





"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - generate model_cards - useful if you have multiple models from the same paper

import argparse
import json
import os
import re
from collections import OrderedDict
from os.path import basename, dirname

import fairseq
import torch
from fairseq import hub_utils
from fairseq.data.dictionary import Dictionary

from transformers import FSMTConfig, FSMTForConditionalGeneration
from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transformers.utils import WEIGHTS_NAME, logging


logging.set_verbosity_warning()

__UpperCamelCase     :						str						       =  2

# based on the results of a search on a range of `num_beams`, `length_penalty` and `early_stopping`
# values against wmt19 test data to obtain the best BLEU scores, we will use the following defaults:
#
# * `num_beams`: 5 (higher scores better, but requires more memory/is slower, can be adjusted by users)
# * `early_stopping`: `False` consistently scored better
# * `length_penalty` varied, so will assign the best one depending on the model
__UpperCamelCase     :						Tuple						       =  {
    # fairseq:
    '''wmt19-ru-en''': {'''length_penalty''': 1.1},
    '''wmt19-en-ru''': {'''length_penalty''': 1.15},
    '''wmt19-en-de''': {'''length_penalty''': 1.0},
    '''wmt19-de-en''': {'''length_penalty''': 1.1},
    # allenai:
    '''wmt16-en-de-dist-12-1''': {'''length_penalty''': 0.6},
    '''wmt16-en-de-dist-6-1''': {'''length_penalty''': 0.6},
    '''wmt16-en-de-12-1''': {'''length_penalty''': 0.8},
    '''wmt19-de-en-6-6-base''': {'''length_penalty''': 0.6},
    '''wmt19-de-en-6-6-big''': {'''length_penalty''': 0.6},
}

# this remaps the different models to their organization names
__UpperCamelCase     :						int						       =  {}
for m in ["wmt19-ru-en", "wmt19-en-ru", "wmt19-en-de", "wmt19-de-en"]:
       __UpperCamelCase     :						str						       =  '''facebook'''
for m in [
    "wmt16-en-de-dist-12-1",
    "wmt16-en-de-dist-6-1",
    "wmt16-en-de-12-1",
    "wmt19-de-en-6-6-base",
    "wmt19-de-en-6-6-big",
]:
       __UpperCamelCase     :						Any						       =  '''allenai'''

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    Union[str, Any]			):
 # (1) remove word breaking symbol, (2) add word ending symbol where the word is not broken up,
 # e.g.: d = {'le@@': 5, 'tt@@': 6, 'er': 7} => {'le': 5, 'tt': 6, 'er</w>': 7}
 lowerCAmelCase    				= dict((re.sub(R'@@$'  ,     ''  ,     _UpperCAmelCase			), v) if k.endswith('@@'			) else (re.sub(R'$'  ,     '</w>'  ,     _UpperCAmelCase			), v) for k, v in d.items()			)
 lowerCAmelCase    				= '<s> <pad> </s> <unk>'.split()
 # restore the special tokens
 for k in keep_keys:
  del da[F'{k}</w>']
  lowerCAmelCase    				= d[k]  # restore
 return da

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    str  ,     _UpperCAmelCase					:    Any			):
 # prep
 assert os.path.exists(_UpperCAmelCase			)
 os.makedirs(_UpperCAmelCase  ,     exist_ok=_UpperCAmelCase			)
 print(F'Writing results to {pytorch_dump_folder_path}'			)

 # handle various types of models

 lowerCAmelCase    				= basename(_UpperCAmelCase			)
 lowerCAmelCase    				= dirname(_UpperCAmelCase			)

 lowerCAmelCase    				= fairseq.model_parallel.models.transformer.ModelParallelTransformerModel
 lowerCAmelCase    				= cls.hub_models()
 lowerCAmelCase    				= {'bpe': 'fastbpe', 'tokenizer': 'moses'}
 lowerCAmelCase    				= '.'
 # note: since the model dump is old, fairseq has upgraded its model some
 # time later, and it does a whole lot of rewrites and splits on the saved
 # weights, therefore we can't use torch.load() directly on the model file.
 # see: upgrade_state_dict(state_dict) in fairseq_model.py
 print(F'using checkpoint {checkpoint_file}'			)
 lowerCAmelCase    				= hub_utils.from_pretrained(
     _UpperCAmelCase  ,     _UpperCAmelCase  ,     _UpperCAmelCase  ,     archive_map=_UpperCAmelCase  ,     **_UpperCAmelCase			)

 lowerCAmelCase    				= vars(chkpt['args']['model']			)

 lowerCAmelCase    				= args['source_lang']
 lowerCAmelCase    				= args['target_lang']

 lowerCAmelCase    				= dirname(_UpperCAmelCase			)
 lowerCAmelCase    				= basename(_UpperCAmelCase			)

 # dicts
 lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     F'dict.{src_lang}.txt'			)
 lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     F'dict.{tgt_lang}.txt'			)

 lowerCAmelCase    				= Dictionary.load(_UpperCAmelCase			)
 lowerCAmelCase    				= rewrite_dict_keys(src_dict.indices			)
 lowerCAmelCase    				= len(_UpperCAmelCase			)
 lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     'vocab-src.json'			)
 print(F'Generating {src_vocab_file} of {src_vocab_size} of {src_lang} records'			)
 with open(_UpperCAmelCase  ,     'w'  ,     encoding='utf-8'			) as f:
  f.write(json.dumps(_UpperCAmelCase  ,     ensure_ascii=_UpperCAmelCase  ,     indent=_UpperCAmelCase			)			)

 # detect whether this is a do_lower_case situation, which can be derived by checking whether we
 # have at least one uppercase letter in the source vocab
 lowerCAmelCase    				= True
 for k in src_vocab.keys():
  if not k.islower():
   lowerCAmelCase    				= False
   break

 lowerCAmelCase    				= Dictionary.load(_UpperCAmelCase			)
 lowerCAmelCase    				= rewrite_dict_keys(tgt_dict.indices			)
 lowerCAmelCase    				= len(_UpperCAmelCase			)
 lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     'vocab-tgt.json'			)
 print(F'Generating {tgt_vocab_file} of {tgt_vocab_size} of {tgt_lang} records'			)
 with open(_UpperCAmelCase  ,     'w'  ,     encoding='utf-8'			) as f:
  f.write(json.dumps(_UpperCAmelCase  ,     ensure_ascii=_UpperCAmelCase  ,     indent=_UpperCAmelCase			)			)

 # merges_file (bpecodes)
 lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     VOCAB_FILES_NAMES['merges_file']			)
 for fn in ["bpecodes", "code"]:  # older fairseq called the merges file "code"
  lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     _UpperCAmelCase			)
  if os.path.exists(_UpperCAmelCase			):
   break
 with open(_UpperCAmelCase  ,     encoding='utf-8'			) as fin:
  lowerCAmelCase    				= fin.read()
 lowerCAmelCase    				= re.sub(R' \d+$'  ,     ''  ,     _UpperCAmelCase  ,     0  ,     re.M			)  # remove frequency number
 print(F'Generating {merges_file}'			)
 with open(_UpperCAmelCase  ,     'w'  ,     encoding='utf-8'			) as fout:
  fout.write(_UpperCAmelCase			)

 # model config
 lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     'config.json'			)

 # validate bpe/tokenizer config, as currently it's hardcoded to moses+fastbpe -
 # may have to modify the tokenizer if a different type is used by a future model
 assert args["bpe"] == "fastbpe", F'need to extend tokenizer to support bpe={args["bpe"]}'
 assert args["tokenizer"] == "moses", F'need to extend tokenizer to support bpe={args["tokenizer"]}'

 lowerCAmelCase    				= {
     'architectures': ['FSMTForConditionalGeneration'],
     'model_type': 'fsmt',
     'activation_dropout': args['activation_dropout'],
     'activation_function': 'relu',
     'attention_dropout': args['attention_dropout'],
     'd_model': args['decoder_embed_dim'],
     'dropout': args['dropout'],
     'init_std': 0.02,
     'max_position_embeddings': args['max_source_positions'],
     'num_hidden_layers': args['encoder_layers'],
     'src_vocab_size': src_vocab_size,
     'tgt_vocab_size': tgt_vocab_size,
     'langs': [src_lang, tgt_lang],
     'encoder_attention_heads': args['encoder_attention_heads'],
     'encoder_ffn_dim': args['encoder_ffn_embed_dim'],
     'encoder_layerdrop': args['encoder_layerdrop'],
     'encoder_layers': args['encoder_layers'],
     'decoder_attention_heads': args['decoder_attention_heads'],
     'decoder_ffn_dim': args['decoder_ffn_embed_dim'],
     'decoder_layerdrop': args['decoder_layerdrop'],
     'decoder_layers': args['decoder_layers'],
     'bos_token_id': 0,
     'pad_token_id': 1,
     'eos_token_id': 2,
     'is_encoder_decoder': True,
     'scale_embedding': not args['no_scale_embedding'],
     'tie_word_embeddings': args['share_all_embeddings'],
 }

 # good hparam defaults to start with
 lowerCAmelCase    				= 5
 lowerCAmelCase    				= False
 if model_dir in best_score_hparams and "length_penalty" in best_score_hparams[model_dir]:
  lowerCAmelCase    				= best_score_hparams[model_dir]['length_penalty']
 else:
  lowerCAmelCase    				= 1.0

 print(F'Generating {fsmt_model_config_file}'			)
 with open(_UpperCAmelCase  ,     'w'  ,     encoding='utf-8'			) as f:
  f.write(json.dumps(_UpperCAmelCase  ,     ensure_ascii=_UpperCAmelCase  ,     indent=_UpperCAmelCase			)			)

 # tokenizer config
 lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     _UpperCAmelCase			)

 lowerCAmelCase    				= {
     'langs': [src_lang, tgt_lang],
     'model_max_length': 1024,
     'do_lower_case': do_lower_case,
 }

 print(F'Generating {fsmt_tokenizer_config_file}'			)
 with open(_UpperCAmelCase  ,     'w'  ,     encoding='utf-8'			) as f:
  f.write(json.dumps(_UpperCAmelCase  ,     ensure_ascii=_UpperCAmelCase  ,     indent=_UpperCAmelCase			)			)

 # model
 lowerCAmelCase    				= chkpt['models'][0]
 lowerCAmelCase    				= model.state_dict()

 # rename keys to start with 'model.'
 lowerCAmelCase    				= OrderedDict(('model.' + k, v) for k, v in model_state_dict.items()			)

 # remove unneeded keys
 lowerCAmelCase    				= [
     'model.model',
     'model.encoder.version',
     'model.decoder.version',
     'model.encoder_embed_tokens.weight',
     'model.decoder_embed_tokens.weight',
     'model.encoder.embed_positions._float_tensor',
     'model.decoder.embed_positions._float_tensor',
 ]
 for k in ignore_keys:
  model_state_dict.pop(_UpperCAmelCase  ,     _UpperCAmelCase			)

 lowerCAmelCase    				= FSMTConfig.from_pretrained(_UpperCAmelCase			)
 lowerCAmelCase    				= FSMTForConditionalGeneration(_UpperCAmelCase			)

 # check that it loads ok
 model_new.load_state_dict(_UpperCAmelCase  ,     strict=_UpperCAmelCase			)

 # save
 lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     _UpperCAmelCase			)
 print(F'Generating {pytorch_weights_dump_path}'			)
 torch.save(_UpperCAmelCase  ,     _UpperCAmelCase			)

 print('Conversion is done!'			)
 print('\nLast step is to upload the files to s3'			)
 print(F'cd {data_root}'			)
 print(F'transformers-cli upload {model_dir}'			)


if __name__ == "__main__":
       __UpperCamelCase     :						List[Any]						       =  argparse.ArgumentParser()
       # Required parameters
       parser.add_argument(
           '''--fsmt_checkpoint_path''',
           default=None,
           type=str,
           required=True,
           help=(
               '''Path to the official PyTorch checkpoint file which is expected to reside in the dump dir with dicts,'''
               ''' bpecodes, etc.'''
           ),
       )
       parser.add_argument(
           '''--pytorch_dump_folder_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
       )
       __UpperCamelCase     :						Tuple						       =  parser.parse_args()
       convert_fsmt_checkpoint_to_pytorch(args.fsmt_checkpoint_path, args.pytorch_dump_folder_path)












"""simple docstring"""
from typing import Any







class       a							:



 def __init__(     self				,       _snake_case     ):







  """simple docstring"""






  lowerCAmelCase    				= data
  lowerCAmelCase    				= None



 def __repr__(     self     ):







  """simple docstring"""






  return F'Node({self.data})'







class       a							:



 def __init__(     self     ):







  """simple docstring"""






  lowerCAmelCase    				= None



 def __iter__(     self     ):







  """simple docstring"""






  lowerCAmelCase    				= self.head
  while node:
   yield node.data
   lowerCAmelCase    				= node.next



 def __len__(     self     ):







  """simple docstring"""






  return sum(1 for _ in self     )



 def __repr__(     self     ):







  """simple docstring"""






  return "->".join([str(_snake_case     ) for item in self]     )



 def __getitem__(     self				,       _snake_case     ):







  """simple docstring"""






  if not 0 <= index < len(self     ):
   raise ValueError('list index out of range.'     )
  for i, node in enumerate(self     ):
   if i == index:
    return node
  return None



 def __setitem__(     self				,       _snake_case				,       _snake_case     ):







  """simple docstring"""






  if not 0 <= index < len(self     ):
   raise ValueError('list index out of range.'     )
  lowerCAmelCase    				= self.head
  for _ in range(_snake_case     ):
   lowerCAmelCase    				= current.next
  lowerCAmelCase    				= data



 def    UpperCamelCase__  (     self				,       _snake_case     ):







  """simple docstring"""






  self.insert_nth(len(self     )				,       _snake_case     )



 def    UpperCamelCase__  (     self				,       _snake_case     ):







  """simple docstring"""






  self.insert_nth(0				,       _snake_case     )



 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case     ):







  """simple docstring"""






  if not 0 <= index <= len(self     ):
   raise IndexError('list index out of range'     )
  lowerCAmelCase    				= Node(_snake_case     )
  if self.head is None:
   lowerCAmelCase    				= new_node
  elif index == 0:
   lowerCAmelCase    				= self.head  # link new_node to head
   lowerCAmelCase    				= new_node
  else:
   lowerCAmelCase    				= self.head
   for _ in range(index - 1     ):
    lowerCAmelCase    				= temp.next
   lowerCAmelCase    				= temp.next
   lowerCAmelCase    				= new_node



 def    UpperCamelCase__  (     self     ):  # print every node data







  """simple docstring"""






  print(self     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  return self.delete_nth(0     )



 def    UpperCamelCase__  (     self     ):  # delete from tail







  """simple docstring"""






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



 def    UpperCamelCase__  (     self				,       _snake_case = 0     ):







  """simple docstring"""






  if not 0 <= index <= len(self     ) - 1:  # test if index is valid
   raise IndexError('List index out of range.'     )
  lowerCAmelCase    				= self.head  # default first node
  if index == 0:
   lowerCAmelCase    				= self.head.next
  else:
   lowerCAmelCase    				= self.head
   for _ in range(index - 1     ):
    lowerCAmelCase    				= temp.next
   lowerCAmelCase    				= temp.next
   lowerCAmelCase    				= temp.next.next
  return delete_node.data



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  return self.head is None



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  lowerCAmelCase    				= None
  lowerCAmelCase    				= self.head

  while current:
   # Store the current node's next node.
   lowerCAmelCase    				= current.next
   # Make the current node's next point backwards
   lowerCAmelCase    				= prev
   # Make the previous node be the current node
   lowerCAmelCase    				= current
   # Make the current node the next node (to progress iteration)
   lowerCAmelCase    				= next_node
  # Return prev in order to put the head at the end
  lowerCAmelCase    				= prev


def 		_SCREAMING_SNAKE_CASE			():
 lowerCAmelCase    				= LinkedList()
 assert linked_list.is_empty() is True
 assert str(_UpperCAmelCase			) == ""

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

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

 for i in range(10			):
  assert len(_UpperCAmelCase			) == i
  linked_list.insert_nth(_UpperCAmelCase  ,     i + 1			)
 assert str(_UpperCAmelCase			) == "->".join(str(_UpperCAmelCase			) for i in range(1  ,     11			)			)

 linked_list.insert_head(0			)
 linked_list.insert_tail(11			)
 assert str(_UpperCAmelCase			) == "->".join(str(_UpperCAmelCase			) for i in range(0  ,     12			)			)

 assert linked_list.delete_head() == 0
 assert linked_list.delete_nth(9			) == 10
 assert linked_list.delete_tail() == 11
 assert len(_UpperCAmelCase			) == 9
 assert str(_UpperCAmelCase			) == "->".join(str(_UpperCAmelCase			) for i in range(1  ,     10			)			)

 assert all(linked_list[i] == i + 1 for i in range(0  ,     9			)			) is True

 for i in range(0  ,     9			):
  lowerCAmelCase    				= -i
 assert all(linked_list[i] == -i for i in range(0  ,     9			)			) is True

 linked_list.reverse()
 assert str(_UpperCAmelCase			) == "->".join(str(_UpperCAmelCase			) for i in range(-8  ,     1			)			)

def 		_SCREAMING_SNAKE_CASE			():
 lowerCAmelCase    				= [
     -9,
     100,
     Node(7734_5112			),
     'dlrow olleH',
     7,
     5555,
     0,
     -192.5_5555,
     'Hello, world!',
     77.9,
     Node(10			),
     None,
     None,
     12.20,
 ]
 lowerCAmelCase    				= LinkedList()

 for i in test_input:
  linked_list.insert_tail(_UpperCAmelCase			)

 # Check if it's empty or not
 assert linked_list.is_empty() is False
 assert (
     str(_UpperCAmelCase			) == "-9->100->Node(77345112)->dlrow olleH->7->5555->0->"
     "-192.55555->Hello, world!->77.9->Node(10)->None->None->12.2"
 )

 # Delete the head
 lowerCAmelCase    				= linked_list.delete_head()
 assert result == -9
 assert (
     str(_UpperCAmelCase			) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
     "Hello, world!->77.9->Node(10)->None->None->12.2"
 )

 # Delete the tail
 lowerCAmelCase    				= linked_list.delete_tail()
 assert result == 12.2
 assert (
     str(_UpperCAmelCase			) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
     "Hello, world!->77.9->Node(10)->None->None"
 )

 # Delete a node in specific location in linked list
 lowerCAmelCase    				= linked_list.delete_nth(10			)
 assert result is None
 assert (
     str(_UpperCAmelCase			) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
     "Hello, world!->77.9->Node(10)->None"
 )

 # Add a Node instance to its head
 linked_list.insert_head(Node('Hello again, world!'			)			)
 assert (
     str(_UpperCAmelCase			)
     == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
     "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None"
 )

 # Add None to its tail
 linked_list.insert_tail(_UpperCAmelCase			)
 assert (
     str(_UpperCAmelCase			)
     == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
     "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None->None"
 )

 # Reverse the linked list
 linked_list.reverse()
 assert (
     str(_UpperCAmelCase			)
     == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
     "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
 )

def 		_SCREAMING_SNAKE_CASE			():
 from doctest import testmod

 testmod()

 lowerCAmelCase    				= LinkedList()
 linked_list.insert_head(input('Inserting 1st at head '			).strip()			)
 linked_list.insert_head(input('Inserting 2nd at head '			).strip()			)
 print('\nPrint list:'			)
 linked_list.print_list()
 linked_list.insert_tail(input('\nInserting 1st at tail '			).strip()			)
 linked_list.insert_tail(input('Inserting 2nd at tail '			).strip()			)
 print('\nPrint list:'			)
 linked_list.print_list()
 print('\nDelete head'			)
 linked_list.delete_head()
 print('Delete tail'			)
 linked_list.delete_tail()
 print('\nPrint list:'			)
 linked_list.print_list()
 print('\nReverse linked list'			)
 linked_list.reverse()
 print('\nPrint list:'			)
 linked_list.print_list()
 print('\nString representation of linked list:'			)
 print(_UpperCAmelCase			)
 print('\nReading/changing Node data using indexing:'			)
 print(F'Element at Position 1: {linked_list[1]}'			)
 lowerCAmelCase    				= input('Enter New Value: '			).strip()
 print('New list:'			)
 print(_UpperCAmelCase			)
 print(F'length of linked_list is : {len(_UpperCAmelCase			)}'			)


if __name__ == "__main__":
       main()





