
"""simple docstring"""




import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 	lowerCAmelCase_						(a__ ,					unittest.TestCase  ):


				"""simple docstring"""



				__UpperCamelCase      :						List[str]					       =   CodeGenTokenizer
				__UpperCamelCase      :						int					       =   CodeGenTokenizerFast
				__UpperCamelCase      :						List[str]					       =   True
				__UpperCamelCase      :						Optional[Any]					       =   {'''add_prefix_space''': True}
				__UpperCamelCase      :						str					       =   False



				def 	__magic_name__    (self    )					->		Union[str, Any]:



											"""simple docstring"""




											super().setUp()

											# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
											SCREAMING_SNAKE_CASE__						:       List[Any]           =   [
											    """l""",
											    """o""",
											    """w""",
											    """e""",
											    """r""",
											    """s""",
											    """t""",
											    """i""",
											    """d""",
											    """n""",
											    """\u0120""",
											    """\u0120l""",
											    """\u0120n""",
											    """\u0120lo""",
											    """\u0120low""",
											    """er""",
											    """\u0120lowest""",
											    """\u0120newer""",
											    """\u0120wider""",
											    """<unk>""",
											    """<|endoftext|>""",
											]
											SCREAMING_SNAKE_CASE__						:       Any           =   dict(zip(SCREAMING_SNAKE_CASE__   ,       range(len(SCREAMING_SNAKE_CASE__    )    )    )    )
											SCREAMING_SNAKE_CASE__						:       Dict           =   ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
											SCREAMING_SNAKE_CASE__						:       List[str]           =   {"""unk_token""": """<unk>"""}

											SCREAMING_SNAKE_CASE__						:       List[Any]           =   os.path.join(self.tmpdirname   ,       VOCAB_FILES_NAMES["""vocab_file"""]    )
											SCREAMING_SNAKE_CASE__						:       Any           =   os.path.join(self.tmpdirname   ,       VOCAB_FILES_NAMES["""merges_file"""]    )
											with open(self.vocab_file   ,       """w"""   ,       encoding="""utf-8"""    ) as fp:
																		fp.write(json.dumps(SCREAMING_SNAKE_CASE__    ) + """\n"""    )
											with open(self.merges_file   ,       """w"""   ,       encoding="""utf-8"""    ) as fp:
																		fp.write("""\n""".join(SCREAMING_SNAKE_CASE__    )    )



				def 	__magic_name__    (self   ,       **SCREAMING_SNAKE_CASE__    )					->		Dict:



											"""simple docstring"""




											kwargs.update(self.special_tokens_map    )
											return CodeGenTokenizer.from_pretrained(self.tmpdirname   ,       **SCREAMING_SNAKE_CASE__    )



				def 	__magic_name__    (self   ,       **SCREAMING_SNAKE_CASE__    )					->		Union[str, Any]:



											"""simple docstring"""




											kwargs.update(self.special_tokens_map    )
											return CodeGenTokenizerFast.from_pretrained(self.tmpdirname   ,       **SCREAMING_SNAKE_CASE__    )



				def 	__magic_name__    (self   ,       SCREAMING_SNAKE_CASE__    )					->		Tuple:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Tuple           =   """lower newer"""
											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   """lower newer"""
											return input_text, output_text



				def 	__magic_name__    (self    )					->		Dict:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       str           =   CodeGenTokenizer(self.vocab_file   ,       self.merges_file   ,       **self.special_tokens_map    )
											SCREAMING_SNAKE_CASE__						:       int           =   """lower newer"""
											SCREAMING_SNAKE_CASE__						:       Dict           =   ["""\u0120low""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
											SCREAMING_SNAKE_CASE__						:       int           =   tokenizer.tokenize(SCREAMING_SNAKE_CASE__   ,       add_prefix_space=SCREAMING_SNAKE_CASE__    )
											self.assertListEqual(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )

											SCREAMING_SNAKE_CASE__						:       List[Any]           =   tokens + [tokenizer.unk_token]
											SCREAMING_SNAKE_CASE__						:       Tuple           =   [14, 15, 10, 9, 3, 2, 15, 19]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__    )   ,       SCREAMING_SNAKE_CASE__    )



				def 	__magic_name__    (self    )					->		Union[str, Any]:



											"""simple docstring"""




											if not self.test_rust_tokenizer:
																		return

											SCREAMING_SNAKE_CASE__						:       Any           =   self.get_tokenizer()
											SCREAMING_SNAKE_CASE__						:       str           =   self.get_rust_tokenizer(add_prefix_space=SCREAMING_SNAKE_CASE__    )

											SCREAMING_SNAKE_CASE__						:       Tuple           =   """lower newer"""

											# Testing tokenization
											SCREAMING_SNAKE_CASE__						:       List[str]           =   tokenizer.tokenize(SCREAMING_SNAKE_CASE__   ,       add_prefix_space=SCREAMING_SNAKE_CASE__    )
											SCREAMING_SNAKE_CASE__						:       List[str]           =   rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE__    )
											self.assertListEqual(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )

											# Testing conversion to ids without special tokens
											SCREAMING_SNAKE_CASE__						:       int           =   tokenizer.encode(SCREAMING_SNAKE_CASE__   ,       add_special_tokens=SCREAMING_SNAKE_CASE__   ,       add_prefix_space=SCREAMING_SNAKE_CASE__    )
											SCREAMING_SNAKE_CASE__						:       Dict           =   rust_tokenizer.encode(SCREAMING_SNAKE_CASE__   ,       add_special_tokens=SCREAMING_SNAKE_CASE__    )
											self.assertListEqual(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )

											# Testing conversion to ids with special tokens
											SCREAMING_SNAKE_CASE__						:       Optional[int]           =   self.get_rust_tokenizer(add_prefix_space=SCREAMING_SNAKE_CASE__    )
											SCREAMING_SNAKE_CASE__						:       Dict           =   tokenizer.encode(SCREAMING_SNAKE_CASE__   ,       add_prefix_space=SCREAMING_SNAKE_CASE__    )
											SCREAMING_SNAKE_CASE__						:       List[Any]           =   rust_tokenizer.encode(SCREAMING_SNAKE_CASE__    )
											self.assertListEqual(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )

											# Testing the unknown token
											SCREAMING_SNAKE_CASE__						:       str           =   tokens + [rust_tokenizer.unk_token]
											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   [14, 15, 10, 9, 3, 2, 15, 19]
											self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__    )   ,       SCREAMING_SNAKE_CASE__    )



				def 	__magic_name__    (self   ,       *SCREAMING_SNAKE_CASE__   ,       **SCREAMING_SNAKE_CASE__    )					->		Dict:



											"""simple docstring"""




											pass



				def 	__magic_name__    (self   ,       SCREAMING_SNAKE_CASE__=15    )					->		List[str]:



											"""simple docstring"""




											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''    ):
																									SCREAMING_SNAKE_CASE__						:       Tuple           =   self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__   ,       **SCREAMING_SNAKE_CASE__    )

																									# Simple input
																									SCREAMING_SNAKE_CASE__						:       Any           =   """This is a simple input"""
																									SCREAMING_SNAKE_CASE__						:       Tuple           =   ["""This is a simple input 1""", """This is a simple input 2"""]
																									SCREAMING_SNAKE_CASE__						:       Dict           =   ("""This is a simple input""", """This is a pair""")
																									SCREAMING_SNAKE_CASE__						:       Optional[int]           =   [
																									    ("""This is a simple input 1""", """This is a simple input 2"""),
																									    ("""This is a simple pair 1""", """This is a simple pair 2"""),
																									]

																									# Simple input tests
																									self.assertRaises(SCREAMING_SNAKE_CASE__   ,       tokenizer_r.encode   ,       SCREAMING_SNAKE_CASE__   ,       max_length=SCREAMING_SNAKE_CASE__   ,       padding="""max_length"""    )

																									# Simple input
																									self.assertRaises(SCREAMING_SNAKE_CASE__   ,       tokenizer_r.encode_plus   ,       SCREAMING_SNAKE_CASE__   ,       max_length=SCREAMING_SNAKE_CASE__   ,       padding="""max_length"""    )

																									# Simple input
																									self.assertRaises(
																									    SCREAMING_SNAKE_CASE__   ,       tokenizer_r.batch_encode_plus   ,       SCREAMING_SNAKE_CASE__   ,       max_length=SCREAMING_SNAKE_CASE__   ,       padding="""max_length"""   ,       )

																									# Pair input
																									self.assertRaises(SCREAMING_SNAKE_CASE__   ,       tokenizer_r.encode   ,       SCREAMING_SNAKE_CASE__   ,       max_length=SCREAMING_SNAKE_CASE__   ,       padding="""max_length"""    )

																									# Pair input
																									self.assertRaises(SCREAMING_SNAKE_CASE__   ,       tokenizer_r.encode_plus   ,       SCREAMING_SNAKE_CASE__   ,       max_length=SCREAMING_SNAKE_CASE__   ,       padding="""max_length"""    )

																									# Pair input
																									self.assertRaises(
																									    SCREAMING_SNAKE_CASE__   ,       tokenizer_r.batch_encode_plus   ,       SCREAMING_SNAKE_CASE__   ,       max_length=SCREAMING_SNAKE_CASE__   ,       padding="""max_length"""   ,       )



				def 	__magic_name__    (self    )					->		Dict:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   CodeGenTokenizer.from_pretrained(self.tmpdirname   ,       pad_token="""<pad>"""    )

											# Simple input
											SCREAMING_SNAKE_CASE__						:       str           =   """This is a simple input"""
											SCREAMING_SNAKE_CASE__						:       int           =   ["""This is a simple input looooooooong""", """This is a simple input"""]
											SCREAMING_SNAKE_CASE__						:       str           =   ("""This is a simple input""", """This is a pair""")
											SCREAMING_SNAKE_CASE__						:       List[Any]           =   [
											    ("""This is a simple input loooooong""", """This is a simple input"""),
											    ("""This is a simple pair loooooong""", """This is a simple pair"""),
											]

											SCREAMING_SNAKE_CASE__						:       Dict           =   tokenizer.pad_token_id

											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   tokenizer(SCREAMING_SNAKE_CASE__   ,       padding="""max_length"""   ,       max_length=30   ,       return_tensors="""np"""    )
											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   tokenizer(SCREAMING_SNAKE_CASE__   ,       padding=SCREAMING_SNAKE_CASE__   ,       truncate=SCREAMING_SNAKE_CASE__   ,       return_tensors="""np"""    )
											SCREAMING_SNAKE_CASE__						:       Dict           =   tokenizer(*SCREAMING_SNAKE_CASE__   ,       padding="""max_length"""   ,       max_length=60   ,       return_tensors="""np"""    )
											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   tokenizer(SCREAMING_SNAKE_CASE__   ,       padding=SCREAMING_SNAKE_CASE__   ,       truncate=SCREAMING_SNAKE_CASE__   ,       return_tensors="""np"""    )

											# s
											# test single string max_length padding
											self.assertEqual(out_s["""input_ids"""].shape[-1]   ,       30    )
											self.assertTrue(pad_token_id in out_s["""input_ids"""]    )
											self.assertTrue(0 in out_s["""attention_mask"""]    )

											# s2
											# test automatic padding
											self.assertEqual(out_sa["""input_ids"""].shape[-1]   ,       33    )
											# long slice doesn't have padding
											self.assertFalse(pad_token_id in out_sa["""input_ids"""][0]    )
											self.assertFalse(0 in out_sa["""attention_mask"""][0]    )
											# short slice does have padding
											self.assertTrue(pad_token_id in out_sa["""input_ids"""][1]    )
											self.assertTrue(0 in out_sa["""attention_mask"""][1]    )

											# p
											# test single pair max_length padding
											self.assertEqual(out_p["""input_ids"""].shape[-1]   ,       60    )
											self.assertTrue(pad_token_id in out_p["""input_ids"""]    )
											self.assertTrue(0 in out_p["""attention_mask"""]    )

											# p2
											# test automatic padding pair
											self.assertEqual(out_pa["""input_ids"""].shape[-1]   ,       52    )
											# long slice pair doesn't have padding
											self.assertFalse(pad_token_id in out_pa["""input_ids"""][0]    )
											self.assertFalse(0 in out_pa["""attention_mask"""][0]    )
											# short slice pair does have padding
											self.assertTrue(pad_token_id in out_pa["""input_ids"""][1]    )
											self.assertTrue(0 in out_pa["""attention_mask"""][1]    )



				def 	__magic_name__    (self    )					->		Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       str           =   """$$$"""
											SCREAMING_SNAKE_CASE__						:       Optional[int]           =   CodeGenTokenizer.from_pretrained(self.tmpdirname   ,       bos_token=SCREAMING_SNAKE_CASE__   ,       add_bos_token=SCREAMING_SNAKE_CASE__    )

											SCREAMING_SNAKE_CASE__						:       Optional[int]           =   """This is a simple input"""
											SCREAMING_SNAKE_CASE__						:       List[str]           =   ["""This is a simple input 1""", """This is a simple input 2"""]

											SCREAMING_SNAKE_CASE__						:       Dict           =   tokenizer.bos_token_id

											SCREAMING_SNAKE_CASE__						:       Any           =   tokenizer(SCREAMING_SNAKE_CASE__    )
											SCREAMING_SNAKE_CASE__						:       Any           =   tokenizer(SCREAMING_SNAKE_CASE__    )

											self.assertEqual(out_s.input_ids[0]   ,       SCREAMING_SNAKE_CASE__    )
											self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids    )    )

											SCREAMING_SNAKE_CASE__						:       Optional[int]           =   tokenizer.decode(out_s.input_ids    )
											SCREAMING_SNAKE_CASE__						:       int           =   tokenizer.batch_decode(out_sa.input_ids    )

											self.assertEqual(decode_s.split()[0]   ,       SCREAMING_SNAKE_CASE__    )
											self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa    )    )



				@slow
				def 	__magic_name__    (self    )					->		Tuple:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   CodeGenTokenizer.from_pretrained("""Salesforce/codegen-350M-mono"""    )

											SCREAMING_SNAKE_CASE__						:       str           =   """\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#"""
											SCREAMING_SNAKE_CASE__						:       int           =   """\nif len_a > len_b:      result = a\nelse:      result = b"""

											SCREAMING_SNAKE_CASE__						:       List[Any]           =   tokenizer.encode(SCREAMING_SNAKE_CASE__    )
											SCREAMING_SNAKE_CASE__						:       List[str]           =   ["""^#""", re.escape("""<|endoftext|>"""    ), """^'''""", """^\"\"\"""", """\n\n\n"""]
											SCREAMING_SNAKE_CASE__						:       Any           =   tokenizer.decode(SCREAMING_SNAKE_CASE__   ,       truncate_before_pattern=SCREAMING_SNAKE_CASE__    )
											self.assertEqual(SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )



				def 	__magic_name__    (self    )					->		Dict:



											"""simple docstring"""




											pass






"""simple docstring"""




import argparse
import json
import os

from tensorflow.core.protobuf.saved_model_pba import SavedModel


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCAmelCase__      :    List[str]    							= '.'

# Internal TensorFlow ops that can be safely ignored (mostly specific to a saved model)
UpperCAmelCase__      :    List[Any]    							= [
    'Assert',
    'AssignVariableOp',
    'EmptyTensorList',
    'MergeV2Checkpoints',
    'ReadVariableOp',
    'ResourceGather',
    'RestoreV2',
    'SaveV2',
    'ShardedFilename',
    'StatefulPartitionedCall',
    'StaticRegexFullMatch',
    'VarHandleOp',
]

def lowercase_  (   _snake_case   ,_snake_case   ,_snake_case						):
							SCREAMING_SNAKE_CASE__						:       List[str]           =   SavedModel()
							SCREAMING_SNAKE_CASE__						:       Dict           =   []

							with open(os.path.join(_snake_case   ,"""utils"""   ,"""tf_ops"""   ,"""onnx.json"""						)						) as f:
														SCREAMING_SNAKE_CASE__						:       Any           =   json.load(_snake_case						)["""opsets"""]

							for i in range(1   ,opset + 1						):
														onnx_ops.extend(onnx_opsets[str(_snake_case						)]						)

							with open(_snake_case   ,"""rb"""						) as f:
														saved_model.ParseFromString(f.read()						)

							SCREAMING_SNAKE_CASE__						:       List[str]           =   set()

							# Iterate over every metagraph in case there is more than one (a saved model can contain multiple graphs)
							for meta_graph in saved_model.meta_graphs:
														# Add operations in the graph definition
														model_op_names.update(node.op for node in meta_graph.graph_def.node						)

														# Go through the functions in the graph definition
														for func in meta_graph.graph_def.library.function:
																					# Add operations in each function
																					model_op_names.update(node.op for node in func.node_def						)

    # Convert to list, sorted if you want
							SCREAMING_SNAKE_CASE__						:       int           =   sorted(_snake_case						)
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   []

							for op in model_op_names:
														if op not in onnx_ops and op not in INTERNAL_OPS:
																					incompatible_ops.append(_snake_case						)

							if strict and len(_snake_case						) > 0:
														raise Exception(f'''Found the following incompatible ops for the opset {opset}:\n''' + incompatible_ops						)
							elif len(_snake_case						) > 0:
														print(f'''Found the following incompatible ops for the opset {opset}:'''						)
														print(*_snake_case   ,sep="""\n"""						)
							else:
														print(f'''The saved model {saved_model_path} can properly be converted with ONNX.'''						)


if __name__ == "__main__":
					UpperCAmelCase__      :    Optional[int]    							= argparse.ArgumentParser()
					parser.add_argument('--saved_model_path', help='Path of the saved model to check (the .pb file).')
					parser.add_argument(
					    '--opset', default=1_2, type=int, help='The ONNX opset against which the model has to be tested.'
					)
					parser.add_argument(
					    '--framework', choices=['onnx'], default='onnx', help='Frameworks against which to test the saved model.'
					)
					parser.add_argument(
					    '--strict', action='store_true', help='Whether make the checking strict (raise errors) or not (raise warnings)'
					)
					UpperCAmelCase__      :    Dict    							= parser.parse_args()

					if args.framework == "onnx":
										onnx_compliancy(args.saved_model_path, args.strict, args.opset)




