






"""simple docstring"""



import argparse
import glob
import importlib.util
import os
import re

import black
from doc_builder.style_doc import style_docstrings_in_code


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
A__			:							Tuple					   =   'src/diffusers'
A__			:							Tuple					   =   '.'


# This is to make sure the diffusers module imported is the one in the repo.
A__			:							Dict					   =   importlib.util.spec_from_file_location(
    'diffusers',
    os.path.join(DIFFUSERS_PATH, '__init__.py'),
    submodule_search_locations=[DIFFUSERS_PATH],
)
A__			:							Optional[Any]					   =   spec.loader.load_module()

def 					_snake_case							(	lowerCamelCase__      :       Union[str, Any]							,		lowerCamelCase__      :       Optional[int]    )							->      Any:
							return line.startswith(lowerCamelCase__    ) or len(lowerCamelCase__    ) <= 1 or re.search(r"^\s*\)(\s*->.*:|:)\s*$"							,		lowerCamelCase__    ) is not None

def 					_snake_case							(	lowerCamelCase__      :       str    )							->      Optional[int]:
							lowerCamelCase_			:				Tuple										=object_name.split("."    )
							lowerCamelCase_			:				List[str]										=0

							# First let's find the module where our object lives.
							lowerCamelCase_			:				Any										=parts[i]
							while i < len(lowerCamelCase__    ) and not os.path.isfile(os.path.join(lowerCamelCase__							,		F"""{module}.py"""    )    ):
														i += 1
														if i < len(lowerCamelCase__    ):
																					lowerCamelCase_			:				Any										=os.path.join(lowerCamelCase__							,		parts[i]    )
							if i >= len(lowerCamelCase__    ):
														raise ValueError(F"""`object_name` should begin with the name of a module of diffusers but got {object_name}."""    )

							with open(os.path.join(lowerCamelCase__							,		F"""{module}.py"""    )							,		"r"							,		encoding="utf-8"							,		newline="\n"    ) as f:
														lowerCamelCase_			:				Optional[Any]										=f.readlines()

							# Now let's find the class / func in the code!
							lowerCamelCase_			:				Tuple										=""
							lowerCamelCase_			:				List[str]										=0
							for name in parts[i + 1 :]:
														while (
														    line_index < len(lowerCamelCase__    ) and re.search(rF"""^{indent}(class|def)\s+{name}(\(|\:)"""							,		lines[line_index]    ) is None
														):
																					line_index += 1
														indent += "    "
														line_index += 1

							if line_index >= len(lowerCamelCase__    ):
														raise ValueError(F""" {object_name} does not match any function or class in {module}."""    )

							# We found the beginning of the class / func, now let's find the end (when the indent diminishes).
							lowerCamelCase_			:				List[Any]										=line_index
							while line_index < len(lowerCamelCase__    ) and _should_continue(lines[line_index]							,		lowerCamelCase__    ):
														line_index += 1
							# Clean up empty lines at the end (if any).
							while len(lines[line_index - 1]    ) <= 1:
														line_index -= 1

							lowerCamelCase_			:				Optional[int]										=lines[start_index:line_index]
							return "".join(lowerCamelCase__    )


A__			:							Optional[int]					   =   re.compile(r'^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)')
A__			:							Any					   =   re.compile(r'^\s*(\S+)->(\S+)(\s+.*|$)')
A__			:							str					   =   re.compile(r'<FILL\s+[^>]*>')

def 					_snake_case							(	lowerCamelCase__      :       List[Any]    )							->      int:
							lowerCamelCase_			:				List[Any]										=code.split("\n"    )
							lowerCamelCase_			:				Union[str, Any]										=0
							while idx < len(lowerCamelCase__    ) and len(lines[idx]    ) == 0:
														idx += 1
							if idx < len(lowerCamelCase__    ):
														return re.search(r"^(\s*)\S"							,		lines[idx]    ).groups()[0]
							return ""

def 					_snake_case							(	lowerCamelCase__      :       List[str]    )							->      Optional[int]:
							lowerCamelCase_			:				List[str]										=len(get_indent(lowerCamelCase__    )    ) > 0
							if has_indent:
														lowerCamelCase_			:				List[str]										=F"""class Bla:\n{code}"""
							lowerCamelCase_			:				Dict										=black.Mode(target_versions={black.TargetVersion.PYaa}							,		line_length=119							,		preview=lowerCamelCase__    )
							lowerCamelCase_			:				List[Any]										=black.format_str(lowerCamelCase__							,		mode=lowerCamelCase__    )
							lowerCamelCase_				,		lowerCamelCase_			:				Union[str, Any]										=style_docstrings_in_code(lowerCamelCase__    )
							return result[len("class Bla:\n"    ) :] if has_indent else result

def 					_snake_case							(	lowerCamelCase__      :       Union[str, Any]							,		lowerCamelCase__      :       Any=False    )							->      Any:




							with open(lowerCamelCase__							,		"r"							,		encoding="utf-8"							,		newline="\n"    ) as f:
														lowerCamelCase_			:				List[str]										=f.readlines()
							lowerCamelCase_			:				Any										=[]
							lowerCamelCase_			:				Optional[int]										=0
							# Not a for loop cause `lines` is going to change (if `overwrite=True`).
							while line_index < len(lowerCamelCase__    ):
														lowerCamelCase_			:				List[Any]										=_re_copy_warning.search(lines[line_index]    )
														if search is None:
																					line_index += 1
																					continue

														# There is some copied code here, let's retrieve the original.
														lowerCamelCase_				,		lowerCamelCase_				,		lowerCamelCase_			:				Dict										=search.groups()
														lowerCamelCase_			:				Optional[int]										=find_code_in_diffusers(lowerCamelCase__    )
														lowerCamelCase_			:				Tuple										=get_indent(lowerCamelCase__    )

														lowerCamelCase_			:				Any										=line_index + 1 if indent == theoretical_indent else line_index + 2
														lowerCamelCase_			:				Tuple										=theoretical_indent
														lowerCamelCase_			:				List[str]										=start_index

														# Loop to check the observed code, stop when indentation diminishes or if we see a End copy comment.
														lowerCamelCase_			:				List[Any]										=True
														while line_index < len(lowerCamelCase__    ) and should_continue:
																					line_index += 1
																					if line_index >= len(lowerCamelCase__    ):
																												break
																					lowerCamelCase_			:				List[str]										=lines[line_index]
																					lowerCamelCase_			:				Dict										=_should_continue(lowerCamelCase__							,		lowerCamelCase__    ) and re.search(F"""^{indent}# End copy"""							,		lowerCamelCase__    ) is None
														# Clean up empty lines at the end (if any).
														while len(lines[line_index - 1]    ) <= 1:
																					line_index -= 1

														lowerCamelCase_			:				Tuple										=lines[start_index:line_index]
														lowerCamelCase_			:				Optional[Any]										="".join(lowerCamelCase__    )

														# Remove any nested `Copied from` comments to avoid circular copies
														lowerCamelCase_			:				int										=[line for line in theoretical_code.split("\n"    ) if _re_copy_warning.search(lowerCamelCase__    ) is None]
														lowerCamelCase_			:				Any										="\n".join(lowerCamelCase__    )

														# Before comparing, use the `replace_pattern` on the original code.
														if len(lowerCamelCase__    ) > 0:
																					lowerCamelCase_			:				str										=replace_pattern.replace("with"							,		""    ).split(","    )
																					lowerCamelCase_			:				Optional[int]										=[_re_replace_pattern.search(lowerCamelCase__    ) for p in patterns]
																					for pattern in patterns:
																												if pattern is None:
																																			continue
																												lowerCamelCase_				,		lowerCamelCase_				,		lowerCamelCase_			:				Optional[Any]										=pattern.groups()
																												lowerCamelCase_			:				List[str]										=re.sub(lowerCamelCase__							,		lowerCamelCase__							,		lowerCamelCase__    )
																												if option.strip() == "all-casing":
																																			lowerCamelCase_			:				Optional[int]										=re.sub(obja.lower()							,		obja.lower()							,		lowerCamelCase__    )
																																			lowerCamelCase_			:				str										=re.sub(obja.upper()							,		obja.upper()							,		lowerCamelCase__    )

            # Blackify after replacement. To be able to do that, we need the header (class or function definition)
            # from the previous line
																					lowerCamelCase_			:				int										=blackify(lines[start_index - 1] + theoretical_code    )
																					lowerCamelCase_			:				Any										=theoretical_code[len(lines[start_index - 1]    ) :]

														# Test for a diff and act accordingly.
														if observed_code != theoretical_code:
																					diffs.append([object_name, start_index]    )
																					if overwrite:
																												lowerCamelCase_			:				int										=lines[:start_index] + [theoretical_code] + lines[line_index:]
																												lowerCamelCase_			:				Any										=start_index + 1

							if overwrite and len(lowerCamelCase__    ) > 0:
														# Warn the user a file has been modified.
														print(F"""Detected changes, rewriting {filename}."""    )
														with open(lowerCamelCase__							,		"w"							,		encoding="utf-8"							,		newline="\n"    ) as f:
																					f.writelines(lowerCamelCase__    )
							return diffs

def 					_snake_case							(	lowerCamelCase__      :       bool = False    )							->      Optional[Any]:
							lowerCamelCase_			:				Dict										=glob.glob(os.path.join(lowerCamelCase__							,		"**/*.py"    )							,		recursive=lowerCamelCase__    )
							lowerCamelCase_			:				Any										=[]
							for filename in all_files:
														lowerCamelCase_			:				Optional[Any]										=is_copy_consistent(lowerCamelCase__							,		lowerCamelCase__    )
														diffs += [F"""- {filename}: copy does not match {d[0]} at line {d[1]}""" for d in new_diffs]
							if not overwrite and len(lowerCamelCase__    ) > 0:
														lowerCamelCase_			:				Optional[Any]										="\n".join(lowerCamelCase__    )
														raise Exception(
														    "Found the following copy inconsistencies:\n"
														    + diff
														    + "\nRun `make fix-copies` or `python utils/check_copies.py --fix_and_overwrite` to fix them."    )


if __name__ == "__main__":
						A__			:							Tuple					   =   argparse.ArgumentParser()
						parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
						A__			:							str					   =   parser.parse_args()

						check_copies(args.fix_and_overwrite)





"""simple docstring"""

import functools
import operator

from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_            =    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_            =    {
    '''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json''',
    # See all SEW-D models at https://huggingface.co/models?filter=sew-d
}
class   _UpperCAmelCase				(		SCREAMING_SNAKE_CASE_				):
      __SCREAMING_SNAKE_CASE :				List[str]				   =						"sew-d"




      def __init__(				self ,							lowercase_=3_2 ,							lowercase_=7_6_8 ,							lowercase_=1_2 ,							lowercase_=1_2 ,							lowercase_=3_0_7_2 ,							lowercase_=2 ,							lowercase_=5_1_2 ,							lowercase_=2_5_6 ,							lowercase_=True ,							lowercase_=True ,							lowercase_=("p2c", "c2p") ,							lowercase_="layer_norm" ,							lowercase_="gelu_python" ,							lowercase_=0.1 ,							lowercase_=0.1 ,							lowercase_=0.1 ,							lowercase_=0.0 ,							lowercase_=0.1 ,							lowercase_=0.0_2 ,							lowercase_=1E-7 ,							lowercase_=1E-5 ,							lowercase_="group" ,							lowercase_="gelu" ,							lowercase_=(6_4, 1_2_8, 1_2_8, 1_2_8, 1_2_8, 2_5_6, 2_5_6, 2_5_6, 2_5_6, 5_1_2, 5_1_2, 5_1_2, 5_1_2) ,							lowercase_=(5, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1) ,							lowercase_=(1_0, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1) ,							lowercase_=False ,							lowercase_=1_2_8 ,							lowercase_=1_6 ,							lowercase_=True ,							lowercase_=0.0_5 ,							lowercase_=1_0 ,							lowercase_=2 ,							lowercase_=0.0 ,							lowercase_=1_0 ,							lowercase_=0 ,							lowercase_="mean" ,							lowercase_=False ,							lowercase_=False ,							lowercase_=2_5_6 ,							lowercase_=0 ,							lowercase_=1 ,							lowercase_=2 ,							**lowercase_ ,							)    ->       Dict:
          super().__init__(**lowercase_ ,							pad_token_id=lowercase_ ,							bos_token_id=lowercase_ ,							eos_token_id=lowercase_				)
          UpperCAmelCase          =       hidden_size
          UpperCAmelCase          =       feat_extract_norm
          UpperCAmelCase          =       feat_extract_activation
          UpperCAmelCase          =       list(lowercase_				)
          UpperCAmelCase          =       list(lowercase_				)
          UpperCAmelCase          =       list(lowercase_				)
          UpperCAmelCase          =       conv_bias
          UpperCAmelCase          =       num_conv_pos_embeddings
          UpperCAmelCase          =       num_conv_pos_embedding_groups
          UpperCAmelCase          =       len(self.conv_dim				)
          UpperCAmelCase          =       num_hidden_layers
          UpperCAmelCase          =       intermediate_size
          UpperCAmelCase          =       squeeze_factor
          UpperCAmelCase          =       max_position_embeddings
          UpperCAmelCase          =       position_buckets
          UpperCAmelCase          =       share_att_key
          UpperCAmelCase          =       relative_attention
          UpperCAmelCase          =       norm_rel_ebd
          UpperCAmelCase          =       list(lowercase_				)
          UpperCAmelCase          =       hidden_act
          UpperCAmelCase          =       num_attention_heads
          UpperCAmelCase          =       hidden_dropout
          UpperCAmelCase          =       attention_dropout
          UpperCAmelCase          =       activation_dropout
          UpperCAmelCase          =       feat_proj_dropout
          UpperCAmelCase          =       final_dropout
          UpperCAmelCase          =       layer_norm_eps
          UpperCAmelCase          =       feature_layer_norm_eps
          UpperCAmelCase          =       initializer_range
          UpperCAmelCase          =       vocab_size

          if (
              (len(self.conv_stride				) != self.num_feat_extract_layers)
              or (len(self.conv_kernel				) != self.num_feat_extract_layers)
              or (len(self.conv_dim				) != self.num_feat_extract_layers)
          ):
              raise ValueError(
                  'Configuration for convolutional layers is incorrect.'
                  'It is required that `len(config.conv_dim)` == `len(config.conv_stride)` == `len(config.conv_kernel)`,'
                  F"but is `len(config.conv_dim) = {len(self.conv_dim				)}`, `len(config.conv_stride)"
                  F"= {len(self.conv_stride				)}`, `len(config.conv_kernel) = {len(self.conv_kernel				)}`."				)

          # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
          UpperCAmelCase          =       apply_spec_augment
          UpperCAmelCase          =       mask_time_prob
          UpperCAmelCase          =       mask_time_length
          UpperCAmelCase          =       mask_time_min_masks
          UpperCAmelCase          =       mask_feature_prob
          UpperCAmelCase          =       mask_feature_length
          UpperCAmelCase          =       mask_feature_min_masks

          # ctc loss
          UpperCAmelCase          =       ctc_loss_reduction
          UpperCAmelCase          =       ctc_zero_infinity

          # sequence classification
          UpperCAmelCase          =       use_weighted_layer_sum
          UpperCAmelCase          =       classifier_proj_size




      @property
      def      a_   (				self				)    ->       Tuple:
          return functools.reduce(operator.mul ,							self.conv_stride ,							1				)



