

import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
						from PIL import Image

						from transformers import AlignProcessor, EfficientNetImageProcessor



@require_vision
class   __lowercase				( unittest.TestCase	):




			"""simple docstring"""







			def        _SCREAMING_SNAKE_CASE			( self  :     Union[str, Any]):
									SCREAMING_SNAKE_CASE_: int  		=       tempfile.mkdtemp()

									SCREAMING_SNAKE_CASE_: Dict  		=       [
									    "[UNK]",
									    "[CLS]",
									    "[SEP]",
									    "[PAD]",
									    "[MASK]",
									    "want",
									    "##want",
									    "##ed",
									    "wa",
									    "un",
									    "runn",
									    "##ing",
									    ",",
									    "low",
									    "lowest",
									]
									SCREAMING_SNAKE_CASE_: str  		=       os.path.join(self.tmpdirname   ,						VOCAB_FILES_NAMES["vocab_file"])
									with open(self.vocab_file   ,						"w"   ,						encoding="utf-8") as vocab_writer:
															vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))

									SCREAMING_SNAKE_CASE_: Any  		=       {
									    "do_resize": True,
									    "size": 20,
									    "do_center_crop": True,
									    "crop_size": 18,
									    "do_normalize": True,
									    "image_mean": [0.4814_5466, 0.457_8275, 0.4082_1073],
									    "image_std": [0.2686_2954, 0.2613_0258, 0.2757_7711],
									}
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       os.path.join(self.tmpdirname   ,						lowerCAmelCase__)
									with open(self.image_processor_file   ,						"w"   ,						encoding="utf-8") as fp:
															json.dump(lowerCAmelCase__   ,						lowerCAmelCase__)



			def        _SCREAMING_SNAKE_CASE			( self  :     List[Any]   ,						**lowerCAmelCase__  :     Optional[int]):
									return BertTokenizer.from_pretrained(self.tmpdirname   ,						**lowerCAmelCase__)



			def        _SCREAMING_SNAKE_CASE			( self  :     Optional[int]   ,						**lowerCAmelCase__  :     str):
									return BertTokenizerFast.from_pretrained(self.tmpdirname   ,						**lowerCAmelCase__)



			def        _SCREAMING_SNAKE_CASE			( self  :     List[str]   ,						**lowerCAmelCase__  :     Tuple):
									return EfficientNetImageProcessor.from_pretrained(self.tmpdirname   ,						**lowerCAmelCase__)



			def        _SCREAMING_SNAKE_CASE			( self  :     List[str]):
									shutil.rmtree(self.tmpdirname)



			def        _SCREAMING_SNAKE_CASE			( self  :     List[Any]):
									SCREAMING_SNAKE_CASE_: int  		=       [np.random.randint(255   ,						size=(3, 30, 400)   ,						dtype=np.uinta)]
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       [Image.fromarray(np.moveaxis(lowerCAmelCase__   ,						0   ,						-1)) for x in image_inputs]
									return image_inputs



			def        _SCREAMING_SNAKE_CASE			( self  :     str):
									SCREAMING_SNAKE_CASE_: Tuple  		=       self.get_tokenizer()
									SCREAMING_SNAKE_CASE_: List[Any]  		=       self.get_rust_tokenizer()
									SCREAMING_SNAKE_CASE_: List[Any]  		=       self.get_image_processor()

									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       AlignProcessor(tokenizer=lowerCAmelCase__   ,						image_processor=lowerCAmelCase__)
									processor_slow.save_pretrained(self.tmpdirname)
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       AlignProcessor.from_pretrained(self.tmpdirname   ,						use_fast=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: List[Any]  		=       AlignProcessor(tokenizer=lowerCAmelCase__   ,						image_processor=lowerCAmelCase__)
									processor_fast.save_pretrained(self.tmpdirname)
									SCREAMING_SNAKE_CASE_: Tuple  		=       AlignProcessor.from_pretrained(self.tmpdirname)

									self.assertEqual(processor_slow.tokenizer.get_vocab()   ,						tokenizer_slow.get_vocab())
									self.assertEqual(processor_fast.tokenizer.get_vocab()   ,						tokenizer_fast.get_vocab())
									self.assertEqual(tokenizer_slow.get_vocab()   ,						tokenizer_fast.get_vocab())
									self.assertIsInstance(processor_slow.tokenizer   ,						lowerCAmelCase__)
									self.assertIsInstance(processor_fast.tokenizer   ,						lowerCAmelCase__)

									self.assertEqual(processor_slow.image_processor.to_json_string()   ,						image_processor.to_json_string())
									self.assertEqual(processor_fast.image_processor.to_json_string()   ,						image_processor.to_json_string())
									self.assertIsInstance(processor_slow.image_processor   ,						lowerCAmelCase__)
									self.assertIsInstance(processor_fast.image_processor   ,						lowerCAmelCase__)



			def        _SCREAMING_SNAKE_CASE			( self  :     Tuple):
									SCREAMING_SNAKE_CASE_: List[Any]  		=       AlignProcessor(tokenizer=self.get_tokenizer()   ,						image_processor=self.get_image_processor())
									processor.save_pretrained(self.tmpdirname)

									SCREAMING_SNAKE_CASE_: Dict  		=       self.get_tokenizer(bos_token="(BOS)"   ,						eos_token="(EOS)")
									SCREAMING_SNAKE_CASE_: List[str]  		=       self.get_image_processor(do_normalize=lowerCAmelCase__   ,						padding_value=1.0)

									SCREAMING_SNAKE_CASE_: Dict  		=       AlignProcessor.from_pretrained(
									    self.tmpdirname   ,						bos_token="(BOS)"   ,						eos_token="(EOS)"   ,						do_normalize=lowerCAmelCase__   ,						padding_value=1.0)

									self.assertEqual(processor.tokenizer.get_vocab()   ,						tokenizer_add_kwargs.get_vocab())
									self.assertIsInstance(processor.tokenizer   ,						lowerCAmelCase__)

									self.assertEqual(processor.image_processor.to_json_string()   ,						image_processor_add_kwargs.to_json_string())
									self.assertIsInstance(processor.image_processor   ,						lowerCAmelCase__)



			def        _SCREAMING_SNAKE_CASE			( self  :     List[str]):
									SCREAMING_SNAKE_CASE_: List[Any]  		=       self.get_image_processor()
									SCREAMING_SNAKE_CASE_: Any  		=       self.get_tokenizer()

									SCREAMING_SNAKE_CASE_: List[str]  		=       AlignProcessor(tokenizer=lowerCAmelCase__   ,						image_processor=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: Any  		=       self.prepare_image_inputs()

									SCREAMING_SNAKE_CASE_: List[Any]  		=       image_processor(lowerCAmelCase__   ,						return_tensors="np")
									SCREAMING_SNAKE_CASE_: int  		=       processor(images=lowerCAmelCase__   ,						return_tensors="np")

									for key in input_image_proc.keys():
															self.assertAlmostEqual(input_image_proc[key].sum()   ,						input_processor[key].sum()   ,						delta=1E-2)



			def        _SCREAMING_SNAKE_CASE			( self  :     Any):
									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       self.get_image_processor()
									SCREAMING_SNAKE_CASE_: List[str]  		=       self.get_tokenizer()

									SCREAMING_SNAKE_CASE_: Any  		=       AlignProcessor(tokenizer=lowerCAmelCase__   ,						image_processor=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: str  		=       "lower newer"

									SCREAMING_SNAKE_CASE_: Tuple  		=       processor(text=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: Dict  		=       tokenizer(lowerCAmelCase__   ,						padding="max_length"   ,						max_length=64)

									for key in encoded_tok.keys():
															self.assertListEqual(encoded_tok[key]   ,						encoded_processor[key])



			def        _SCREAMING_SNAKE_CASE			( self  :     List[str]):
									SCREAMING_SNAKE_CASE_: List[str]  		=       self.get_image_processor()
									SCREAMING_SNAKE_CASE_: str  		=       self.get_tokenizer()

									SCREAMING_SNAKE_CASE_: Dict  		=       AlignProcessor(tokenizer=lowerCAmelCase__   ,						image_processor=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: List[str]  		=       "lower newer"
									SCREAMING_SNAKE_CASE_: Tuple  		=       self.prepare_image_inputs()

									SCREAMING_SNAKE_CASE_: Optional[int]  		=       processor(text=lowerCAmelCase__   ,						images=lowerCAmelCase__)

									self.assertListEqual(list(inputs.keys())   ,						["input_ids", "token_type_ids", "attention_mask", "pixel_values"])

									# test if it raises when no input is passed
									with pytest.raises(lowerCAmelCase__):
															processor()



			def        _SCREAMING_SNAKE_CASE			( self  :     Tuple):
									SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       self.get_image_processor()
									SCREAMING_SNAKE_CASE_: int  		=       self.get_tokenizer()

									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       AlignProcessor(tokenizer=lowerCAmelCase__   ,						image_processor=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: Optional[int]  		=       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

									SCREAMING_SNAKE_CASE_: Optional[Any]  		=       processor.batch_decode(lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_: List[str]  		=       tokenizer.batch_decode(lowerCAmelCase__)

									self.assertListEqual(lowerCAmelCase__   ,						lowerCAmelCase__)




			def        _SCREAMING_SNAKE_CASE			( self  :     List[Any]):
									SCREAMING_SNAKE_CASE_: Dict  		=       self.get_image_processor()
									SCREAMING_SNAKE_CASE_: Tuple  		=       self.get_tokenizer()

									SCREAMING_SNAKE_CASE_: Any  		=       AlignProcessor(tokenizer=lowerCAmelCase__   ,						image_processor=lowerCAmelCase__)

									SCREAMING_SNAKE_CASE_: Tuple  		=       "lower newer"
									SCREAMING_SNAKE_CASE_: str  		=       self.prepare_image_inputs()

									SCREAMING_SNAKE_CASE_: int  		=       processor(text=lowerCAmelCase__   ,						images=lowerCAmelCase__)

									self.assertListEqual(list(inputs.keys())   ,						processor.model_input_names)














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		:       List[str]			     = "src/diffusers"
a		:       str			     = "."


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






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






def 				lowerCamelCase__      (    __lowerCamelCase			:     Any		):
  __UpperCAmelCase							:	Optional[int]           =  object_name.split("""."""		)
  __UpperCAmelCase							:	List[Any]           =  0

  # First let's find the module where our object lives.
  __UpperCAmelCase							:	Optional[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		):
      __UpperCAmelCase							:	List[str]           =  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:
    __UpperCAmelCase							:	Optional[Any]           =  f.readlines()

  # Now let's find the class / func in the code!
  __UpperCAmelCase							:	List[str]           =  """"""
  __UpperCAmelCase							:	int           =  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).
  __UpperCAmelCase							:	List[str]           =  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

  __UpperCAmelCase							:	Dict           =  lines[start_index:line_index]
  return "".join(__lowerCamelCase		)


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






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






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

    __UpperCAmelCase							:	Tuple           =  line_index + 1 if indent == theoretical_indent else line_index + 2
    __UpperCAmelCase							:	Any           =  theoretical_indent
    __UpperCAmelCase							:	Any           =  start_index

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

    __UpperCAmelCase							:	Optional[int]           =  lines[start_index:line_index]
    __UpperCAmelCase							:	int           =  """""".join(__lowerCamelCase		)

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

    # Before comparing, use the `replace_pattern` on the original code.
    if len(__lowerCamelCase		) > 0:
      __UpperCAmelCase							:	List[str]           =  replace_pattern.replace("""with"""  ,		""""""		).split(""","""		)
      __UpperCAmelCase							:	Any           =  [_re_replace_pattern.search(__lowerCamelCase		) for p in patterns]
      for pattern in patterns:
        if pattern is None:
          continue
        __UpperCAmelCase      , __UpperCAmelCase      , __UpperCAmelCase							:	Union[str, Any]           =  pattern.groups()
        __UpperCAmelCase							:	List[str]           =  re.sub(__lowerCamelCase  ,		__lowerCamelCase  ,		__lowerCamelCase		)
        if option.strip() == "all-casing":
          __UpperCAmelCase							:	List[Any]           =  re.sub(obja.lower()  ,		obja.lower()  ,		__lowerCamelCase		)
          __UpperCAmelCase							:	int           =  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
      __UpperCAmelCase							:	Union[str, Any]           =  blackify(lines[start_index - 1] + theoretical_code		)
      __UpperCAmelCase							:	Optional[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:
        __UpperCAmelCase							:	int           =  lines[:start_index] + [theoretical_code] + lines[line_index:]
        __UpperCAmelCase							:	Union[str, 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 				lowerCamelCase__      (    __lowerCamelCase			:     bool = False		):
  __UpperCAmelCase							:	Tuple           =  glob.glob(os.path.join(__lowerCamelCase  ,		"""**/*.py"""		)  ,		recursive=__lowerCamelCase		)
  __UpperCAmelCase							:	Optional[int]           =  []
  for filename in all_files:
    __UpperCAmelCase							:	str           =  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:
    __UpperCAmelCase							:	Union[str, 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		:       Dict			     = argparse.ArgumentParser()
       parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
       a		:       Optional[int]			     = parser.parse_args()

       check_copies(args.fix_and_overwrite)


