
"""simple docstring"""

import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


UpperCamelCase			:       Tuple									=				get_logger(__name__)

class __lowerCAmelCase	:
     lowercase		     =		"dummy_data"
     lowercase		     =		"datasets"
     lowercase		     =		False





     def __init__(			self			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase = None			,  __UpperCAmelCase = False			,  __UpperCAmelCase = True			,  __UpperCAmelCase = None			,  ):

      '''simple docstring'''




      __UpperCamelCase       						= 0
      __UpperCamelCase       						= dataset_name
      __UpperCamelCase       						= cache_dir
      __UpperCamelCase       						= use_local_dummy_data
      __UpperCamelCase       						= config
      # download_callbacks take a single url as input
      __UpperCamelCase       						= download_callbacks or []
      # if False, it doesn't load existing files and it returns the paths of the dummy files relative
      # to the dummy_data zip file root
      __UpperCamelCase       						= load_existing_dummy_data

      # TODO(PVP, QL) might need to make this more general
      __UpperCamelCase       						= str(__UpperCAmelCase   )
      # to be downloaded
      __UpperCamelCase       						= None
      __UpperCamelCase       						= None





     @property
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      if self._dummy_file is None:
       __UpperCamelCase       						= self.download_dummy_data()
      return self._dummy_file





     @property
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      if self.config is not None:
       # structure is dummy / config_name / version_name
       return os.path.join('dummy'			,  self.config.name			,  self.version_name   )
      # structure is dummy / version_name
      return os.path.join('dummy'			,  self.version_name   )





     @property
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      return os.path.join(self.dummy_data_folder			,  'dummy_data.zip'   )





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= (
          self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
      )

      __UpperCamelCase       						= cached_path(
          __UpperCAmelCase			,  cache_dir=self.cache_dir			,  extract_compressed_file=__UpperCAmelCase			,  force_extract=__UpperCAmelCase   )

      return os.path.join(__UpperCAmelCase			,  self.dummy_file_name   )





     @property
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      return os.path.join(self.datasets_scripts_dir			,  self.dataset_name			,  self.dummy_zip_file   )





     @property
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      if self._bucket_url is None:
       __UpperCamelCase       						= hf_github_url(self.dataset_name			,  self.dummy_zip_file.replace(os.sep			,  '/'   )   )
      return self._bucket_url





     @property
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      if os.path.isdir(self.dummy_file   ):
       return self.dummy_file
      # else cut off path to file -> example `xsum`.
      return "/".join(self.dummy_file.replace(os.sep			,  '/'   ).split('/'   )[:-1]   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  *__UpperCAmelCase   ):

      '''simple docstring'''




      if self.load_existing_dummy_data:
       # dummy data is downloaded and tested
       __UpperCamelCase       						= self.dummy_file
      else:
       # dummy data cannot be downloaded and only the path to dummy file is returned
       __UpperCamelCase       						= self.dummy_file_name

      # special case when data_url is a dict
      if isinstance(__UpperCAmelCase			,  __UpperCAmelCase   ):
       return self.create_dummy_data_dict(__UpperCAmelCase			,  __UpperCAmelCase   )
      elif isinstance(__UpperCAmelCase			,  (list, tuple)   ):
       return self.create_dummy_data_list(__UpperCAmelCase			,  __UpperCAmelCase   )
      else:
       return self.create_dummy_data_single(__UpperCAmelCase			,  __UpperCAmelCase   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  *__UpperCAmelCase   ):

      '''simple docstring'''




      return self.download_and_extract(__UpperCAmelCase   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase   ):

      '''simple docstring'''




      return self.download_and_extract(__UpperCAmelCase   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  *__UpperCAmelCase			,  **__UpperCAmelCase   ):

      '''simple docstring'''




      return path





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      return {}





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= {}
      for key, single_urls in data_url.items():
       for download_callback in self.download_callbacks:
        if isinstance(__UpperCAmelCase			,  __UpperCAmelCase   ):
         for single_url in single_urls:
          download_callback(__UpperCAmelCase   )
        else:
         __UpperCamelCase       						= single_urls
         download_callback(__UpperCAmelCase   )
            # we force the name of each key to be the last file / folder name of the url path
            # if the url has arguments, we need to encode them with urllib.parse.quote_plus
       if isinstance(__UpperCAmelCase			,  __UpperCAmelCase   ):
        __UpperCamelCase       						= [os.path.join(__UpperCAmelCase			,  urllib.parse.quote_plus(Path(__UpperCAmelCase   ).name   )   ) for x in single_urls]
       else:
        __UpperCamelCase       						= single_urls
        __UpperCamelCase       						= os.path.join(__UpperCAmelCase			,  urllib.parse.quote_plus(Path(__UpperCAmelCase   ).name   )   )
       __UpperCamelCase       						= value

      # make sure that values are unique
      if all(isinstance(__UpperCAmelCase			,  __UpperCAmelCase   ) for i in dummy_data_dict.values()   ) and len(set(dummy_data_dict.values()   )   ) < len(
          dummy_data_dict.values()   ):
       # append key to value to make its name unique
       __UpperCamelCase       						= {key: value + key for key, value in dummy_data_dict.items()}

      return dummy_data_dict





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= []
      # trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
      __UpperCamelCase       						= all(bool(re.findall('[0-9]{3,}-of-[0-9]{3,}'			,  __UpperCAmelCase   )   ) for url in data_url   )
      __UpperCamelCase       						= all(
          url.startswith('https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed'   ) for url in data_url   )
      if data_url and (is_tf_records or is_pubmed_records):
       __UpperCamelCase       						= [data_url[0]] * len(__UpperCAmelCase   )
      for single_url in data_url:
       for download_callback in self.download_callbacks:
        download_callback(__UpperCAmelCase   )
       # we force the name of each key to be the last file / folder name of the url path
       # if the url has arguments, we need to encode them with urllib.parse.quote_plus
       __UpperCamelCase       						= os.path.join(__UpperCAmelCase			,  urllib.parse.quote_plus(single_url.split('/'   )[-1]   )   )
       dummy_data_list.append(__UpperCAmelCase   )
      return dummy_data_list





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase   ):

      '''simple docstring'''




      for download_callback in self.download_callbacks:
       download_callback(__UpperCAmelCase   )
      # we force the name of each key to be the last file / folder name of the url path
      # if the url has arguments, we need to encode them with urllib.parse.quote_plus
      __UpperCamelCase       						= os.path.join(__UpperCAmelCase			,  urllib.parse.quote_plus(data_url.split('/'   )[-1]   )   )
      if os.path.exists(__UpperCAmelCase   ) or not self.load_existing_dummy_data:
       return value
      else:
       # Backward compatibility, maybe deprecate at one point.
       # For many datasets with single url calls to dl_manager.download_and_extract,
       # the dummy_data.zip file is actually the zipped downloaded file
       # while now we expected the dummy_data.zip file to be a directory containing
       # the downloaded file.
       return path_to_dummy_data





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      pass





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      pass





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      def _iter_archive_members(__UpperCAmelCase   ):
       # this preserves the order of the members inside the ZIP archive
       __UpperCamelCase       						= Path(self.dummy_file   ).parent
       __UpperCamelCase       						= path.relative_to(__UpperCAmelCase   )
       with ZipFile(self.local_path_to_dummy_data   ) as zip_file:
        __UpperCamelCase       						= zip_file.namelist()
       for member in members:
        if member.startswith(relative_path.as_posix()   ):
         yield dummy_parent_path.joinpath(__UpperCAmelCase   )

      __UpperCamelCase       						= Path(__UpperCAmelCase   )
      __UpperCamelCase       						= _iter_archive_members(__UpperCAmelCase   ) if self.use_local_dummy_data else path.rglob('*'   )
      for file_path in file_paths:
       if file_path.is_file() and not file_path.name.startswith(('.', '__')   ):
        yield file_path.relative_to(__UpperCAmelCase   ).as_posix(), file_path.open('rb'   )







     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      if not isinstance(__UpperCAmelCase			,  __UpperCAmelCase   ):
       __UpperCamelCase       						= [paths]
      for path in paths:
       if os.path.isfile(__UpperCAmelCase   ):
        if os.path.basename(__UpperCAmelCase   ).startswith(('.', '__')   ):
         return
        yield path
       else:
        for dirpath, dirnames, filenames in os.walk(__UpperCAmelCase   ):
         if os.path.basename(__UpperCAmelCase   ).startswith(('.', '__')   ):
          continue
         dirnames.sort()
         for filename in sorted(__UpperCAmelCase   ):
          if filename.startswith(('.', '__')   ):
           continue
          yield os.path.join(__UpperCAmelCase			,  __UpperCAmelCase   )





"""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			:       Tuple									=				"."

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






def 							A		(       snake_case   :List[str]       ,      snake_case   :Optional[int]       ,      snake_case   :Optional[Any]	)   ->			Any:
 __UpperCamelCase       						= SavedModel()
 __UpperCamelCase       						= []

 with open(os.path.join(snake_case       ,      'utils'       ,      'tf_ops'       ,      'onnx.json'	)	) as f:
  __UpperCamelCase       						= 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()	)

 __UpperCamelCase       						= 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
 __UpperCamelCase       						= sorted(snake_case	)
 __UpperCamelCase       						= []

 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			:       List[str]									=				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			:       str									=				parser.parse_args()

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



