


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	=							'src/diffusers'
lowerCAmelCase	=							'.'


# This is to make sure the diffusers module imported is the one in the repo.
lowerCAmelCase	=							importlib.util.spec_from_file_location(
    'diffusers',
    os.path.join(DIFFUSERS_PATH, '__init__.py'),
    submodule_search_locations=[DIFFUSERS_PATH],
)
lowerCAmelCase	=							spec.loader.load_module()
def       _a			(				SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE					):
		return line.startswith(SCREAMING_SNAKE_CASE					) or len(SCREAMING_SNAKE_CASE					) <= 1 or re.search(R'''^\s*\)(\s*->.*:|:)\s*$'''						,    SCREAMING_SNAKE_CASE					) is not None
def       _a			(				SCREAMING_SNAKE_CASE					):
		lowercase__						=				object_name.split('''.'''					)
		lowercase__						=				0

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

		with open(os.path.join(SCREAMING_SNAKE_CASE						,    f'{module}.py'					)						,    '''r'''						,    encoding='''utf-8'''						,    newline='''\n'''					) as f:
				lowercase__						=				f.readlines()

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

		lowercase__						=				lines[start_index:line_index]
		return "".join(SCREAMING_SNAKE_CASE					)


lowerCAmelCase	=							re.compile(R'^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)')
lowerCAmelCase	=							re.compile(R'^\s*(\S+)->(\S+)(\s+.*|$)')
lowerCAmelCase	=							re.compile(R'<FILL\s+[^>]*>')
def       _a			(				SCREAMING_SNAKE_CASE					):
		lowercase__						=				code.split('''\n'''					)
		lowercase__						=				0
		while idx < len(SCREAMING_SNAKE_CASE					) and len(lines[idx]					) == 0:
				idx += 1
		if idx < len(SCREAMING_SNAKE_CASE					):
				return re.search(R'''^(\s*)\S'''						,    lines[idx]					).groups()[0]
		return ""
def       _a			(				SCREAMING_SNAKE_CASE					):
		lowercase__						=				len(get_indent(SCREAMING_SNAKE_CASE					)					) > 0
		if has_indent:
				lowercase__						=				f'class Bla:\n{code}'
		lowercase__						=				black.Mode(target_versions={black.TargetVersion.PYaa}						,    line_length=1_19						,    preview=SCREAMING_SNAKE_CASE					)
		lowercase__						=				black.format_str(SCREAMING_SNAKE_CASE						,    mode=SCREAMING_SNAKE_CASE					)
		lowercase__					,		lowercase__						=				style_docstrings_in_code(SCREAMING_SNAKE_CASE					)
		return result[len('''class Bla:\n'''					) :] if has_indent else result
def       _a			(				SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE=False					):




		with open(SCREAMING_SNAKE_CASE						,    '''r'''						,    encoding='''utf-8'''						,    newline='''\n'''					) as f:
				lowercase__						=				f.readlines()
		lowercase__						=				[]
		lowercase__						=				0
		# Not a for loop cause `lines` is going to change (if `overwrite=True`).
		while line_index < len(SCREAMING_SNAKE_CASE					):
				lowercase__						=				_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__						=				search.groups()
				lowercase__						=				find_code_in_diffusers(SCREAMING_SNAKE_CASE					)
				lowercase__						=				get_indent(SCREAMING_SNAKE_CASE					)

				lowercase__						=				line_index + 1 if indent == theoretical_indent else line_index + 2
				lowercase__						=				theoretical_indent
				lowercase__						=				start_index

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

				lowercase__						=				lines[start_index:line_index]
				lowercase__						=				''''''.join(SCREAMING_SNAKE_CASE					)

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

				# Before comparing, use the `replace_pattern` on the original code.
				if len(SCREAMING_SNAKE_CASE					) > 0:
						lowercase__						=				replace_pattern.replace('''with'''						,    ''''''					).split(''','''					)
						lowercase__						=				[_re_replace_pattern.search(SCREAMING_SNAKE_CASE					) for p in patterns]
						for pattern in patterns:
								if pattern is None:
										continue
								lowercase__					,		lowercase__					,		lowercase__						=				pattern.groups()
								lowercase__						=				re.sub(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE					)
								if option.strip() == "all-casing":
										lowercase__						=				re.sub(obja.lower()						,    obja.lower()						,    SCREAMING_SNAKE_CASE					)
										lowercase__						=				re.sub(obja.upper()						,    obja.upper()						,    SCREAMING_SNAKE_CASE					)

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

		if overwrite and len(SCREAMING_SNAKE_CASE					) > 0:
				# Warn the user a file has been modified.
				print(f'Detected changes, rewriting {filename}.'					)
				with open(SCREAMING_SNAKE_CASE						,    '''w'''						,    encoding='''utf-8'''						,    newline='''\n'''					) as f:
						f.writelines(SCREAMING_SNAKE_CASE					)
		return diffs
def       _a			(				SCREAMING_SNAKE_CASE = False					):
		lowercase__						=				glob.glob(os.path.join(SCREAMING_SNAKE_CASE						,    '''**/*.py'''					)						,    recursive=SCREAMING_SNAKE_CASE					)
		lowercase__						=				[]
		for filename in all_files:
				lowercase__						=				is_copy_consistent(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE					)
				diffs += [f'- {filename}: copy does not match {d[0]} at line {d[1]}' for d in new_diffs]
		if not overwrite and len(SCREAMING_SNAKE_CASE					) > 0:
				lowercase__						=				'''\n'''.join(SCREAMING_SNAKE_CASE					)
				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	=							argparse.ArgumentParser()
			parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
			lowerCAmelCase	=							parser.parse_args()

			check_copies(args.fix_and_overwrite)






import json
import logging
import os
import socket

import git
import numpy as np
import torch


logging.basicConfig(
    format='%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d -  %(message)s',
    datefmt='%m/%d/%Y %H:%M:%S',
    level=logging.INFO,
)
lowerCAmelCase	=							logging.getLogger(__name__)
def       _a			(				SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		lowercase__						=				git.Repo(search_parent_directories=SCREAMING_SNAKE_CASE					)
		lowercase__						=				{
		    '''repo_id''': str(SCREAMING_SNAKE_CASE					),
		    '''repo_sha''': str(repo.head.object.hexsha					),
		    '''repo_branch''': str(repo.active_branch					),
		}

		with open(os.path.join(SCREAMING_SNAKE_CASE						,    '''git_log.json'''					)						,    '''w'''					) as f:
				json.dump(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE						,    indent=4					)
def       _a			(				SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		if params.n_gpu <= 0:
				lowercase__						=				0
				lowercase__						=				-1
				lowercase__						=				True
				lowercase__						=				False
				return

		assert torch.cuda.is_available()

		logger.info('''Initializing GPUs'''					)
		if params.n_gpu > 1:
				assert params.local_rank != -1

				lowercase__						=				int(os.environ['''WORLD_SIZE''']					)
				lowercase__						=				int(os.environ['''N_GPU_NODE''']					)
				lowercase__						=				int(os.environ['''RANK''']					)

				# number of nodes / node ID
				lowercase__						=				params.world_size // params.n_gpu_per_node
				lowercase__						=				params.global_rank // params.n_gpu_per_node
				lowercase__						=				True

				assert params.n_nodes == int(os.environ['''N_NODES''']					)
				assert params.node_id == int(os.environ['''NODE_RANK''']					)

		# local job (single GPU)
		else:
				assert params.local_rank == -1

				lowercase__						=				1
				lowercase__						=				0
				lowercase__						=				0
				lowercase__						=				0
				lowercase__						=				1
				lowercase__						=				1
				lowercase__						=				False

		# sanity checks
		assert params.n_nodes >= 1
		assert 0 <= params.node_id < params.n_nodes
		assert 0 <= params.local_rank <= params.global_rank < params.world_size
		assert params.world_size == params.n_nodes * params.n_gpu_per_node

		# define whether this is the master process / if we are in multi-node distributed mode
		lowercase__						=				params.node_id == 0 and params.local_rank == 0
		lowercase__						=				params.n_nodes > 1

		# summary
		lowercase__						=				f'--- Global rank: {params.global_rank} - '
		logger.info(PREFIX + '''Number of nodes: %i''' % params.n_nodes					)
		logger.info(PREFIX + '''Node ID        : %i''' % params.node_id					)
		logger.info(PREFIX + '''Local rank     : %i''' % params.local_rank					)
		logger.info(PREFIX + '''World size     : %i''' % params.world_size					)
		logger.info(PREFIX + '''GPUs per node  : %i''' % params.n_gpu_per_node					)
		logger.info(PREFIX + '''Master         : %s''' % str(params.is_master					)					)
		logger.info(PREFIX + '''Multi-node     : %s''' % str(params.multi_node					)					)
		logger.info(PREFIX + '''Multi-GPU      : %s''' % str(params.multi_gpu					)					)
		logger.info(PREFIX + '''Hostname       : %s''' % socket.gethostname()					)

		# set GPU device
		torch.cuda.set_device(params.local_rank					)

		# initialize multi-GPU
		if params.multi_gpu:
				logger.info('''Initializing PyTorch distributed'''					)
				torch.distributed.init_process_group(
				    init_method='''env://'''						,    backend='''nccl'''						,    )
def       _a			(				SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		np.random.seed(args.seed					)
		torch.manual_seed(args.seed					)
		if args.n_gpu > 0:
				torch.cuda.manual_seed_all(args.seed					)


