





import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
UpperCamelCase__   : List[str]					  = logging.getLogger(__name__)

if __name__ == "__main__":
				UpperCamelCase__   : List[Any]					  = argparse.ArgumentParser(
				    description="""Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)"""
				)
				parser.add_argument(
				    """--data_file""", type=str, default="""data/dump.bert-base-uncased.pickle""", help="""The binarized dataset."""
				)
				parser.add_argument(
				    """--token_counts_dump""", type=str, default="""data/token_counts.bert-base-uncased.pickle""", help="""The dump file."""
				)
				parser.add_argument("""--vocab_size""", default=3_05_22, type=int)
				UpperCamelCase__   : Optional[int]					  = parser.parse_args()

				logger.info(f"Loading data from {args.data_file}")
				with open(args.data_file, """rb""") as fp:
								UpperCamelCase__   : List[Any]					  = pickle.load(fp)

				logger.info("""Counting occurrences for MLM.""")
				UpperCamelCase__   : Optional[int]					  = Counter()
				for tk_ids in data:
								counter.update(tk_ids)
				UpperCamelCase__   : Optional[Any]					  = [0] * args.vocab_size
				for k, v in counter.items():
								UpperCamelCase__   : int					  = v

				logger.info(f"Dump to {args.token_counts_dump}")
				with open(args.token_counts_dump, """wb""") as handle:
								pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)









from __future__ import annotations

import unittest

from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow


if is_tf_available():
				from transformers import (
				    AutoConfig,
				    BertConfig,
				    GPTaConfig,
				    TaConfig,
				    TFAutoModel,
				    TFAutoModelForCausalLM,
				    TFAutoModelForMaskedLM,
				    TFAutoModelForPreTraining,
				    TFAutoModelForQuestionAnswering,
				    TFAutoModelForSeqaSeqLM,
				    TFAutoModelForSequenceClassification,
				    TFAutoModelWithLMHead,
				    TFBertForMaskedLM,
				    TFBertForPreTraining,
				    TFBertForQuestionAnswering,
				    TFBertForSequenceClassification,
				    TFBertModel,
				    TFGPTaLMHeadModel,
				    TFRobertaForMaskedLM,
				    TFTaForConditionalGeneration,
				)
				from transformers.models.bert.modeling_tf_bert import TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST
				from transformers.models.gpta.modeling_tf_gpta import TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST
				from transformers.models.ta.modeling_tf_ta import TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST

if is_torch_available():
				from transformers import (
				    AutoModel,
				    AutoModelForCausalLM,
				    AutoModelForMaskedLM,
				    AutoModelForPreTraining,
				    AutoModelForQuestionAnswering,
				    AutoModelForSeqaSeqLM,
				    AutoModelForSequenceClassification,
				    AutoModelWithLMHead,
				    BertForMaskedLM,
				    BertForPreTraining,
				    BertForQuestionAnswering,
				    BertForSequenceClassification,
				    BertModel,
				    GPTaLMHeadModel,
				    RobertaForMaskedLM,
				    TaForConditionalGeneration,
				)







@is_pt_tf_cross_test
class   _UpperCamelCase  (       unittest.TestCase  ):







					'''simple docstring'''

					@slow
					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						for model_name in ["bert-base-uncased"]:
							UpperCAmelCase_								=     AutoConfig.from_pretrained(__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     TFAutoModel.from_pretrained(__lowercase ,					from_pt=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     AutoModel.from_pretrained(__lowercase ,					from_tf=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)





					@slow
					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						for model_name in ["bert-base-uncased"]:
							UpperCAmelCase_								=     AutoConfig.from_pretrained(__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     TFAutoModelForPreTraining.from_pretrained(__lowercase ,					from_pt=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     AutoModelForPreTraining.from_pretrained(__lowercase ,					from_tf=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)





					@slow
					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						for model_name in TF_GPT2_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
							UpperCAmelCase_								=     AutoConfig.from_pretrained(__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     TFAutoModelForCausalLM.from_pretrained(__lowercase ,					from_pt=__lowercase		)
							UpperCAmelCase_						,	UpperCAmelCase_								=     TFAutoModelForCausalLM.from_pretrained(
							    __lowercase ,					output_loading_info=__lowercase ,					from_pt=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     AutoModelForCausalLM.from_pretrained(__lowercase ,					from_tf=__lowercase		)
							UpperCAmelCase_						,	UpperCAmelCase_								=     AutoModelForCausalLM.from_pretrained(
							    __lowercase ,					output_loading_info=__lowercase ,					from_tf=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)





					@slow
					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any]		):






						'''simple docstring'''







						for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
							UpperCAmelCase_								=     AutoConfig.from_pretrained(__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     TFAutoModelWithLMHead.from_pretrained(__lowercase ,					from_pt=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     AutoModelWithLMHead.from_pretrained(__lowercase ,					from_tf=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)





					@slow
					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						for model_name in TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
							UpperCAmelCase_								=     AutoConfig.from_pretrained(__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     TFAutoModelForMaskedLM.from_pretrained(__lowercase ,					from_pt=__lowercase		)
							UpperCAmelCase_						,	UpperCAmelCase_								=     TFAutoModelForMaskedLM.from_pretrained(
							    __lowercase ,					output_loading_info=__lowercase ,					from_pt=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     AutoModelForMaskedLM.from_pretrained(__lowercase ,					from_tf=__lowercase		)
							UpperCAmelCase_						,	UpperCAmelCase_								=     AutoModelForMaskedLM.from_pretrained(
							    __lowercase ,					output_loading_info=__lowercase ,					from_tf=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)





					@slow
					def        SCREAMING_SNAKE_CASE							(						self    :  Union[str, Any]		):






						'''simple docstring'''







						for model_name in TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
							UpperCAmelCase_								=     AutoConfig.from_pretrained(__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     TFAutoModelForSeqaSeqLM.from_pretrained(__lowercase ,					from_pt=__lowercase		)
							UpperCAmelCase_						,	UpperCAmelCase_								=     TFAutoModelForSeqaSeqLM.from_pretrained(
							    __lowercase ,					output_loading_info=__lowercase ,					from_pt=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     AutoModelForSeqaSeqLM.from_pretrained(__lowercase ,					from_tf=__lowercase		)
							UpperCAmelCase_						,	UpperCAmelCase_								=     AutoModelForSeqaSeqLM.from_pretrained(
							    __lowercase ,					output_loading_info=__lowercase ,					from_tf=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)





					@slow
					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[int]		):






						'''simple docstring'''







						for model_name in ["bert-base-uncased"]:
							UpperCAmelCase_								=     AutoConfig.from_pretrained(__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     TFAutoModelForSequenceClassification.from_pretrained(__lowercase ,					from_pt=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     AutoModelForSequenceClassification.from_pretrained(__lowercase ,					from_tf=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)





					@slow
					def        SCREAMING_SNAKE_CASE							(						self    :  str		):






						'''simple docstring'''







						for model_name in ["bert-base-uncased"]:
							UpperCAmelCase_								=     AutoConfig.from_pretrained(__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     TFAutoModelForQuestionAnswering.from_pretrained(__lowercase ,					from_pt=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)

							UpperCAmelCase_								=     AutoModelForQuestionAnswering.from_pretrained(__lowercase ,					from_tf=__lowercase		)
							self.assertIsNotNone(__lowercase		)
							self.assertIsInstance(__lowercase ,					__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple		):






						'''simple docstring'''







						UpperCAmelCase_								=     TFAutoModelWithLMHead.from_pretrained(__lowercase ,					from_pt=__lowercase		)
						self.assertIsInstance(__lowercase ,					__lowercase		)
						self.assertEqual(model.num_parameters() ,					1_44_10		)
						self.assertEqual(model.num_parameters(only_trainable=__lowercase		) ,					1_44_10		)

						UpperCAmelCase_								=     AutoModelWithLMHead.from_pretrained(__lowercase ,					from_tf=__lowercase		)
						self.assertIsInstance(__lowercase ,					__lowercase		)
						self.assertEqual(model.num_parameters() ,					1_44_10		)
						self.assertEqual(model.num_parameters(only_trainable=__lowercase		) ,					1_44_10		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     TFAutoModelWithLMHead.from_pretrained(__lowercase ,					from_pt=__lowercase		)
						self.assertIsInstance(__lowercase ,					__lowercase		)
						self.assertEqual(model.num_parameters() ,					1_44_10		)
						self.assertEqual(model.num_parameters(only_trainable=__lowercase		) ,					1_44_10		)

						UpperCAmelCase_								=     AutoModelWithLMHead.from_pretrained(__lowercase ,					from_tf=__lowercase		)
						self.assertIsInstance(__lowercase ,					__lowercase		)
						self.assertEqual(model.num_parameters() ,					1_44_10		)
						self.assertEqual(model.num_parameters(only_trainable=__lowercase		) ,					1_44_10		)


