




"""simple docstring"""

import argparse

import torch
from torch import nn

from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration




def     _A					( __lowercase    ):





       """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(lowercase__							,     lowercase__    )




def     _A					( __lowercase    ):





       """simple docstring"""



       lowerCamelCase__     ,	lowerCamelCase__          =						emb.weight.shape
       lowerCamelCase__          =						nn.Linear(lowercase__							,     lowercase__							,     bias=lowercase__    )
       lowerCamelCase__          =						emb.weight.data
       return lin_layer




def     _A					( __lowercase    ):





       """simple docstring"""



       lowerCamelCase__          =						torch.load(lowercase__							,     map_location="""cpu"""    )
       lowerCamelCase__          =						mam_aaa["""args"""] or mam_aaa["""cfg"""]["""model"""]
       lowerCamelCase__          =						mam_aaa["""model"""]
       remove_ignore_keys_(lowercase__    )
       lowerCamelCase__          =						state_dict["""encoder.embed_tokens.weight"""].shape[0]

       lowerCamelCase__          =						MaMaaaConfig(
           vocab_size=lowercase__							,     max_position_embeddings=1024							,     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							,     encoder_layerdrop=args.encoder_layerdrop							,     decoder_layerdrop=args.decoder_layerdrop							,     dropout=args.dropout							,     attention_dropout=args.attention_dropout							,     activation_dropout=args.activation_dropout							,     activation_function="""relu"""							,     )

       lowerCamelCase__          =						state_dict["""decoder.embed_tokens.weight"""]
       lowerCamelCase__          =						MaMaaaForConditionalGeneration(lowercase__    )
       model.model.load_state_dict(lowercase__							,     strict=lowercase__    )
       lowerCamelCase__          =						make_linear_from_emb(model.model.shared    )

       return model


if __name__ == "__main__":
  __magic_name__				     =     argparse.ArgumentParser()
  # Required parameters
  parser.add_argument("""fairseq_path""", type=str, help="""path to a model.pt on local filesystem.""")
  parser.add_argument("""pytorch_dump_folder_path""", default=None, type=str, help="""Path to the output PyTorch model.""")
  __magic_name__				     =     parser.parse_args()
  __magic_name__				     =     convert_fairseq_mamaaa_checkpoint_from_disk(args.fairseq_pathß)
  model.save_pretrained(args.pytorch_dump_folder_path)










"""simple docstring"""




import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from requests.exceptions import HTTPError

from transformers.utils import (
    CONFIG_NAME,
    FLAX_WEIGHTS_NAME,
    TF2_WEIGHTS_NAME,
    TRANSFORMERS_CACHE,
    WEIGHTS_NAME,
    cached_file,
    get_file_from_repo,
    has_file,
)


__magic_name__						: Tuple    =				'hf-internal-testing/tiny-random-bert'
__magic_name__						: Dict    =				os.path.join(TRANSFORMERS_CACHE, 'models--hf-internal-testing--tiny-random-bert')
__magic_name__						: Optional[Any]    =				'9b8c223d42b2188cb49d29af482996f9d0f3e5a6'




class 			__snake_case   (unittest.TestCase  ):




							def   __a   (     self:    List[Any]   ):
										__lowerCamelCase          =      cached_file(A_     ,							A_   )
										# Should have downloaded the file in here
										self.assertTrue(os.path.isdir(A_   )   )
										# Cache should contain at least those three subfolders:
										for subfolder in ["blobs", "refs", "snapshots"]:
													self.assertTrue(os.path.isdir(os.path.join(A_     ,							A_   )   )   )
										with open(os.path.join(A_     ,							"""refs"""     ,							"""main"""   )   ) as f:
													__lowerCamelCase          =      f.read()
										self.assertEqual(A_     ,							os.path.join(A_     ,							"""snapshots"""     ,							A_     ,							A_   )   )
										self.assertTrue(os.path.isfile(A_   )   )

										# File is cached at the same place the second time.
										__lowerCamelCase          =      cached_file(A_     ,							A_   )
										self.assertEqual(A_     ,							A_   )

										# Using a specific revision to test the full commit hash.
										__lowerCamelCase          =      cached_file(A_     ,							A_     ,							revision="""9b8c223"""   )
										self.assertEqual(A_     ,							os.path.join(A_     ,							"""snapshots"""     ,							A_     ,							A_   )   )




							def   __a   (     self:    int   ):
										with self.assertRaisesRegex(A_     ,							"""is not a valid model identifier"""   ):
													__lowerCamelCase          =      cached_file("""tiny-random-bert"""     ,							A_   )

										with self.assertRaisesRegex(A_     ,							"""is not a valid git identifier"""   ):
													__lowerCamelCase          =      cached_file(A_     ,							A_     ,							revision="""aaaa"""   )

										with self.assertRaisesRegex(A_     ,							"""does not appear to have a file named"""   ):
													__lowerCamelCase          =      cached_file(A_     ,							"""conf"""   )




							def   __a   (     self:    Optional[int]   ):
										with self.assertRaisesRegex(A_     ,							"""does not appear to have a file named"""   ):
													__lowerCamelCase          =      cached_file(A_     ,							"""conf"""   )

										with open(os.path.join(A_     ,							"""refs"""     ,							"""main"""   )   ) as f:
													__lowerCamelCase          =      f.read()
										self.assertTrue(os.path.isfile(os.path.join(A_     ,							""".no_exist"""     ,							A_     ,							"""conf"""   )   )   )

										__lowerCamelCase          =      cached_file(A_     ,							"""conf"""     ,							_raise_exceptions_for_missing_entries=A_   )
										self.assertIsNone(A_   )

										__lowerCamelCase          =      cached_file(A_     ,							"""conf"""     ,							local_files_only=A_     ,							_raise_exceptions_for_missing_entries=A_   )
										self.assertIsNone(A_   )

										__lowerCamelCase          =      mock.Mock()
										__lowerCamelCase          =      5_00
										__lowerCamelCase          =      {}
										__lowerCamelCase          =      HTTPError
										__lowerCamelCase          =      {}

										# Under the mock environment we get a 500 error when trying to reach the tokenizer.
										with mock.patch("""requests.Session.request"""     ,							return_value=A_   ) as mock_head:
													__lowerCamelCase          =      cached_file(A_     ,							"""conf"""     ,							_raise_exceptions_for_connection_errors=A_   )
													self.assertIsNone(A_   )
													# This check we did call the fake head request
													mock_head.assert_called()




							def   __a   (     self:    str   ):
										self.assertTrue(has_file("""hf-internal-testing/tiny-bert-pt-only"""     ,							A_   )   )
										self.assertFalse(has_file("""hf-internal-testing/tiny-bert-pt-only"""     ,							A_   )   )
										self.assertFalse(has_file("""hf-internal-testing/tiny-bert-pt-only"""     ,							A_   )   )




							def   __a   (     self:    str   ):
										# `get_file_from_repo` returns None if the file does not exist
										self.assertIsNone(get_file_from_repo("""bert-base-cased"""     ,							"""ahah.txt"""   )   )

										# The function raises if the repository does not exist.
										with self.assertRaisesRegex(A_     ,							"""is not a valid model identifier"""   ):
													get_file_from_repo("""bert-base-case"""     ,							A_   )

										# The function raises if the revision does not exist.
										with self.assertRaisesRegex(A_     ,							"""is not a valid git identifier"""   ):
													get_file_from_repo("""bert-base-cased"""     ,							A_     ,							revision="""ahaha"""   )

										__lowerCamelCase          =      get_file_from_repo("""bert-base-cased"""     ,							A_   )
										# The name is the cached name which is not very easy to test, so instead we load the content.
										__lowerCamelCase          =      json.loads(open(A_     ,							"""r"""   ).read()   )
										self.assertEqual(config["""hidden_size"""]     ,							7_68   )




							def   __a   (     self:    Union[str, Any]   ):
										with tempfile.TemporaryDirectory() as tmp_dir:
													__lowerCamelCase          =      Path(A_   ) / """a.txt"""
													filename.touch()
													self.assertEqual(get_file_from_repo(A_     ,							"""a.txt"""   )     ,							str(A_   )   )

													self.assertIsNone(get_file_from_repo(A_     ,							"""b.txt"""   )   )




