


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


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




def   snake_case		(     UpperCamelCase__       :						Optional[Any]			,				UpperCamelCase__       :						Optional[Any]    )   ->      List[str]:
      return line.startswith(UpperCamelCase__    ) or len(UpperCamelCase__    ) <= 1 or re.search(R"""^\s*\)(\s*->.*:|:)\s*$"""			,				UpperCamelCase__    ) is not None




def   snake_case		(     UpperCamelCase__       :						Any    )   ->      Optional[int]:
      lowerCamelCase					:					Dict        =	object_name.split("""."""    )
      lowerCamelCase					:					Union[str, Any]        =	0

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

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

      # Now let's find the class / func in the code!
      lowerCamelCase					:					List[Any]        =	""""""
      lowerCamelCase					:					Union[str, Any]        =	0
      for name in parts[i + 1 :]:
            while (
                line_index < len(UpperCamelCase__    ) 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(UpperCamelCase__    ):
            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					:					str        =	line_index
      while line_index < len(UpperCamelCase__    ) and _should_continue(lines[line_index]			,				UpperCamelCase__    ):
            line_index += 1
      # Clean up empty lines at the end (if any).
      while len(lines[line_index - 1]    ) <= 1:
            line_index -= 1

      lowerCamelCase					:					Optional[Any]        =	lines[start_index:line_index]
      return "".join(UpperCamelCase__    )


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




def   snake_case		(     UpperCamelCase__       :						Any    )   ->      Union[str, Any]:
      lowerCamelCase					:					Optional[Any]        =	code.split("""\n"""    )
      lowerCamelCase					:					Any        =	0
      while idx < len(UpperCamelCase__    ) and len(lines[idx]    ) == 0:
            idx += 1
      if idx < len(UpperCamelCase__    ):
            return re.search(R"""^(\s*)\S"""			,				lines[idx]    ).groups()[0]
      return ""




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




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

            lowerCamelCase					:					Dict        =	line_index + 1 if indent == theoretical_indent else line_index + 2
            lowerCamelCase					:					Optional[Any]        =	theoretical_indent
            lowerCamelCase					:					int        =	start_index

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

            lowerCamelCase					:					Any        =	lines[start_index:line_index]
            lowerCamelCase					:					Any        =	"""""".join(UpperCamelCase__    )

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

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

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

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




def   snake_case		(     UpperCamelCase__       :						bool = False    )   ->      Tuple:
      lowerCamelCase					:					int        =	glob.glob(os.path.join(UpperCamelCase__			,				"""**/*.py"""    )			,				recursive=UpperCamelCase__    )
      lowerCamelCase					:					List[str]        =	[]
      for filename in all_files:
            lowerCamelCase					:					Any        =	is_copy_consistent(UpperCamelCase__			,				UpperCamelCase__    )
            diffs += [F'- {filename}: copy does not match {d[0]} at line {d[1]}' for d in new_diffs]
      if not overwrite and len(UpperCamelCase__    ) > 0:
            lowerCamelCase					:					Tuple        =	"""\n""".join(UpperCamelCase__    )
            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      :Optional[int]	    =		argparse.ArgumentParser()
    parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
    __lowerCamelCase      :str	    =		parser.parse_args()

    check_copies(args.fix_and_overwrite)








"""simple docstring"""


from typing import List, Optional, Union

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


__lowerCamelCase      :str	    =		logging.get_logger(__name__)

__lowerCamelCase      :Any	    =		{
    'huggingface/time-series-transformer-tourism-monthly': (
        'https://huggingface.co/huggingface/time-series-transformer-tourism-monthly/resolve/main/config.json'
    ),
    # See all TimeSeriesTransformer models at https://huggingface.co/models?filter=time_series_transformer
}


class 			A__	(						__lowercase):


     """simple docstring"""
     snake_case__	:					List[Any]													='''time_series_transformer'''
     snake_case__	:					List[Any]													={
         '''hidden_size''': '''d_model''',
         '''num_attention_heads''': '''encoder_attention_heads''',
         '''num_hidden_layers''': '''encoder_layers''',
     }

     def __init__(	self:						List[str]     ,		__a:						Optional[int] = None     ,		__a:						Optional[int] = None     ,		__a:						str = "student_t"     ,		__a:						str = "nll"     ,		__a:						int = 1     ,		__a:						List[int] = [1, 2, 3, 4, 5, 6, 7]     ,		__a:						Optional[Union[str, bool]] = "mean"     ,		__a:						int = 0     ,		__a:						int = 0     ,		__a:						int = 0     ,		__a:						int = 0     ,		__a:						Optional[List[int]] = None     ,		__a:						Optional[List[int]] = None     ,		__a:						int = 32     ,		__a:						int = 32     ,		__a:						int = 2     ,		__a:						int = 2     ,		__a:						int = 2     ,		__a:						int = 2     ,		__a:						bool = True     ,		__a:						str = "gelu"     ,		__a:						int = 64     ,		__a:						float = 0.1     ,		__a:						float = 0.1     ,		__a:						float = 0.1     ,		__a:						float = 0.1     ,		__a:						float = 0.1     ,		__a:						int = 100     ,		__a:						float = 0.02     ,		__a:						Tuple=True     ,		**__a:						str     ,		)->    Any:
           # time series specific configuration
           lowerCamelCase					:					str        =	prediction_length
           lowerCamelCase					:					Optional[Any]        =	context_length or prediction_length
           lowerCamelCase					:					Tuple        =	distribution_output
           lowerCamelCase					:					Any        =	loss
           lowerCamelCase					:					List[Any]        =	input_size
           lowerCamelCase					:					int        =	num_time_features
           lowerCamelCase					:					Dict        =	lags_sequence
           lowerCamelCase					:					Optional[int]        =	scaling
           lowerCamelCase					:					int        =	num_dynamic_real_features
           lowerCamelCase					:					Tuple        =	num_static_real_features
           lowerCamelCase					:					Any        =	num_static_categorical_features
           if cardinality and num_static_categorical_features > 0:
                 if len(__a	) != num_static_categorical_features:
                       raise ValueError(
                           """The cardinality should be a list of the same length as `num_static_categorical_features`"""	)
                 lowerCamelCase					:					int        =	cardinality
           else:
                 lowerCamelCase					:					Dict        =	[0]
           if embedding_dimension and num_static_categorical_features > 0:
                 if len(__a	) != num_static_categorical_features:
                       raise ValueError(
                           """The embedding dimension should be a list of the same length as `num_static_categorical_features`"""	)
                 lowerCamelCase					:					str        =	embedding_dimension
           else:
                 lowerCamelCase					:					str        =	[min(50     ,		(cat + 1) // 2	) for cat in self.cardinality]
           lowerCamelCase					:					Any        =	num_parallel_samples

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

           lowerCamelCase					:					Optional[int]        =	dropout
           lowerCamelCase					:					List[str]        =	attention_dropout
           lowerCamelCase					:					Tuple        =	activation_dropout
           lowerCamelCase					:					Optional[int]        =	encoder_layerdrop
           lowerCamelCase					:					int        =	decoder_layerdrop

           lowerCamelCase					:					Optional[int]        =	activation_function
           lowerCamelCase					:					Optional[Any]        =	init_std

           lowerCamelCase					:					Optional[Any]        =	use_cache

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







     @property
     def 		a__						(	self:						int	)->    int:
           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
           )




