





import unittest
from pathlib import Path
from tempfile import TemporaryDirectory

from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, require_tf, slow


if is_tf_available():
					import tensorflow as tf

if is_tensorflow_text_available():
					from transformers.models.bert import TFBertTokenizer


UpperCamelCase__           =			["bert-base-uncased", "bert-base-cased"]
UpperCamelCase__           =			"hf-internal-testing/tiny-bert-tf-only"

if is_tf_available():

					class 							__SCREAMING_SNAKE_CASE       (  tf.keras.Model							):






												def __init__(    self	,			__lowerCAmelCase	):
																			super().__init__()
																			UpperCamelCase__					  =      tokenizer
																			UpperCamelCase__					  =      AutoConfig.from_pretrained(__lowerCAmelCase	)
																			UpperCamelCase__					  =      TFAutoModel.from_config(__lowerCAmelCase	)







												def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
																			UpperCamelCase__					  =      self.tokenizer(__lowerCAmelCase	)
																			UpperCamelCase__					  =      self.bert(**__lowerCAmelCase	)
																			return out["pooler_output"]

@require_tf
@require_tensorflow_text
class 							__SCREAMING_SNAKE_CASE       (  unittest.TestCase							):






							def 					_lowerCamelCase		(    self	):
														super().setUp()

														UpperCamelCase__					  =      [
														    BertTokenizer.from_pretrained(__lowerCAmelCase	) for checkpoint in (TOKENIZER_CHECKPOINTS * 2)
														]  # repeat for when fast_bert_tokenizer=false
														UpperCamelCase__					  =      [TFBertTokenizer.from_pretrained(__lowerCAmelCase	) for checkpoint in TOKENIZER_CHECKPOINTS] + [
														    TFBertTokenizer.from_pretrained(__lowerCAmelCase	,			use_fast_bert_tokenizer=__lowerCAmelCase	)
														    for checkpoint in TOKENIZER_CHECKPOINTS
														]
														assert len(self.tokenizers	) == len(self.tf_tokenizers	)

														UpperCamelCase__					  =      [
														    """This is a straightforward English test sentence.""",
														    """This one has some weird characters\rto\nsee\r\nif  those\u00E9break things.""",
														    """Now we're going to add some Chinese: 一 二 三 一二三""",
														    """And some much more rare Chinese: 齉 堃 齉堃""",
														    """Je vais aussi écrire en français pour tester les accents""",
														    """Classical Irish also has some unusual characters, so in they go: Gaelaċ, ꝼ""",
														]
														UpperCamelCase__					  =      list(zip(self.test_sentences	,			self.test_sentences[::-1]	)	)






							def 					_lowerCamelCase		(    self	):
														for tokenizer, tf_tokenizer in zip(self.tokenizers	,			self.tf_tokenizers	):
																					for test_inputs in (self.test_sentences, self.paired_sentences):
																												UpperCamelCase__					  =      tokenizer(__lowerCAmelCase	,			return_tensors="""tf"""	,			padding="""longest"""	)
																												UpperCamelCase__					  =      tf_tokenizer(__lowerCAmelCase	)

																												for key in python_outputs.keys():
																																			self.assertTrue(tf.reduce_all(python_outputs[key].shape == tf_outputs[key].shape	)	)
																																			self.assertTrue(tf.reduce_all(tf.cast(python_outputs[key]	,			tf.intaa	) == tf_outputs[key]	)	)






							@slow
							def 					_lowerCamelCase		(    self	):
														for tf_tokenizer in self.tf_tokenizers:
																					UpperCamelCase__					  =      tf_tokenizer(self.paired_sentences	)
																					UpperCamelCase__					  =      tf_tokenizer(
																					    text=[sentence[0] for sentence in self.paired_sentences]	,			text_pair=[sentence[1] for sentence in self.paired_sentences]	,			)
																					for key in merged_outputs.keys():
																												self.assertTrue(tf.reduce_all(tf.cast(merged_outputs[key]	,			tf.intaa	) == separated_outputs[key]	)	)






							@slow
							def 					_lowerCamelCase		(    self	):
														for tf_tokenizer in self.tf_tokenizers:
																					UpperCamelCase__					  =      tf.function(__lowerCAmelCase	)
																					for test_inputs in (self.test_sentences, self.paired_sentences):
																												UpperCamelCase__					  =      tf.constant(__lowerCAmelCase	)
																												UpperCamelCase__					  =      compiled_tokenizer(__lowerCAmelCase	)
																												UpperCamelCase__					  =      tf_tokenizer(__lowerCAmelCase	)

																												for key in eager_outputs.keys():
																																			self.assertTrue(tf.reduce_all(eager_outputs[key] == compiled_outputs[key]	)	)







							@slow
							def 					_lowerCamelCase		(    self	):
														for tf_tokenizer in self.tf_tokenizers:
																					UpperCamelCase__					  =      ModelToSave(tokenizer=__lowerCAmelCase	)
																					UpperCamelCase__					  =      tf.convert_to_tensor(self.test_sentences	)
																					UpperCamelCase__					  =      model(__lowerCAmelCase	)  # Build model with some sample inputs
																					with TemporaryDirectory() as tempdir:
																												UpperCamelCase__					  =      Path(__lowerCAmelCase	) / """saved.model"""
																												model.save(__lowerCAmelCase	)
																												UpperCamelCase__					  =      tf.keras.models.load_model(__lowerCAmelCase	)
																					UpperCamelCase__					  =      loaded_model(__lowerCAmelCase	)
																					# We may see small differences because the loaded model is compiled, so we need an epsilon for the test
																					self.assertLessEqual(tf.reduce_max(tf.abs(out - loaded_output	)	)	,			1E-5	)











# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


UpperCamelCase__           =			subprocess.check_output("git merge-base main HEAD".split()).decode("utf-8")
UpperCamelCase__           =			subprocess.check_output(f"""git diff --name-only {fork_point_sha}""".split()).decode("utf-8").split()

UpperCamelCase__           =			"|".join(sys.argv[1:])
UpperCamelCase__           =			re.compile(rf"""^({joined_dirs}).*?\.py$""")

UpperCamelCase__           =			[x for x in modified_files if regex.match(x)]
print(" ".join(relevant_modified_files), end="")




