52 +02:00
parent 59fe641b8b
commit ad0ab9afe9
4 changed files with 101 additions and 46 deletions
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90
pytorch_transformers/__init__.py
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@@ -1,4 +1,5 @@
__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
@@ -11,6 +12,10 @@ try:
except:
pass
import logging
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
# Tokenizer
from .tokenization_utils import (PreTrainedTokenizer)
from .tokenization_auto import AutoTokenizer
@@ -36,38 +41,63 @@ from .configuration_roberta import RobertaConfig, ROBERTA_PRETRAINED_CONFIG_ARCH
from .configuration_distilbert import DistilBertConfig, DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
# Modeling
from .modeling_utils import (PreTrainedModel, prune_layer, Conv1D)
from .modeling_auto import (AutoModel, AutoModelForSequenceClassification, AutoModelForQuestionAnswering,
AutoModelWithLMHead)
try:
import torch
torch_available = True # pylint: disable=invalid-name
except ImportError:
torch_available = False # pylint: disable=invalid-name
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)
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
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_bert import (TFBertPreTrainedModel, TFBertModel, TFBertForPreTraining,
TFBertForMaskedLM, TFBertForNextSentencePrediction, load_pt_weights_in_bert)
# Optimization
from .optimization import (AdamW, ConstantLRSchedule, WarmupConstantSchedule, WarmupCosineSchedule,
WarmupCosineWithHardRestartsSchedule, WarmupLinearSchedule)
# Files and general utilities
from .file_utils import (PYTORCH_TRANSFORMERS_CACHE, PYTORCH_PRETRAINED_BERT_CACHE,