


"""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
_lowerCAmelCase							:    str					   =	'''src/diffusers'''
_lowerCAmelCase							:    List[Any]					   =	'''.'''


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







def        lowerCamelCase_(		_lowerCamelCase			,		_lowerCamelCase       )    ->     List[Any]:
   '''simple docstring'''





   return line.startswith(_lowerCamelCase       ) or len(_lowerCamelCase       ) <= 1 or re.search(R"^\s*\)(\s*->.*:|:)\s*$"			,		_lowerCamelCase       ) is not None







def        lowerCamelCase_(		_lowerCamelCase       )    ->     Union[str, Any]:
   '''simple docstring'''





   _lowerCamelCase   :				Any							=     object_name.split("."       )
   _lowerCamelCase   :				Tuple							=     0

   # First let's find the module where our object lives.
   _lowerCamelCase   :				Dict							=     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   :				Dict							=     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   :				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   :				Optional[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   :				int							=     lines[start_index:line_index]
   return "".join(_lowerCamelCase       )


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







def        lowerCamelCase_(		_lowerCamelCase       )    ->     Union[str, Any]:
   '''simple docstring'''





   _lowerCamelCase   :				Tuple							=     code.split("\n"       )
   _lowerCamelCase   :				Optional[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        lowerCamelCase_(		_lowerCamelCase       )    ->     Optional[int]:
   '''simple docstring'''





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







def        lowerCamelCase_(		_lowerCamelCase			,		_lowerCamelCase=False       )    ->     List[str]:
   '''simple docstring'''





   with open(_lowerCamelCase			,		"r"			,		encoding="utf-8"			,		newline="\n"       ) as f:
      _lowerCamelCase   :				Union[str, Any]							=     f.readlines()
   _lowerCamelCase   :				Tuple							=     []
   _lowerCamelCase   :				List[str]							=     0
   # Not a for loop cause `lines` is going to change (if `overwrite=True`).
   while line_index < len(_lowerCamelCase       ):
      _lowerCamelCase   :				Tuple							=     _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   :				Any							=     search.groups()
      _lowerCamelCase   :				Dict							=     find_code_in_diffusers(_lowerCamelCase       )
      _lowerCamelCase   :				Optional[int]							=     get_indent(_lowerCamelCase       )

      _lowerCamelCase   :				List[Any]							=     line_index + 1 if indent == theoretical_indent else line_index + 2
      _lowerCamelCase   :				Any							=     theoretical_indent
      _lowerCamelCase   :				Optional[Any]							=     start_index

      # Loop to check the observed code, stop when indentation diminishes or if we see a End copy comment.
      _lowerCamelCase   :				Any							=     True
      while line_index < len(_lowerCamelCase       ) and should_continue:
         line_index += 1
         if line_index >= len(_lowerCamelCase       ):
            break
         _lowerCamelCase   :				int							=     lines[line_index]
         _lowerCamelCase   :				Optional[int]							=     _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   :				Optional[int]							=     lines[start_index:line_index]
      _lowerCamelCase   :				List[Any]							=     "".join(_lowerCamelCase       )

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

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





   _lowerCamelCase   :				List[Any]							=     glob.glob(os.path.join(_lowerCamelCase			,		"**/*.py"       )			,		recursive=_lowerCamelCase       )
   _lowerCamelCase   :				Dict							=     []
   for filename in all_files:
      _lowerCamelCase   :				int							=     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[int]							=     "\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__":
  _lowerCAmelCase							:    List[str]					   =	argparse.ArgumentParser()
  parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
  _lowerCAmelCase							:    Union[str, Any]					   =	parser.parse_args()

  check_copies(args.fix_and_overwrite)



from typing import List, Optional

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


lowerCAmelCase       		=    logging.get_logger(__name__)

lowerCAmelCase       		=    {
    """huggingface/autoformer-tourism-monthly""": """https://huggingface.co/huggingface/autoformer-tourism-monthly/resolve/main/config.json""",
}




class 							lowerCamelCase   (  _UpperCamelCase ):
	_lowerCAmelCase     :		Optional[int]										=						'''autoformer'''
	_lowerCAmelCase     :		Any										=						{
	    '''hidden_size''': '''d_model''',
	    '''num_attention_heads''': '''encoder_attention_heads''',
	    '''num_hidden_layers''': '''encoder_layers''',
	}


	def __init__(    self				,     lowercase__ = None				,     lowercase__ = None				,     lowercase__ = "student_t"				,     lowercase__ = "nll"				,     lowercase__ = 1				,     lowercase__ = [1, 2, 3, 4, 5, 6, 7]				,     lowercase__ = True				,     lowercase__ = 0				,     lowercase__ = 0				,     lowercase__ = 0				,     lowercase__ = 0				,     lowercase__ = None				,     lowercase__ = None				,     lowercase__ = 6_4				,     lowercase__ = 2				,     lowercase__ = 2				,     lowercase__ = 2				,     lowercase__ = 2				,     lowercase__ = 3_2				,     lowercase__ = 3_2				,     lowercase__ = "gelu"				,     lowercase__ = 0.1				,     lowercase__ = 0.1				,     lowercase__ = 0.1				,     lowercase__ = 0.1				,     lowercase__ = 0.1				,     lowercase__ = 1_0_0				,     lowercase__ = 0.0_2				,     lowercase__ = True				,     lowercase__=True				,     lowercase__ = 1_0				,     lowercase__ = 2_5				,     lowercase__ = 3				,     **lowercase__				,     ):
							# time series specific configuration
							__UpperCAmelCase			:							Optional[int]	    =	prediction_length
							__UpperCAmelCase			:							Tuple	    =	context_length if context_length is not None else prediction_length
							__UpperCAmelCase			:							Tuple	    =	distribution_output
							__UpperCAmelCase			:							Tuple	    =	loss
							__UpperCAmelCase			:							Dict	    =	input_size
							__UpperCAmelCase			:							str	    =	num_time_features
							__UpperCAmelCase			:							str	    =	lags_sequence
							__UpperCAmelCase			:							int	    =	scaling
							__UpperCAmelCase			:							int	    =	num_dynamic_real_features
							__UpperCAmelCase			:							List[str]	    =	num_static_real_features
							__UpperCAmelCase			:							List[str]	    =	num_static_categorical_features
							if cardinality is not None and num_static_categorical_features > 0:
													if len(lowercase__) != num_static_categorical_features:
																			raise ValueError(
																			    '''The cardinality should be a list of the same length as `num_static_categorical_features`''')
													__UpperCAmelCase			:							Union[str, Any]	    =	cardinality
							else:
													__UpperCAmelCase			:							List[Any]	    =	[0]
							if embedding_dimension is not None and num_static_categorical_features > 0:
													if len(lowercase__) != num_static_categorical_features:
																			raise ValueError(
																			    '''The embedding dimension should be a list of the same length as `num_static_categorical_features`''')
													__UpperCAmelCase			:							Union[str, Any]	    =	embedding_dimension
							else:
													__UpperCAmelCase			:							int	    =	[min(5_0				,     (cat + 1) // 2) for cat in self.cardinality]
							__UpperCAmelCase			:							Tuple	    =	num_parallel_samples

							# Transformer architecture configuration
							__UpperCAmelCase			:							Dict	    =	input_size * len(self.lags_sequence) + self._number_of_features
							__UpperCAmelCase			:							Optional[int]	    =	d_model
							__UpperCAmelCase			:							List[Any]	    =	encoder_attention_heads
							__UpperCAmelCase			:							int	    =	decoder_attention_heads
							__UpperCAmelCase			:							str	    =	encoder_ffn_dim
							__UpperCAmelCase			:							int	    =	decoder_ffn_dim
							__UpperCAmelCase			:							List[Any]	    =	encoder_layers
							__UpperCAmelCase			:							Tuple	    =	decoder_layers

							__UpperCAmelCase			:							Union[str, Any]	    =	dropout
							__UpperCAmelCase			:							int	    =	attention_dropout
							__UpperCAmelCase			:							int	    =	activation_dropout
							__UpperCAmelCase			:							str	    =	encoder_layerdrop
							__UpperCAmelCase			:							Dict	    =	decoder_layerdrop

							__UpperCAmelCase			:							int	    =	activation_function
							__UpperCAmelCase			:							Optional[int]	    =	init_std

							__UpperCAmelCase			:							Optional[int]	    =	use_cache

							# Autoformer
							__UpperCAmelCase			:							str	    =	label_length
							__UpperCAmelCase			:							int	    =	moving_average
							__UpperCAmelCase			:							Optional[int]	    =	autocorrelation_factor

							super().__init__(is_encoder_decoder=lowercase__				,     **lowercase__)


	@property
	def  A(    self):
							return (
							    sum(self.embedding_dimension)
							    + self.num_dynamic_real_features
							    + self.num_time_features
							    + self.num_static_real_features
							    + self.input_size * 2  # the log1p(abs(loc)) and log(scale) features
							)

