import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List

from ..utils import logging
from . import BaseTransformersCLICommand


try:
  from cookiecutter.main import cookiecutter

  SCREAMING_SNAKE_CASE :	List[Any]							     =		True
except ImportError:
  SCREAMING_SNAKE_CASE :	Dict							     =		False

SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		logging.get_logger(__name__)  # pylint: disable=invalid-name



def   __A		(			_A					):



 """simple docstring"""


 return AddNewModelCommand(args.testing							,				args.testing_file							,				path=args.path					)






class    A_ (       a_ ):

  @staticmethod
  def 		_UpperCAmelCase   (		__SCREAMING_SNAKE_CASE :      ArgumentParser       ):
   __a       =  parser.add_parser("add-new-model"       )
   add_new_model_parser.add_argument("--testing"     ,							action="store_true"     ,							help="If in testing mode."       )
   add_new_model_parser.add_argument("--testing_file"     ,							type=__SCREAMING_SNAKE_CASE     ,							help="Configuration file on which to run."       )
   add_new_model_parser.add_argument(
       "--path"     ,							type=__SCREAMING_SNAKE_CASE     ,							help="Path to cookiecutter. Should only be used for testing purposes."       )
   add_new_model_parser.set_defaults(func=__SCREAMING_SNAKE_CASE       )

  def __init__(		self :      Any     ,							__SCREAMING_SNAKE_CASE :      bool     ,							__SCREAMING_SNAKE_CASE :      str     ,							__SCREAMING_SNAKE_CASE :      List[str]=None     ,							*__SCREAMING_SNAKE_CASE :      Optional[int]       ):
   __a       =  testing
   __a       =  testing_file
   __a       =  path

  def 		_UpperCAmelCase   (		self :      Union[str, Any]       ):
   warnings.warn(
       "The command `transformers-cli add-new-model` is deprecated and will be removed in v5 of Transformers. "
       "It is not actively maintained anymore, so might give a result that won't pass all tests and quality "
       "checks, you should use `transformers-cli add-new-model-like` instead."       )
   if not _has_cookiecutter:
    raise ImportError(
        "Model creation dependencies are required to use the `add_new_model` command. Install them by running "
        "the following at the root of your `transformers` clone:\n\n\t$ pip install -e .[modelcreation]\n"       )
   # Ensure that there is no other `cookiecutter-template-xxx` directory in the current working directory
   __a       =  [directory for directory in os.listdir() if "cookiecutter-template-" == directory[:22]]
   if len(__SCREAMING_SNAKE_CASE       ) > 0:
    raise ValueError(
        "Several directories starting with `cookiecutter-template-` in current working directory. "
        "Please clean your directory by removing all folders starting with `cookiecutter-template-` or "
        "change your working directory."       )

   __a       =  (
       Path(__SCREAMING_SNAKE_CASE       ).parent.parent.parent.parent if self._path is None else Path(self._path       ).parent.parent
   )
   __a       =  path_to_transformer_root / "templates" / "adding_a_new_model"

   # Execute cookiecutter
   if not self._testing:
    cookiecutter(str(__SCREAMING_SNAKE_CASE       )       )
   else:
    with open(self._testing_file     ,							"r"       ) as configuration_file:
     __a       =  json.load(__SCREAMING_SNAKE_CASE       )

    cookiecutter(
        str(path_to_cookiecutter if self._path is None else self._path       )     ,							no_input=__SCREAMING_SNAKE_CASE     ,							extra_context=__SCREAMING_SNAKE_CASE     ,							)

   __a       =  [directory for directory in os.listdir() if "cookiecutter-template-" in directory[:22]][0]

   # Retrieve configuration
   with open(directory + "/configuration.json"     ,							"r"       ) as configuration_file:
    __a       =  json.load(__SCREAMING_SNAKE_CASE       )

   __a       =  configuration["lowercase_modelname"]
   __a       =  configuration["generate_tensorflow_pytorch_and_flax"]
   os.remove(f"""{directory}/configuration.json"""       )

   __a       =  "PyTorch" in generate_tensorflow_pytorch_and_flax
   __a       =  "TensorFlow" in generate_tensorflow_pytorch_and_flax
   __a       =  "Flax" in generate_tensorflow_pytorch_and_flax

   __a       =  f"""{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}"""
   os.makedirs(__SCREAMING_SNAKE_CASE     ,							exist_ok=__SCREAMING_SNAKE_CASE       )
   os.makedirs(f"""{path_to_transformer_root}/tests/models/{lowercase_model_name}"""     ,							exist_ok=__SCREAMING_SNAKE_CASE       )

   # Tests require submodules as they have parent imports
   with open(f"""{path_to_transformer_root}/tests/models/{lowercase_model_name}/__init__.py"""     ,							"w"       ):
    pass

   shutil.move(
       f"""{directory}/__init__.py"""     ,							f"""{model_dir}/__init__.py"""     ,							)
   shutil.move(
       f"""{directory}/configuration_{lowercase_model_name}.py"""     ,							f"""{model_dir}/configuration_{lowercase_model_name}.py"""     ,							)

   def remove_copy_lines(__SCREAMING_SNAKE_CASE :      List[Any]       ):
    with open(__SCREAMING_SNAKE_CASE     ,							"r"       ) as f:
     __a       =  f.readlines()
    with open(__SCREAMING_SNAKE_CASE     ,							"w"       ) as f:
     for line in lines:
      if "# Copied from transformers." not in line:
       f.write(__SCREAMING_SNAKE_CASE       )

   if output_pytorch:
    if not self._testing:
     remove_copy_lines(f"""{directory}/modeling_{lowercase_model_name}.py"""       )

    shutil.move(
        f"""{directory}/modeling_{lowercase_model_name}.py"""     ,							f"""{model_dir}/modeling_{lowercase_model_name}.py"""     ,							)

    shutil.move(
        f"""{directory}/test_modeling_{lowercase_model_name}.py"""     ,							f"""{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_{lowercase_model_name}.py"""     ,							)
   else:
    os.remove(f"""{directory}/modeling_{lowercase_model_name}.py"""       )
    os.remove(f"""{directory}/test_modeling_{lowercase_model_name}.py"""       )

   if output_tensorflow:
    if not self._testing:
     remove_copy_lines(f"""{directory}/modeling_tf_{lowercase_model_name}.py"""       )

    shutil.move(
        f"""{directory}/modeling_tf_{lowercase_model_name}.py"""     ,							f"""{model_dir}/modeling_tf_{lowercase_model_name}.py"""     ,							)

    shutil.move(
        f"""{directory}/test_modeling_tf_{lowercase_model_name}.py"""     ,							f"""{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_tf_{lowercase_model_name}.py"""     ,							)
   else:
    os.remove(f"""{directory}/modeling_tf_{lowercase_model_name}.py"""       )
    os.remove(f"""{directory}/test_modeling_tf_{lowercase_model_name}.py"""       )

   if output_flax:
    if not self._testing:
     remove_copy_lines(f"""{directory}/modeling_flax_{lowercase_model_name}.py"""       )

    shutil.move(
        f"""{directory}/modeling_flax_{lowercase_model_name}.py"""     ,							f"""{model_dir}/modeling_flax_{lowercase_model_name}.py"""     ,							)

    shutil.move(
        f"""{directory}/test_modeling_flax_{lowercase_model_name}.py"""     ,							f"""{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_flax_{lowercase_model_name}.py"""     ,							)
   else:
    os.remove(f"""{directory}/modeling_flax_{lowercase_model_name}.py"""       )
    os.remove(f"""{directory}/test_modeling_flax_{lowercase_model_name}.py"""       )

   shutil.move(
       f"""{directory}/{lowercase_model_name}.md"""     ,							f"""{path_to_transformer_root}/docs/source/en/model_doc/{lowercase_model_name}.md"""     ,							)

   shutil.move(
       f"""{directory}/tokenization_{lowercase_model_name}.py"""     ,							f"""{model_dir}/tokenization_{lowercase_model_name}.py"""     ,							)

   shutil.move(
       f"""{directory}/tokenization_fast_{lowercase_model_name}.py"""     ,							f"""{model_dir}/tokenization_{lowercase_model_name}_fast.py"""     ,							)

   from os import fdopen, remove
   from shutil import copymode, move
   from tempfile import mkstemp

   def replace(__SCREAMING_SNAKE_CASE :      str     ,							__SCREAMING_SNAKE_CASE :      str     ,							__SCREAMING_SNAKE_CASE :      List[str]       ):
    # Create temp file
    __a       ,     __a       =  mkstemp()
    __a       =  False
    with fdopen(__SCREAMING_SNAKE_CASE     ,							"w"       ) as new_file:
     with open(__SCREAMING_SNAKE_CASE       ) as old_file:
      for line in old_file:
       new_file.write(__SCREAMING_SNAKE_CASE       )
       if line_to_copy_below in line:
        __a       =  True
        for line_to_copy in lines_to_copy:
         new_file.write(__SCREAMING_SNAKE_CASE       )

    if not line_found:
     raise ValueError(f"""Line {line_to_copy_below} was not found in file."""       )

    # Copy the file permissions from the old file to the new file
    copymode(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )
    # Remove original file
    remove(__SCREAMING_SNAKE_CASE       )
    # Move new file
    move(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )

   def skip_units(__SCREAMING_SNAKE_CASE :      Any       ):
    return (
        ("generating PyTorch" in line and not output_pytorch)
        or ("generating TensorFlow" in line and not output_tensorflow)
        or ("generating Flax" in line and not output_flax)
    )

   def replace_in_files(__SCREAMING_SNAKE_CASE :      List[Any]       ):
    with open(__SCREAMING_SNAKE_CASE       ) as datafile:
     __a       =  []
     __a       =  False
     __a       =  False
     for line in datafile:
      if "# To replace in: " in line and "##" not in line:
       __a       =  line.split("\""       )[1]
       __a       =  skip_units(__SCREAMING_SNAKE_CASE       )
      elif "# Below: " in line and "##" not in line:
       __a       =  line.split("\""       )[1]
       __a       =  skip_units(__SCREAMING_SNAKE_CASE       )
      elif "# End." in line and "##" not in line:
       if not skip_file and not skip_snippet:
        replace(__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE     ,							__SCREAMING_SNAKE_CASE       )

       __a       =  []
      elif "# Replace with" in line and "##" not in line:
       __a       =  []
      elif "##" not in line:
       lines_to_copy.append(__SCREAMING_SNAKE_CASE       )

    remove(__SCREAMING_SNAKE_CASE       )

   replace_in_files(f"""{directory}/to_replace_{lowercase_model_name}.py"""       )
   os.rmdir(__SCREAMING_SNAKE_CASE       )



import unittest

from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow


if is_flax_available():
  import jax.numpy as jnp

  from transformers import FlaxXLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_flax
class    A_ (       unittest.TestCase ):

  @slow
  def 		_UpperCAmelCase   (		self :      Dict       ):
   __a       =  FlaxXLMRobertaModel.from_pretrained("xlm-roberta-base"       )
   __a       =  AutoTokenizer.from_pretrained("xlm-roberta-base"       )
   __a       =  "The dog is cute and lives in the garden house"
   __a       =  jnp.array([tokenizer.encode(__SCREAMING_SNAKE_CASE       )]       )

   __a       =  (1, 12, 7_68)  # batch_size, sequence_length, embedding_vector_dim
   __a       =  jnp.array(
       [[-0.01_01, 0.12_18, -0.08_03, 0.08_01, 0.13_27, 0.07_76, -0.12_15, 0.23_83, 0.33_38, 0.31_06, 0.03_00, 0.02_52]]       )

   __a       =  model(__SCREAMING_SNAKE_CASE       )["last_hidden_state"]
   self.assertEqual(output.shape     ,							__SCREAMING_SNAKE_CASE       )
   # compare the actual values for a slice of last dim
   self.assertTrue(jnp.allclose(output[:, :, -1]     ,							__SCREAMING_SNAKE_CASE     ,							atol=1E-3       )       )


