



import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


lowercase_								=     get_tests_dir("""fixtures/test_sentencepiece.model""")

if is_torch_available():
							from transformers.models.mbart.modeling_mbart import shift_tokens_right

lowercase_								=     25_0004
lowercase_								=     25_0020
@require_sentencepiece
@require_tokenizers
class 				_snake_case			(					lowercase__    ,	unittest.TestCase):
				UpperCamelCase__				:					Optional[Any]     		=MBartaaTokenizer
				UpperCamelCase__				:					Tuple     		=MBartaaTokenizerFast
				UpperCamelCase__				:					Tuple     		=True
				UpperCamelCase__				:					Dict     		=True




				def 							A__      (						self					:						Tuple						):
							super().setUp()

							# We have a SentencePiece fixture for testing
							lowercase__					  =				MBartaaTokenizer(__lowercase,					src_lang="en_XX",					tgt_lang="ro_RO",					keep_accents=__lowercase						)
							tokenizer.save_pretrained(self.tmpdirname						)




				def 							A__      (						self					:						Dict						):
							lowercase__					  =				"<s>"
							lowercase__					  =				0

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowercase						),					__lowercase						)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowercase						),					__lowercase						)




				def 							A__      (						self					:						List[Any]						):
							lowercase__					  =				list(self.get_tokenizer().get_vocab().keys()						)

							self.assertEqual(vocab_keys[0],					"<s>"						)
							self.assertEqual(vocab_keys[1],					"<pad>"						)
							self.assertEqual(vocab_keys[-1],					"<mask>"						)
							self.assertEqual(len(__lowercase						),					1054						)




				def 							A__      (						self					:						Union[str, Any]						):
							self.assertEqual(self.get_tokenizer().vocab_size,					1054						)




				def 							A__      (						self					:						List[Any]						):
							lowercase__					  =				MBartaaTokenizer(__lowercase,					src_lang="en_XX",					tgt_lang="ro_RO",					keep_accents=__lowercase						)

							lowercase__					  =				tokenizer.tokenize("This is a test"						)
							self.assertListEqual(__lowercase,					["▁This", "▁is", "▁a", "▁t", "est"]						)

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(__lowercase						),					[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]],					)

							lowercase__					  =				tokenizer.tokenize("I was born in 92000, and this is falsé."						)
							self.assertListEqual(
							    __lowercase,					[SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "9", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "é", "."],					)
							lowercase__					  =				tokenizer.convert_tokens_to_ids(__lowercase						)
							self.assertListEqual(
							    __lowercase,					[
							        value + tokenizer.fairseq_offset
							        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
							    ],					)

							lowercase__					  =				tokenizer.convert_ids_to_tokens(__lowercase						)
							self.assertListEqual(
							    __lowercase,					[SPIECE_UNDERLINE + "I", SPIECE_UNDERLINE + "was", SPIECE_UNDERLINE + "b", "or", "n", SPIECE_UNDERLINE + "in", SPIECE_UNDERLINE + "", "<unk>", "2", "0", "0", "0", ",", SPIECE_UNDERLINE + "and", SPIECE_UNDERLINE + "this", SPIECE_UNDERLINE + "is", SPIECE_UNDERLINE + "f", "al", "s", "<unk>", "."],					)




				@slow
				def 							A__      (						self					:						Dict						):
							# fmt: off
							lowercase__					  =				{"input_ids": [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=__lowercase,					model_name="facebook/mbart-large-50",					revision="d3913889c59cd5c9e456b269c376325eabad57e2",					)




				def 							A__      (						self					:						Tuple						):
							if not self.test_slow_tokenizer:
										# as we don't have a slow version, we can't compare the outputs between slow and fast versions
										return

							lowercase__					  =				(self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart50", {})
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
													lowercase__					  =				self.rust_tokenizer_class.from_pretrained(__lowercase,					**__lowercase						)
													lowercase__					  =				self.tokenizer_class.from_pretrained(__lowercase,					**__lowercase						)

													lowercase__					  =				tempfile.mkdtemp()

													lowercase__					  =				tokenizer_r.save_pretrained(__lowercase						)
													lowercase__					  =				tokenizer_p.save_pretrained(__lowercase						)

													# Checks it save with the same files + the tokenizer.json file for the fast one
													self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files						)						)
													lowercase__					  =				tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f						)
													self.assertSequenceEqual(__lowercase,					__lowercase						)

													# Checks everything loads correctly in the same way
													lowercase__					  =				tokenizer_r.from_pretrained(__lowercase						)
													lowercase__					  =				tokenizer_p.from_pretrained(__lowercase						)

													# Check special tokens are set accordingly on Rust and Python
													for key in tokenizer_pp.special_tokens_map:
																self.assertTrue(hasattr(__lowercase,					__lowercase						)						)
																# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

													shutil.rmtree(__lowercase						)

													# Save tokenizer rust, legacy_format=True
													lowercase__					  =				tempfile.mkdtemp()

													lowercase__					  =				tokenizer_r.save_pretrained(__lowercase,					legacy_format=__lowercase						)
													lowercase__					  =				tokenizer_p.save_pretrained(__lowercase						)

													# Checks it save with the same files
													self.assertSequenceEqual(__lowercase,					__lowercase						)

													# Checks everything loads correctly in the same way
													lowercase__					  =				tokenizer_r.from_pretrained(__lowercase						)
													lowercase__					  =				tokenizer_p.from_pretrained(__lowercase						)

													# Check special tokens are set accordingly on Rust and Python
													for key in tokenizer_pp.special_tokens_map:
																self.assertTrue(hasattr(__lowercase,					__lowercase						)						)

													shutil.rmtree(__lowercase						)

													# Save tokenizer rust, legacy_format=False
													lowercase__					  =				tempfile.mkdtemp()

													lowercase__					  =				tokenizer_r.save_pretrained(__lowercase,					legacy_format=__lowercase						)
													lowercase__					  =				tokenizer_p.save_pretrained(__lowercase						)

													# Checks it saved the tokenizer.json file
													self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files						)						)

													# Checks everything loads correctly in the same way
													lowercase__					  =				tokenizer_r.from_pretrained(__lowercase						)
													lowercase__					  =				tokenizer_p.from_pretrained(__lowercase						)

													# Check special tokens are set accordingly on Rust and Python
													for key in tokenizer_pp.special_tokens_map:
																self.assertTrue(hasattr(__lowercase,					__lowercase						)						)

													shutil.rmtree(__lowercase						)
@require_torch
@require_sentencepiece
@require_tokenizers
class 				_snake_case			(					unittest.TestCase):
				UpperCamelCase__				:					Optional[Any]     		="""facebook/mbart-large-50-one-to-many-mmt"""
				UpperCamelCase__				:					Optional[int]     		=[
				    """ UN Chief Says There Is No Military Solution in Syria""",
				    """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
				]
				UpperCamelCase__				:					Optional[int]     		=[
				    """Şeful ONU declară că nu există o soluţie militară în Siria""",
				    """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
				    """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
				    """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
				]
				UpperCamelCase__				:					Union[str, Any]     		=[EN_CODE, 8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2]




				@classmethod
				def 							A__      (						cls					:						Optional[Any]						):
							lowercase__					  =				MBartaaTokenizer.from_pretrained(
							    cls.checkpoint_name,					src_lang="en_XX",					tgt_lang="ro_RO"						)
							lowercase__					  =				1
							return cls




				def 							A__      (						self					:						int						):
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ar_AR"],					25_0001						)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["en_EN"],					25_0004						)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["ro_RO"],					25_0020						)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["mr_IN"],					25_0038						)




				def 							A__      (						self					:						Optional[Any]						):
							lowercase__					  =				self.tokenizer.batch_encode_plus(self.src_text						).input_ids[0]
							self.assertListEqual(self.expected_src_tokens,					__lowercase						)




				def 							A__      (						self					:						Any						):
							self.assertIn(__lowercase,					self.tokenizer.all_special_ids						)
							lowercase__					  =				[RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
							lowercase__					  =				self.tokenizer.decode(__lowercase,					skip_special_tokens=__lowercase						)
							lowercase__					  =				self.tokenizer.decode(generated_ids[1:],					skip_special_tokens=__lowercase						)
							self.assertEqual(__lowercase,					__lowercase						)
							self.assertNotIn(self.tokenizer.eos_token,					__lowercase						)




				def 							A__      (						self					:						Optional[int]						):
							lowercase__					  =				["this is gunna be a long sentence " * 20]
							assert isinstance(src_text[0],					__lowercase						)
							lowercase__					  =				10
							lowercase__					  =				self.tokenizer(__lowercase,					max_length=__lowercase,					truncation=__lowercase						).input_ids[0]
							self.assertEqual(ids[0],					__lowercase						)
							self.assertEqual(ids[-1],					2						)
							self.assertEqual(len(__lowercase						),					__lowercase						)




				def 							A__      (						self					:						Optional[int]						):
							self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "ar_AR"]						),					[25_0053, 25_0001]						)




				def 							A__      (						self					:						Optional[int]						):
							lowercase__					  =				tempfile.mkdtemp()
							lowercase__					  =				self.tokenizer.fairseq_tokens_to_ids
							self.tokenizer.save_pretrained(__lowercase						)
							lowercase__					  =				MBartaaTokenizer.from_pretrained(__lowercase						)
							self.assertDictEqual(new_tok.fairseq_tokens_to_ids,					__lowercase						)




				@require_torch
				def 							A__      (						self					:						List[str]						):
							lowercase__					  =				self.tokenizer(self.src_text,					text_target=self.tgt_text,					padding=__lowercase,					return_tensors="pt"						)
							lowercase__					  =				shift_tokens_right(batch["labels"],					self.tokenizer.pad_token_id						)

							# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
							assert batch.input_ids[1][0] == EN_CODE
							assert batch.input_ids[1][-1] == 2
							assert batch.labels[1][0] == RO_CODE
							assert batch.labels[1][-1] == 2
							assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]




				@require_torch
				def 							A__      (						self					:						str						):
							lowercase__					  =				self.tokenizer(
							    self.src_text,					text_target=self.tgt_text,					padding=__lowercase,					truncation=__lowercase,					max_length=len(self.expected_src_tokens						),					return_tensors="pt",					)
							lowercase__					  =				shift_tokens_right(batch["labels"],					self.tokenizer.pad_token_id						)

							self.assertIsInstance(__lowercase,					__lowercase						)

							self.assertEqual((2, 14),					batch.input_ids.shape						)
							self.assertEqual((2, 14),					batch.attention_mask.shape						)
							lowercase__					  =				batch.input_ids.tolist()[0]
							self.assertListEqual(self.expected_src_tokens,					__lowercase						)
							self.assertEqual(2,					batch.decoder_input_ids[0, 0]						)  # decoder_start_token_id
							# Test that special tokens are reset
							self.assertEqual(self.tokenizer.prefix_tokens,					[EN_CODE]						)
							self.assertEqual(self.tokenizer.suffix_tokens,					[self.tokenizer.eos_token_id]						)




				def 							A__      (						self					:						Optional[int]						):
							lowercase__					  =				self.tokenizer(self.src_text,					padding=__lowercase,					truncation=__lowercase,					max_length=3,					return_tensors="pt"						)
							lowercase__					  =				self.tokenizer(
							    text_target=self.tgt_text,					padding=__lowercase,					truncation=__lowercase,					max_length=10,					return_tensors="pt"						)
							lowercase__					  =				targets["input_ids"]
							lowercase__					  =				shift_tokens_right(__lowercase,					self.tokenizer.pad_token_id						)

							self.assertEqual(batch.input_ids.shape[1],					3						)
							self.assertEqual(batch.decoder_input_ids.shape[1],					10						)




				@require_torch
				def 							A__      (						self					:						Any						):
							lowercase__					  =				self.tokenizer._build_translation_inputs(
							    "A test",					return_tensors="pt",					src_lang="en_XX",					tgt_lang="ar_AR"						)

							self.assertEqual(
							    nested_simplify(__lowercase						),					{
							        # en_XX, A, test, EOS
							        "input_ids": [[25_0004, 62, 3034, 2]],
							        "attention_mask": [[1, 1, 1, 1]],
							        # ar_AR
							        "forced_bos_token_id": 25_0001,
							    },					)









import argparse
import os

import numpy as np
import tensorflow as tf
import torch

from transformers import BertModel



def __lowerCAmelCase (     SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  ):
			lowercase__					  =				("dense.weight", "attention.self.query", "attention.self.key", "attention.self.value")

			lowercase__					  =				(
			    ("layer.", "layer_"),
			    ("word_embeddings.weight", "word_embeddings"),
			    ("position_embeddings.weight", "position_embeddings"),
			    ("token_type_embeddings.weight", "token_type_embeddings"),
			    (".", "/"),
			    ("LayerNorm/weight", "LayerNorm/gamma"),
			    ("LayerNorm/bias", "LayerNorm/beta"),
			    ("weight", "kernel"),
			)

			if not os.path.isdir(SCREAMING_SNAKE_CASE_  ):
						os.makedirs(SCREAMING_SNAKE_CASE_  )

			lowercase__					  =				model.state_dict()

			def to_tf_var_name(SCREAMING_SNAKE_CASE_  ):
						for patt, repl in iter(SCREAMING_SNAKE_CASE_  ):
									lowercase__					  =				name.replace(SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  )
						return f'''bert/{name}'''

			def create_tf_var(SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  ):
						lowercase__					  =				tf.dtypes.as_dtype(tensor.dtype  )
						lowercase__					  =				tf.get_variable(dtype=SCREAMING_SNAKE_CASE_						,  shape=tensor.shape						,  name=SCREAMING_SNAKE_CASE_						,  initializer=tf.zeros_initializer()  )
						session.run(tf.variables_initializer([tf_var]  )  )
						session.run(SCREAMING_SNAKE_CASE_  )
						return tf_var

			tf.reset_default_graph()
			with tf.Session() as session:
						for var_name in state_dict:
									lowercase__					  =				to_tf_var_name(SCREAMING_SNAKE_CASE_  )
									lowercase__					  =				state_dict[var_name].numpy()
									if any(x in var_name for x in tensors_to_transpose  ):
												lowercase__					  =				torch_tensor.T
									lowercase__					  =				create_tf_var(tensor=SCREAMING_SNAKE_CASE_						,  name=SCREAMING_SNAKE_CASE_						,  session=SCREAMING_SNAKE_CASE_  )
									tf.keras.backend.set_value(SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  )
									lowercase__					  =				session.run(SCREAMING_SNAKE_CASE_  )
									print(f'''Successfully created {tf_name}: {np.allclose(SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  )}'''  )

						lowercase__					  =				tf.train.Saver(tf.trainable_variables()  )
						saver.save(SCREAMING_SNAKE_CASE_						,  os.path.join(SCREAMING_SNAKE_CASE_						,  model_name.replace("-"						,  "_"  ) + ".ckpt"  )  )



def __lowerCAmelCase (     SCREAMING_SNAKE_CASE_=None  ):
			lowercase__					  =				argparse.ArgumentParser()
			parser.add_argument("--model_name"						,  type=SCREAMING_SNAKE_CASE_						,  required=SCREAMING_SNAKE_CASE_						,  help="model name e.g. bert-base-uncased"  )
			parser.add_argument(
			    "--cache_dir"						,  type=SCREAMING_SNAKE_CASE_						,  default=SCREAMING_SNAKE_CASE_						,  required=SCREAMING_SNAKE_CASE_						,  help="Directory containing pytorch model"  )
			parser.add_argument("--pytorch_model_path"						,  type=SCREAMING_SNAKE_CASE_						,  required=SCREAMING_SNAKE_CASE_						,  help="/path/to/<pytorch-model-name>.bin"  )
			parser.add_argument("--tf_cache_dir"						,  type=SCREAMING_SNAKE_CASE_						,  required=SCREAMING_SNAKE_CASE_						,  help="Directory in which to save tensorflow model"  )
			lowercase__					  =				parser.parse_args(SCREAMING_SNAKE_CASE_  )

			lowercase__					  =				BertModel.from_pretrained(
			    pretrained_model_name_or_path=args.model_name						,  state_dict=torch.load(args.pytorch_model_path  )						,  cache_dir=args.cache_dir						,  )

			convert_pytorch_checkpoint_to_tf(model=SCREAMING_SNAKE_CASE_						,  ckpt_dir=args.tf_cache_dir						,  model_name=args.model_name  )


if __name__ == "__main__":
							main()




