



"""simple docstring"""


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

				snake_case_    					=	True
except ImportError:
				snake_case_    					=	False

snake_case_    					=	logging.get_logger(__name__)  # pylint: disable=invalid-name

def 			_lowerCAmelCase				(       lowercase_						):
						return AddNewModelCommand(args.testing		,     args.testing_file		,     path=args.path						)







class 				A_      (					SCREAMING_SNAKE_CASE_    ):



						"""simple docstring"""






						@staticmethod
						def      UpperCAmelCase__					( lowercase_			:ArgumentParser )    ->      Any:
												UpperCAmelCase					=			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=lowercase_       ,  help='Configuration file on which to run.' )
												add_new_model_parser.add_argument(
												    '--path'       ,  type=lowercase_       ,  help='Path to cookiecutter. Should only be used for testing purposes.' )
												add_new_model_parser.set_defaults(func=lowercase_ )






						def __init__( self			:Tuple       ,  lowercase_			:bool       ,  lowercase_			:str       ,  lowercase_			:List[str]=None       ,  *lowercase_			:List[str] )    ->      List[Any]:
												UpperCAmelCase					=			testing
												UpperCAmelCase					=			testing_file
												UpperCAmelCase					=			path






						def      UpperCAmelCase__					( self			:Any )    ->      str:
												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
												UpperCAmelCase					=			[directory for directory in os.listdir() if 'cookiecutter-template-' == directory[:22]]
												if len(lowercase_ ) > 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.' )

												UpperCAmelCase					=			(
												    Path(lowercase_ ).parent.parent.parent.parent if self._path is None else Path(self._path ).parent.parent
												)
												UpperCAmelCase					=			path_to_transformer_root / 'templates' / 'adding_a_new_model'

												# Execute cookiecutter
												if not self._testing:
																		cookiecutter(str(lowercase_ ) )
												else:
																		with open(self._testing_file       ,  'r' ) as configuration_file:
																								UpperCAmelCase					=			json.load(lowercase_ )

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

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

												# Retrieve configuration
												with open(directory + '/configuration.json'       ,  'r' ) as configuration_file:
																		UpperCAmelCase					=			json.load(lowercase_ )

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

												UpperCAmelCase					=			'PyTorch' in generate_tensorflow_pytorch_and_flax
												UpperCAmelCase					=			'TensorFlow' in generate_tensorflow_pytorch_and_flax
												UpperCAmelCase					=			'Flax' in generate_tensorflow_pytorch_and_flax

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

												# 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(lowercase_			:Optional[Any] ):
																		with open(lowercase_       ,  'r' ) as f:
																								UpperCAmelCase					=			f.readlines()
																		with open(lowercase_       ,  'w' ) as f:
																								for line in lines:
																														if "# Copied from transformers." not in line:
																																				f.write(lowercase_ )

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

																		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(lowercase_       ,  lowercase_ )
																		# Remove original file
																		remove(lowercase_ )
																		# Move new file
																		move(lowercase_       ,  lowercase_ )

												def skip_units(lowercase_			:Optional[int] ):
																		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(lowercase_			:int ):
																		with open(lowercase_ ) as datafile:
																								UpperCAmelCase					=			[]
																								UpperCAmelCase					=			False
																								UpperCAmelCase					=			False
																								for line in datafile:
																														if "# To replace in: " in line and "##" not in line:
																																				UpperCAmelCase					=			line.split('"' )[1]
																																				UpperCAmelCase					=			skip_units(lowercase_ )
																														elif "# Below: " in line and "##" not in line:
																																				UpperCAmelCase					=			line.split('"' )[1]
																																				UpperCAmelCase					=			skip_units(lowercase_ )
																														elif "# End." in line and "##" not in line:
																																				if not skip_file and not skip_snippet:
																																										replace(lowercase_       ,  lowercase_       ,  lowercase_ )

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

																		remove(lowercase_ )

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










"""simple docstring"""


import re

import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey

from ..utils import logging


snake_case_    					=	logging.get_logger(__name__)

def 			_lowerCAmelCase				(       lowercase_						):
						UpperCAmelCase					=			R'\w+[.]\d+'
						UpperCAmelCase					=			re.findall(lowercase_		,     lowercase_						)
						for pat in pats:
												UpperCAmelCase					=			key.replace(lowercase_		,     '_'.join(pat.split('.'						)						)						)
						return key

def 			_lowerCAmelCase				(       lowercase_		,     lowercase_		,     lowercase_						):
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('scale',)
						if (
						    any('norm' in str_ for str_ in pt_tuple_key						)
						    and (pt_tuple_key[-1] == "bias")
						    and (pt_tuple_key[:-1] + ("bias",) not in random_flax_state_dict)
						    and (pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict)
						):
												UpperCAmelCase					=			pt_tuple_key[:-1] + ('scale',)
												return renamed_pt_tuple_key, pt_tensor
						elif pt_tuple_key[-1] in ["weight", "gamma"] and pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict:
												UpperCAmelCase					=			pt_tuple_key[:-1] + ('scale',)
												return renamed_pt_tuple_key, pt_tensor

						# embedding
						if pt_tuple_key[-1] == "weight" and pt_tuple_key[:-1] + ("embedding",) in random_flax_state_dict:
												UpperCAmelCase					=			pt_tuple_key[:-1] + ('embedding',)
												return renamed_pt_tuple_key, pt_tensor

						# conv layer
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('kernel',)
						if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
												UpperCAmelCase					=			pt_tensor.transpose(2		,     3		,     1		,     0						)
												return renamed_pt_tuple_key, pt_tensor

						# linear layer
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('kernel',)
						if pt_tuple_key[-1] == "weight":
												UpperCAmelCase					=			pt_tensor.T
												return renamed_pt_tuple_key, pt_tensor

						# old PyTorch layer norm weight
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('weight',)
						if pt_tuple_key[-1] == "gamma":
												return renamed_pt_tuple_key, pt_tensor

						# old PyTorch layer norm bias
						UpperCAmelCase					=			pt_tuple_key[:-1] + ('bias',)
						if pt_tuple_key[-1] == "beta":
												return renamed_pt_tuple_key, pt_tensor

						return pt_tuple_key, pt_tensor






def 			_lowerCAmelCase				(       lowercase_		,     lowercase_		,     lowercase_=42						):
						# Step 1: Convert pytorch tensor to numpy
						UpperCAmelCase					=			{k: v.numpy() for k, v in pt_state_dict.items()}

						# Step 2: Since the model is stateless, get random Flax params
						UpperCAmelCase					=			flax_model.init_weights(PRNGKey(lowercase_						)						)

						UpperCAmelCase					=			flatten_dict(lowercase_						)
						UpperCAmelCase					=			{}

						# Need to change some parameters name to match Flax names
						for pt_key, pt_tensor in pt_state_dict.items():
												UpperCAmelCase					=			rename_key(lowercase_						)
												UpperCAmelCase					=			tuple(renamed_pt_key.split('.'						)						)

												# Correctly rename weight parameters
												UpperCAmelCase				,   UpperCAmelCase					=			rename_key_and_reshape_tensor(lowercase_		,     lowercase_		,     lowercase_						)

												if flax_key in random_flax_state_dict:
																		if flax_tensor.shape != random_flax_state_dict[flax_key].shape:
																								raise ValueError(
																								    F"""PyTorch checkpoint seems to be incorrect. Weight {pt_key} was expected to be of shape """
																								    F"""{random_flax_state_dict[flax_key].shape}, but is {flax_tensor.shape}."""						)

        # also add unexpected weight so that warning is thrown
												UpperCAmelCase					=			jnp.asarray(lowercase_						)

						return unflatten_dict(lowercase_						)





