


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
SCREAMING_SNAKE_CASE :   Union[str, Any]							      =				'''src/diffusers'''
SCREAMING_SNAKE_CASE :   Union[str, Any]							      =				'''.'''


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



def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		List[str]:
    return line.startswith(lowerCAmelCase__				) or len(lowerCAmelCase__				) <= 1 or re.search(R'^\s*\)(\s*->.*:|:)\s*$'							,				lowerCAmelCase__				) is not None



def        UpperCamelCase_(   lowerCamelCase_				)					->		List[str]:
    _lowercase :							Optional[Any]   	=	object_name.split('.'				)
    _lowercase :							Tuple   	=	0

    # First let's find the module where our object lives.
    _lowercase :							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__				):
            _lowercase :							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:
        _lowercase :							Tuple   	=	f.readlines()

    # Now let's find the class / func in the code!
    _lowercase :							Tuple   	=	''
    _lowercase :							Union[str, Any]   	=	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).
    _lowercase :							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

    _lowercase :							Dict   	=	lines[start_index:line_index]
    return "".join(lowerCAmelCase__				)


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



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



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

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

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

        _lowercase :							Union[str, Any]   	=	lines[start_index:line_index]
        _lowercase :							Union[str, Any]   	=	''.join(lowerCAmelCase__				)

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

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

 check_copies(args.fix_and_overwrite)






import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List

from ..utils import logging


SCREAMING_SNAKE_CASE :   Dict							      =				logging.get_logger(__name__)



def        UpperCamelCase_(   lowerCamelCase_=None							,				lowerCamelCase_=None				)					->		Tuple:
    return field(default_factory=lambda: default							,				metadata=lowerCamelCase_				)






@dataclass
class _lowerCamelCase:
       lowercase_				:			List[str]									=    list_field(
           default=[],				metadata={
               """help""": (
                   """Model checkpoints to be provided to the AutoModel classes. Leave blank to benchmark the base version"""
                   """ of all available models"""
               )
           },				)

       lowercase_				:			List[int]									=    list_field(
           default=[8],				metadata={"""help""": """List of batch sizes for which memory and time performance will be evaluated"""}     )

       lowercase_				:			List[int]									=    list_field(
           default=[8, 32, 1_28, 5_12],				metadata={"""help""": """List of sequence lengths for which memory and time performance will be evaluated"""},				)

       lowercase_				:			bool									=    field(
           default=_a,				metadata={"""help""": """Whether to benchmark inference of model. Inference can be disabled via --no-inference."""},				)
       lowercase_				:			bool									=    field(
           default=_a,				metadata={"""help""": """Whether to run on available cuda devices. Cuda can be disabled via --no-cuda."""},				)
       lowercase_				:			bool									=    field(
           default=_a,				metadata={"""help""": """Whether to run on available tpu devices. TPU can be disabled via --no-tpu."""}     )
       lowercase_				:			bool									=    field(default=_a,				metadata={"""help""": """Use FP16 to accelerate inference."""}     )
       lowercase_				:			bool									=    field(default=_a,				metadata={"""help""": """Benchmark training of model"""}     )
       lowercase_				:			bool									=    field(default=_a,				metadata={"""help""": """Verbose memory tracing"""}     )
       lowercase_				:			bool									=    field(
           default=_a,				metadata={"""help""": """Whether to perform speed measurements. Speed measurements can be disabled via --no-speed."""},				)
       lowercase_				:			bool									=    field(
           default=_a,				metadata={
               """help""": """Whether to perform memory measurements. Memory measurements can be disabled via --no-memory"""
           },				)
       lowercase_				:			bool									=    field(default=_a,				metadata={"""help""": """Trace memory line by line"""}     )
       lowercase_				:			bool									=    field(default=_a,				metadata={"""help""": """Save result to a CSV file"""}     )
       lowercase_				:			bool									=    field(default=_a,				metadata={"""help""": """Save all print statements in a log file"""}     )
       lowercase_				:			bool									=    field(default=_a,				metadata={"""help""": """Whether to print environment information"""}     )
       lowercase_				:			bool									=    field(
           default=_a,				metadata={
               """help""": (
                   """Whether to use multiprocessing for memory and speed measurement. It is highly recommended to use"""
                   """ multiprocessing for accurate CPU and GPU memory measurements. This option should only be disabled"""
                   """ for debugging / testing and on TPU."""
               )
           },				)
       lowercase_				:			str									=    field(
           default=F'''inference_time_{round(time()     )}.csv''',				metadata={"""help""": """CSV filename used if saving time results to csv."""},				)
       lowercase_				:			str									=    field(
           default=F'''inference_memory_{round(time()     )}.csv''',				metadata={"""help""": """CSV filename used if saving memory results to csv."""},				)
       lowercase_				:			str									=    field(
           default=F'''train_time_{round(time()     )}.csv''',				metadata={"""help""": """CSV filename used if saving time results to csv for training."""},				)
       lowercase_				:			str									=    field(
           default=F'''train_memory_{round(time()     )}.csv''',				metadata={"""help""": """CSV filename used if saving memory results to csv for training."""},				)
       lowercase_				:			str									=    field(
           default=F'''env_info_{round(time()     )}.csv''',				metadata={"""help""": """CSV filename used if saving environment information."""},				)
       lowercase_				:			str									=    field(
           default=F'''log_{round(time()     )}.csv''',				metadata={"""help""": """Log filename used if print statements are saved in log."""},				)
       lowercase_				:			int									=    field(default=3,				metadata={"""help""": """Times an experiment will be run."""}     )
       lowercase_				:			bool									=    field(
           default=_a,				metadata={
               """help""": (
                   """Instead of loading the model as defined in `config.architectures` if exists, just load the pretrain"""
                   """ model weights."""
               )
           },				)
       def     UpperCamelCase  (      self) ->     Union[str, Any]:




           """simple docstring"""

           warnings.warn(
               F'''The class {self.__class__} is deprecated. Hugging Face Benchmarking utils'''
               ' are deprecated in general and it is advised to use external Benchmarking libraries '
               ' to benchmark Transformer models.',   lowerCamelCase,   )
       def     UpperCamelCase  (      self) ->     Optional[Any]:




           """simple docstring"""

           return json.dumps(dataclasses.asdict(self),   indent=2)
       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           if len(self.models) <= 0:
               raise ValueError(
                   'Please make sure you provide at least one model name / model identifier, *e.g.* `--models'
                   ' bert-base-cased` or `args.models = [\'bert-base-cased\'].')
           return self.models




       @property
       def     UpperCamelCase  (      self) ->     Dict:




           """simple docstring"""

           if not self.multi_process:
               return False
           elif self.is_tpu:
               logger.info('Multiprocessing is currently not possible on TPU.')
               return False
           else:
               return True


