






'''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


__lowerCamelCase   :					List[Any]   							=						'''http://www.mocksite.com/file1.txt'''
__lowerCamelCase   :					Dict   							=						'''"text": ["foo", "foo"]'''
__lowerCamelCase   :					str   							=						'''6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8'''







class    A_	:
							"""simple docstring"""




							a__   		=	200
							a__   		=	{'''Content-Length''': '''100'''}
							a__   		=	{}

							def 							_A	(		self			:Dict       ,							**lowerCAmelCase__			:Optional[int]				)				->  List[Any]:


										'''simple docstring'''




										return [bytes(lowerCAmelCase__       ,							"utf-8"				)]

def 	__UpperCAmelCase       ( *__magic_name__     ,**__magic_name__						)->    str:



			"""simple docstring"""



			return MockResponse()

@pytest.mark.parametrize("urls_type"     ,[str, list, dict]						)
def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__     ,__magic_name__						)->    Dict:



			"""simple docstring"""



			import requests

			monkeypatch.setattr(__magic_name__     ,"request"     ,__magic_name__						)

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

@pytest.mark.parametrize("paths_type"     ,[str, list, dict]						)
def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__     ,__magic_name__						)->    Dict:



			"""simple docstring"""



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

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__						)->    List[str]:



			"""simple docstring"""



			assert path.endswith(".jsonl"						)
			for num_items, line in enumerate(__magic_name__     ,start=1						):
						snake_case_				:					Union[str, Any]   =       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 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__						)->    Optional[Any]:



			"""simple docstring"""



			snake_case_				:					List[str]   =       request.getfixturevalue(__magic_name__						)
			snake_case_				:					Dict   =       DownloadManager()
			for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(__magic_name__						)     ,start=1						):
						_test_jsonl(__magic_name__     ,__magic_name__						)
			assert num_jsonl == 2

@pytest.mark.parametrize("archive_nested_jsonl"     ,["tar_nested_jsonl_path", "zip_nested_jsonl_path"]						)
def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__						)->    Any:



			"""simple docstring"""



			snake_case_				:					Optional[Any]   =       request.getfixturevalue(__magic_name__						)
			snake_case_				:					List[str]   =       DownloadManager()
			for num_tar, (path, file) in enumerate(dl_manager.iter_archive(__magic_name__						)     ,start=1						):
						for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(__magic_name__						)     ,start=1						):
									_test_jsonl(__magic_name__     ,__magic_name__						)
			assert num_tar == 1
			assert num_jsonl == 2






def 	__UpperCAmelCase       ( __magic_name__						)->    List[str]:



			"""simple docstring"""



			snake_case_				:					Union[str, Any]   =       DownloadManager()
			for num_file, file in enumerate(dl_manager.iter_files(__magic_name__						)     ,start=1						):
						assert os.path.basename(__magic_name__						) == ("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
__lowerCamelCase   :					str   							=					'''.'''

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

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__     ,__magic_name__						)->    List[str]:



			"""simple docstring"""



			snake_case_				:					Tuple   =       SavedModel()
			snake_case_				:					Dict   =       []

			with open(os.path.join(__magic_name__     ,"utils"     ,"tf_ops"     ,"onnx.json"						)						) as f:
						snake_case_				:					Dict   =       json.load(__magic_name__						)["opsets"]

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

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

			snake_case_				:					Tuple   =       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
			snake_case_				:					str   =       sorted(__magic_name__						)
			snake_case_				:					Optional[int]   =       []

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

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


if __name__ == "__main__":
		__lowerCamelCase   :					Any   							=					argparse.ArgumentParser()
		parser.add_argument('''--saved_model_path''', help='''Path of the saved model to check (the .pb file).''')
		parser.add_argument(
		    '''--opset''', default=12, 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)'''
		)
		__lowerCamelCase   :					Dict   							=					parser.parse_args()

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




