


"""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
__snake_case             =   """src/diffusers"""
__snake_case             =   """."""


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







def   __lowerCAmelCase						(						lowercase  :  str						,							lowercase  :  int			)     ->						Dict:


    """simple docstring"""





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







def   __lowerCAmelCase						(						lowercase  :  Tuple			)     ->						Any:


    """simple docstring"""





    snake_case   :				Union[str, Any]				 =   object_name.split("."			)
    snake_case   :				str				 =   0

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

    with open(os.path.join(lowercase						,							F'{module}.py'			)						,							"r"						,							encoding="utf-8"						,							newline="\n"			) as f:
        snake_case   :				Any				 =   f.readlines()

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

    snake_case   :				str				 =   lines[start_index:line_index]
    return "".join(lowercase			)


__snake_case             =   re.compile(R"""^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)""")
__snake_case             =   re.compile(R"""^\s*(\S+)->(\S+)(\s+.*|$)""")
__snake_case             =   re.compile(R"""<FILL\s+[^>]*>""")







def   __lowerCAmelCase						(						lowercase  :  str			)     ->						str:


    """simple docstring"""





    snake_case   :				Dict				 =   code.split("\n"			)
    snake_case   :				str				 =   0
    while idx < len(lowercase			) and len(lines[idx]			) == 0:
        idx += 1
    if idx < len(lowercase			):
        return re.search(R"^(\s*)\S"						,							lines[idx]			).groups()[0]
    return ""







def   __lowerCAmelCase						(						lowercase  :  List[str]			)     ->						str:


    """simple docstring"""





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







def   __lowerCAmelCase						(						lowercase  :  Dict						,							lowercase  :  Tuple=False			)     ->						Optional[Any]:


    """simple docstring"""





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

        snake_case   :				Any				 =   line_index + 1 if indent == theoretical_indent else line_index + 2
        snake_case   :				str				 =   theoretical_indent
        snake_case   :				str				 =   start_index

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

        snake_case   :				int				 =   lines[start_index:line_index]
        snake_case   :				List[Any]				 =   "".join(lowercase			)

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

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

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

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







def   __lowerCAmelCase						(						lowercase  :  bool = False			)     ->						Dict:


    """simple docstring"""





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

  check_copies(args.fix_and_overwrite)









"""simple docstring"""



from . import __version__

# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
    CLOUDFRONT_DISTRIB_PREFIX,
    CONFIG_NAME,
    DISABLE_TELEMETRY,
    DUMMY_INPUTS,
    DUMMY_MASK,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    FEATURE_EXTRACTOR_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_PREFIX,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    MODEL_CARD_NAME,
    MULTIPLE_CHOICE_DUMMY_INPUTS,
    PYTORCH_PRETRAINED_BERT_CACHE,
    PYTORCH_TRANSFORMERS_CACHE,
    S3_BUCKET_PREFIX,
    SENTENCEPIECE_UNDERLINE,
    SPIECE_UNDERLINE,
    TF2_WEIGHTS_NAME,
    TF_WEIGHTS_NAME,
    TORCH_FX_REQUIRED_VERSION,
    TRANSFORMERS_CACHE,
    TRANSFORMERS_DYNAMIC_MODULE_NAME,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    WEIGHTS_INDEX_NAME,
    WEIGHTS_NAME,
    ContextManagers,
    DummyObject,
    EntryNotFoundError,
    ExplicitEnum,
    ModelOutput,
    PaddingStrategy,
    PushToHubMixin,
    RepositoryNotFoundError,
    RevisionNotFoundError,
    TensorType,
    _LazyModule,
    add_code_sample_docstrings,
    add_end_docstrings,
    add_start_docstrings,
    add_start_docstrings_to_model_forward,
    cached_property,
    copy_func,
    default_cache_path,
    define_sagemaker_information,
    get_cached_models,
    get_file_from_repo,
    get_full_repo_name,
    get_torch_version,
    has_file,
    http_user_agent,
    is_apex_available,
    is_bsa_available,
    is_coloredlogs_available,
    is_datasets_available,
    is_detectrona_available,
    is_faiss_available,
    is_flax_available,
    is_ftfy_available,
    is_in_notebook,
    is_ipex_available,
    is_librosa_available,
    is_offline_mode,
    is_onnx_available,
    is_pandas_available,
    is_phonemizer_available,
    is_protobuf_available,
    is_psutil_available,
    is_pyanvml_available,
    is_pyctcdecode_available,
    is_pytesseract_available,
    is_pytorch_quantization_available,
    is_rjieba_available,
    is_sagemaker_dp_enabled,
    is_sagemaker_mp_enabled,
    is_scipy_available,
    is_sentencepiece_available,
    is_seqio_available,
    is_sklearn_available,
    is_soundfile_availble,
    is_spacy_available,
    is_speech_available,
    is_tensor,
    is_tensorflow_probability_available,
    is_tfaonnx_available,
    is_tf_available,
    is_timm_available,
    is_tokenizers_available,
    is_torch_available,
    is_torch_bfaa_available,
    is_torch_cuda_available,
    is_torch_fx_available,
    is_torch_fx_proxy,
    is_torch_mps_available,
    is_torch_tfaa_available,
    is_torch_tpu_available,
    is_torchaudio_available,
    is_training_run_on_sagemaker,
    is_vision_available,
    replace_return_docstrings,
    requires_backends,
    to_numpy,
    to_py_obj,
    torch_only_method,
)





