
'''simple docstring'''





import argparse

import torch
from torch import nn

from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration






def 		_UpperCAmelCase   (	UpperCamelCase:     Tuple  ):






	"""simple docstring"""


	__lowerCAmelCase         =							[
	    "encoder.version",
	    "decoder.version",
	    "model.encoder.version",
	    "model.decoder.version",
	    "decoder.output_projection.weight",
	    "_float_tensor",
	    "encoder.embed_positions._float_tensor",
	    "decoder.embed_positions._float_tensor",
	]
	for k in ignore_keys:
		state_dict.pop(UpperCamelCase			,							UpperCamelCase  )






def 		_UpperCAmelCase   (	UpperCamelCase:     List[str]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							list(s_dict.keys()  )
	for key in keys:
		if "transformer_layers" in key:
			__lowerCAmelCase         =							s_dict.pop(UpperCamelCase  )
		elif "subsample" in key:
			__lowerCAmelCase         =							s_dict.pop(UpperCamelCase  )






def 		_UpperCAmelCase   (	UpperCamelCase:     Any  ):






	"""simple docstring"""


	__lowerCAmelCase   ,						__lowerCAmelCase         =							emb.weight.shape
	__lowerCAmelCase         =							nn.Linear(UpperCamelCase			,							UpperCamelCase			,							bias=UpperCamelCase  )
	__lowerCAmelCase         =							emb.weight.data
	return lin_layer






def 		_UpperCAmelCase   (	UpperCamelCase:     Dict			,							UpperCamelCase:     List[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							torch.load(UpperCamelCase			,							map_location="cpu"  )
	__lowerCAmelCase         =							mam_aaa["args"]
	__lowerCAmelCase         =							mam_aaa["model"]
	__lowerCAmelCase         =							state_dict["decoder.output_projection.weight"]

	remove_ignore_keys_(UpperCamelCase  )
	rename_keys(UpperCamelCase  )

	__lowerCAmelCase         =							state_dict["decoder.embed_tokens.weight"].shape[0]

	__lowerCAmelCase         =							args.share_decoder_input_output_embed

	__lowerCAmelCase         =							[int(UpperCamelCase  ) for i in args.conv_kernel_sizes.split(","  )]
	__lowerCAmelCase         =							SpeechaTextConfig(
	    vocab_size=UpperCamelCase			,							max_source_positions=args.max_source_positions			,							max_target_positions=args.max_target_positions			,							encoder_layers=args.encoder_layers			,							decoder_layers=args.decoder_layers			,							encoder_attention_heads=args.encoder_attention_heads			,							decoder_attention_heads=args.decoder_attention_heads			,							encoder_ffn_dim=args.encoder_ffn_embed_dim			,							decoder_ffn_dim=args.decoder_ffn_embed_dim			,							d_model=args.encoder_embed_dim			,							dropout=args.dropout			,							attention_dropout=args.attention_dropout			,							activation_dropout=args.activation_dropout			,							activation_function="relu"			,							num_conv_layers=len(UpperCamelCase  )			,							conv_channels=args.conv_channels			,							conv_kernel_sizes=UpperCamelCase			,							input_feat_per_channel=args.input_feat_per_channel			,							input_channels=args.input_channels			,							tie_word_embeddings=UpperCamelCase			,							num_beams=5			,							max_length=2_0_0			,							use_cache=UpperCamelCase			,							decoder_start_token_id=2			,							early_stopping=UpperCamelCase			,							)

	__lowerCAmelCase         =							SpeechaTextForConditionalGeneration(UpperCamelCase  )
	__lowerCAmelCase   ,						__lowerCAmelCase         =							model.model.load_state_dict(UpperCamelCase			,							strict=UpperCamelCase  )
	if len(UpperCamelCase  ) > 0 and not set(UpperCamelCase  ) <= {
	    "encoder.embed_positions.weights",
	    "decoder.embed_positions.weights",
	}:
		raise ValueError(
		    "Only `encoder.embed_positions.weights` and `decoder.embed_positions.weights`  are allowed to be missing,"
		    F" but all the following weights are missing {missing}"  )

	if tie_embeds:
		__lowerCAmelCase         =							make_linear_from_emb(model.model.decoder.embed_tokens  )
	else:
		__lowerCAmelCase         =							lm_head_weights

	model.save_pretrained(UpperCamelCase  )


if __name__ == "__main__":
					UpperCamelCase_   	=	argparse.ArgumentParser()
					# Required parameters
					parser.add_argument("--fairseq_path", type=str, help="Path to the fairseq model (.pt) file.")
					parser.add_argument("--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model.")
					UpperCamelCase_   	=	parser.parse_args()
					convert_fairseq_sat_checkpoint_to_tfms(args.fairseq_path, args.pytorch_dump_folder_path)








from __future__ import annotations

from collections.abc import Iterator
from typing import Any

class       a		:







							def __init__(						self  :  Optional[int]      ,				snake_case__  :  Any ):
								"""simple docstring"""







								__lowerCAmelCase         =							data
								__lowerCAmelCase         =							None

class       a		:







							def __init__(						self  :  Optional[Any] ):
								"""simple docstring"""







								__lowerCAmelCase         =							None
								__lowerCAmelCase         =							None







							def __iter__(						self  :  Dict ):
								"""simple docstring"""







								__lowerCAmelCase         =							self.head
								while self.head:
									yield node.data
									__lowerCAmelCase         =							node.next
									if node == self.head:
										break







							def __len__(						self  :  Dict ):
								"""simple docstring"""







								return sum(1 for _ in self )







							def __repr__(						self  :  str ):
								"""simple docstring"""







								return "->".join(str(snake_case__ ) for item in iter(self ) )







							def       UpperCAmelCase__					(						self  :  Optional[Any]      ,				snake_case__  :  Any ):
								"""simple docstring"""







								self.insert_nth(len(self )      ,				snake_case__ )







							def       UpperCAmelCase__					(						self  :  Union[str, Any]      ,				snake_case__  :  Any ):
								"""simple docstring"""







								self.insert_nth(0      ,				snake_case__ )







							def       UpperCAmelCase__					(						self  :  List[Any]      ,				snake_case__  :  int      ,				snake_case__  :  Any ):
								"""simple docstring"""







								if index < 0 or index > len(self ):
									raise IndexError("list index out of range." )
								__lowerCAmelCase         =							Node(snake_case__ )
								if self.head is None:
									__lowerCAmelCase         =							new_node  # first node points itself
									__lowerCAmelCase         =							__lowerCAmelCase         =							new_node
								elif index == 0:  # insert at head
									__lowerCAmelCase         =							self.head
									__lowerCAmelCase         =							__lowerCAmelCase         =							new_node
								else:
									__lowerCAmelCase         =							self.head
									for _ in range(index - 1 ):
										__lowerCAmelCase         =							temp.next
									__lowerCAmelCase         =							temp.next
									__lowerCAmelCase         =							new_node
									if index == len(self ) - 1:  # insert at tail
										__lowerCAmelCase         =							new_node







							def       UpperCAmelCase__					(						self  :  List[Any] ):
								"""simple docstring"""







								return self.delete_nth(0 )







							def       UpperCAmelCase__					(						self  :  Union[str, Any] ):
								"""simple docstring"""







								return self.delete_nth(len(self ) - 1 )







							def       UpperCAmelCase__					(						self  :  str      ,				snake_case__  :  int = 0 ):
								"""simple docstring"""







								if not 0 <= index < len(self ):
									raise IndexError("list index out of range." )
								__lowerCAmelCase         =							self.head
								if self.head == self.tail:  # just one node
									__lowerCAmelCase         =							__lowerCAmelCase         =							None
								elif index == 0:  # delete head node
									__lowerCAmelCase         =							self.tail.next.next
									__lowerCAmelCase         =							self.head.next
								else:
									__lowerCAmelCase         =							self.head
									for _ in range(index - 1 ):
										__lowerCAmelCase         =							temp.next
									__lowerCAmelCase         =							temp.next
									__lowerCAmelCase         =							temp.next.next
									if index == len(self ) - 1:  # delete at tail
										__lowerCAmelCase         =							temp
								return delete_node.data







							def       UpperCAmelCase__					(						self  :  str ):
								"""simple docstring"""







								return len(self ) == 0






def 		_UpperCAmelCase   (	):






	"""simple docstring"""


	__lowerCAmelCase         =							CircularLinkedList()
	assert len(UpperCamelCase  ) == 0
	assert circular_linked_list.is_empty() is True
	assert str(UpperCamelCase  ) == ""

	try:
		circular_linked_list.delete_front()
		raise AssertionError  # This should not happen
	except IndexError:
		assert True  # This should happen

	try:
		circular_linked_list.delete_tail()
		raise AssertionError  # This should not happen
	except IndexError:
		assert True  # This should happen

	try:
		circular_linked_list.delete_nth(-1  )
		raise AssertionError
	except IndexError:
		assert True

	try:
		circular_linked_list.delete_nth(0  )
		raise AssertionError
	except IndexError:
		assert True

	assert circular_linked_list.is_empty() is True
	for i in range(5  ):
		assert len(UpperCamelCase  ) == i
		circular_linked_list.insert_nth(UpperCamelCase			,							i + 1  )
	assert str(UpperCamelCase  ) == "->".join(str(UpperCamelCase  ) for i in range(1			,							6  )  )

	circular_linked_list.insert_tail(6  )
	assert str(UpperCamelCase  ) == "->".join(str(UpperCamelCase  ) for i in range(1			,							7  )  )
	circular_linked_list.insert_head(0  )
	assert str(UpperCamelCase  ) == "->".join(str(UpperCamelCase  ) for i in range(0			,							7  )  )

	assert circular_linked_list.delete_front() == 0
	assert circular_linked_list.delete_tail() == 6
	assert str(UpperCamelCase  ) == "->".join(str(UpperCamelCase  ) for i in range(1			,							6  )  )
	assert circular_linked_list.delete_nth(2  ) == 3

	circular_linked_list.insert_nth(2			,							3  )
	assert str(UpperCamelCase  ) == "->".join(str(UpperCamelCase  ) for i in range(1			,							6  )  )

	assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
					import doctest

					doctest.testmod()






