


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
__a     =			"""."""

# Internal TensorFlow ops that can be safely ignored (mostly specific to a saved model)
__a     =			[
    """Assert""",
    """AssignVariableOp""",
    """EmptyTensorList""",
    """MergeV2Checkpoints""",
    """ReadVariableOp""",
    """ResourceGather""",
    """RestoreV2""",
    """SaveV2""",
    """ShardedFilename""",
    """StatefulPartitionedCall""",
    """StaticRegexFullMatch""",
    """VarHandleOp""",
]
def   _UpperCamelCase				(						lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_   )						->List[str]:
   UpperCAmelCase							=     SavedModel()
   UpperCAmelCase							=     []

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

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

   with open(lowerCAmelCase_  ,						"""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(lowerCAmelCase_   )
   UpperCAmelCase							=     []

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

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


if __name__ == "__main__":
 __a     =			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)"""
 )
 __a     =			parser.parse_args()

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







from ...configuration_utils import PretrainedConfig
from ...utils import logging


__a     =			logging.get_logger(__name__)

__a     =			{"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}






class   __lowercase				(  __snake_case  ):
      UpperCamelCase								=       '''ctrl'''
      UpperCamelCase								=       ['''past_key_values''']
      UpperCamelCase								=       {
          '''max_position_embeddings''': '''n_positions''',
          '''hidden_size''': '''n_embd''',
          '''num_attention_heads''': '''n_head''',
          '''num_hidden_layers''': '''n_layer''',
      }





      def __init__(		self						:					str					,       __lowerCamelCase						:					Optional[int]=2_4_6_5_3_4					,       __lowerCamelCase						:					Union[str, Any]=2_5_6					,       __lowerCamelCase						:					int=1_2_8_0					,       __lowerCamelCase						:					Optional[Any]=8_1_9_2					,       __lowerCamelCase						:					List[str]=4_8					,       __lowerCamelCase						:					Dict=1_6					,       __lowerCamelCase						:					Union[str, Any]=0.1					,       __lowerCamelCase						:					Union[str, Any]=0.1					,       __lowerCamelCase						:					Union[str, Any]=1e-6					,       __lowerCamelCase						:					str=0.02					,       __lowerCamelCase						:					Union[str, Any]=True					,       **__lowerCamelCase						:					List[str]					,       )    ->   Optional[Any]:






         """simple docstring"""







         UpperCAmelCase							=     vocab_size
         UpperCAmelCase							=     n_positions
         UpperCAmelCase							=     n_embd
         UpperCAmelCase							=     n_layer
         UpperCAmelCase							=     n_head
         UpperCAmelCase							=     dff
         UpperCAmelCase							=     resid_pdrop
         UpperCAmelCase							=     embd_pdrop
         UpperCAmelCase							=     layer_norm_epsilon
         UpperCAmelCase							=     initializer_range

         UpperCAmelCase							=     use_cache

         super().__init__(**__lowerCamelCase       )



