



'''simple docstring'''






import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


UpperCamelCase__:   Union[str, Any]								=			"http://www.mocksite.com/file1.txt"
UpperCamelCase__:   Tuple								=			"\"text\": [\"foo\", \"foo\"]"
UpperCamelCase__:   Dict								=			"6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"

class 				SCREAMING_SNAKE_CASE:







	"""simple docstring"""






	lowerCamelCase__			 =       200
	lowerCamelCase__			 =       {"""Content-Length""": """100"""}
	lowerCamelCase__			 =       {}







	def      A	(						self			:     Tuple		,			**__snake_case			:     Dict		)			->		List[Any]:
								return [bytes(__snake_case		,			'''utf-8'''		)]


def  snake_case_     (					*_lowerCAmelCase  :						Optional[Any]   ,      **_lowerCAmelCase  :						str  )      ->   List[str]:
							return MockResponse()


@pytest.mark.parametrize('''urls_type'''   ,      [str, list, dict]  )
def  snake_case_     (					_lowerCAmelCase  :						str   ,      _lowerCAmelCase  :						Any   ,      _lowerCAmelCase  :						Dict  )      ->   str:
							import requests

							monkeypatch.setattr(_lowerCAmelCase   ,      '''request'''   ,      _lowerCAmelCase  )

							UpperCAmelCase :       Optional[Any] 							=		URL
							if issubclass(_lowerCAmelCase   ,      _lowerCAmelCase  ):
														UpperCAmelCase :       List[Any] 							=		url
							elif issubclass(_lowerCAmelCase   ,      _lowerCAmelCase  ):
														UpperCAmelCase :       int 							=		[url]
							elif issubclass(_lowerCAmelCase   ,      _lowerCAmelCase  ):
														UpperCAmelCase :       str 							=		{'''train''': url}
							UpperCAmelCase :       Dict 							=		'''dummy'''
							UpperCAmelCase :       Optional[int] 							=		'''downloads'''
							UpperCAmelCase :       List[str] 							=		tmp_path
							UpperCAmelCase :       Optional[Any] 							=		DownloadConfig(
							    cache_dir=os.path.join(_lowerCAmelCase   ,      _lowerCAmelCase  )   ,      use_etag=_lowerCAmelCase   ,      )
							UpperCAmelCase :       Tuple 							=		DownloadManager(dataset_name=_lowerCAmelCase   ,      download_config=_lowerCAmelCase  )
							UpperCAmelCase :       Any 							=		dl_manager.download(_lowerCAmelCase  )
							UpperCAmelCase :       Any 							=		urls
							for downloaded_paths in [downloaded_paths]:
														if isinstance(_lowerCAmelCase   ,      _lowerCAmelCase  ):
																					UpperCAmelCase :       Optional[Any] 							=		[downloaded_paths]
																					UpperCAmelCase :       Any 							=		[urls]
														elif isinstance(_lowerCAmelCase   ,      _lowerCAmelCase  ):
																					assert "train" in downloaded_paths.keys()
																					UpperCAmelCase :       Any 							=		downloaded_paths.values()
																					UpperCAmelCase :       Tuple 							=		urls.values()
														assert downloaded_paths
														for downloaded_path, input_url in zip(_lowerCAmelCase   ,      _lowerCAmelCase  ):
																					assert downloaded_path == dl_manager.downloaded_paths[input_url]
																					UpperCAmelCase :       List[str] 							=		Path(_lowerCAmelCase  )
																					UpperCAmelCase :       List[Any] 							=		downloaded_path.parts
																					assert parts[-1] == HASH
																					assert parts[-2] == cache_subdir
																					assert downloaded_path.exists()
																					UpperCAmelCase :       List[Any] 							=		downloaded_path.read_text()
																					assert content == CONTENT
																					UpperCAmelCase :       Union[str, Any] 							=		downloaded_path.with_suffix('''.json'''  )
																					assert metadata_downloaded_path.exists()
																					UpperCAmelCase :       Any 							=		json.loads(metadata_downloaded_path.read_text()  )
																					assert metadata_content == {"url": URL, "etag": None}


@pytest.mark.parametrize('''paths_type'''   ,      [str, list, dict]  )
def  snake_case_     (					_lowerCAmelCase  :						List[str]   ,      _lowerCAmelCase  :						Union[str, Any]   ,      _lowerCAmelCase  :						List[Any]  )      ->   int:
							UpperCAmelCase :       Optional[int] 							=		str(_lowerCAmelCase  )
							if issubclass(_lowerCAmelCase   ,      _lowerCAmelCase  ):
														UpperCAmelCase :       Union[str, Any] 							=		filename
							elif issubclass(_lowerCAmelCase   ,      _lowerCAmelCase  ):
														UpperCAmelCase :       int 							=		[filename]
							elif issubclass(_lowerCAmelCase   ,      _lowerCAmelCase  ):
														UpperCAmelCase :       Union[str, Any] 							=		{'''train''': filename}
							UpperCAmelCase :       Optional[int] 							=		'''dummy'''
							UpperCAmelCase :       Union[str, Any] 							=		xz_file.parent
							UpperCAmelCase :       Tuple 							=		'''extracted'''
							UpperCAmelCase :       List[Any] 							=		DownloadConfig(
							    cache_dir=_lowerCAmelCase   ,      use_etag=_lowerCAmelCase   ,      )
							UpperCAmelCase :       Optional[Any] 							=		DownloadManager(dataset_name=_lowerCAmelCase   ,      download_config=_lowerCAmelCase  )
							UpperCAmelCase :       List[Any] 							=		dl_manager.extract(_lowerCAmelCase  )
							UpperCAmelCase :       Union[str, Any] 							=		paths
							for extracted_paths in [extracted_paths]:
														if isinstance(_lowerCAmelCase   ,      _lowerCAmelCase  ):
																					UpperCAmelCase :       int 							=		[extracted_paths]
																					UpperCAmelCase :       int 							=		[paths]
														elif isinstance(_lowerCAmelCase   ,      _lowerCAmelCase  ):
																					assert "train" in extracted_paths.keys()
																					UpperCAmelCase :       Any 							=		extracted_paths.values()
																					UpperCAmelCase :       Tuple 							=		paths.values()
														assert extracted_paths
														for extracted_path, input_path in zip(_lowerCAmelCase   ,      _lowerCAmelCase  ):
																					assert extracted_path == dl_manager.extracted_paths[input_path]
																					UpperCAmelCase :       Union[str, Any] 							=		Path(_lowerCAmelCase  )
																					UpperCAmelCase :       List[Any] 							=		extracted_path.parts
																					assert parts[-1] == hash_url_to_filename(_lowerCAmelCase   ,      etag=_lowerCAmelCase  )
																					assert parts[-2] == extracted_subdir
																					assert extracted_path.exists()
																					UpperCAmelCase :       Union[str, Any] 							=		extracted_path.read_text()
																					UpperCAmelCase :       List[str] 							=		text_file.read_text()
																					assert extracted_file_content == expected_file_content


def  snake_case_     (					_lowerCAmelCase  :						Union[str, Any]   ,      _lowerCAmelCase  :						List[Any]  )      ->   str:
							assert path.endswith('''.jsonl'''  )
							for num_items, line in enumerate(_lowerCAmelCase   ,      start=1  ):
														UpperCAmelCase :       str 							=		json.loads(line.decode('''utf-8'''  )  )
														assert item.keys() == {"col_1", "col_2", "col_3"}
							assert num_items == 4


@pytest.mark.parametrize('''archive_jsonl'''   ,      ['''tar_jsonl_path''', '''zip_jsonl_path''']  )
def  snake_case_     (					_lowerCAmelCase  :						Union[str, Any]   ,      _lowerCAmelCase  :						str  )      ->   Optional[int]:
							UpperCAmelCase :       Optional[Any] 							=		request.getfixturevalue(_lowerCAmelCase  )
							UpperCAmelCase :       Any 							=		DownloadManager()
							for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(_lowerCAmelCase  )   ,      start=1  ):
														_test_jsonl(_lowerCAmelCase   ,      _lowerCAmelCase  )
							assert num_jsonl == 2


@pytest.mark.parametrize('''archive_nested_jsonl'''   ,      ['''tar_nested_jsonl_path''', '''zip_nested_jsonl_path''']  )
def  snake_case_     (					_lowerCAmelCase  :						Any   ,      _lowerCAmelCase  :						Union[str, Any]  )      ->   Tuple:
							UpperCAmelCase :       int 							=		request.getfixturevalue(_lowerCAmelCase  )
							UpperCAmelCase :       str 							=		DownloadManager()
							for num_tar, (path, file) in enumerate(dl_manager.iter_archive(_lowerCAmelCase  )   ,      start=1  ):
														for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(_lowerCAmelCase  )   ,      start=1  ):
																					_test_jsonl(_lowerCAmelCase   ,      _lowerCAmelCase  )
							assert num_tar == 1
							assert num_jsonl == 2




def  snake_case_     (					_lowerCAmelCase  :						List[Any]  )      ->   Union[str, Any]:
							UpperCAmelCase :       Optional[Any] 							=		DownloadManager()
							for num_file, file in enumerate(dl_manager.iter_files(_lowerCAmelCase  )   ,      start=1  ):
														assert os.path.basename(_lowerCAmelCase  ) == ("test.txt" if num_file == 1 else "train.txt")
							assert num_file == 2







"""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)




