


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


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






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






def 							__lowercase     (				__lowerCAmelCase							:       Any     ):
							a__    =  object_name.split('.'     )
							a__    =  0

							# First let's find the module where our object lives.
							a__    =  parts[i]
							while i < len(__lowerCAmelCase     ) and not os.path.isfile(os.path.join(__lowerCAmelCase      ,					F'{module}.py'     )     ):
														i += 1
														if i < len(__lowerCAmelCase     ):
																					a__    =  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:
														a__    =  f.readlines()

							# Now let's find the class / func in the code!
							a__    =  ''
							a__    =  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).
							a__    =  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

							a__    =  lines[start_index:line_index]
							return "".join(__lowerCAmelCase     )


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






def 							__lowercase     (				__lowerCAmelCase							:       Union[str, Any]     ):
							a__    =  code.split('\n'     )
							a__    =  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 							__lowercase     (				__lowerCAmelCase							:       Any     ):
							a__    =  len(get_indent(__lowerCAmelCase     )     ) > 0
							if has_indent:
														a__    =  F'class Bla:\n{code}'
							a__    =  black.Mode(target_versions={black.TargetVersion.PYaa}      ,					line_length=1_1_9      ,					preview=__lowerCAmelCase     )
							a__    =  black.format_str(__lowerCAmelCase      ,					mode=__lowerCAmelCase     )
							a__   ,      a__    =  style_docstrings_in_code(__lowerCAmelCase     )
							return result[len('class Bla:\n'     ) :] if has_indent else result






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

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

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

														a__    =  lines[start_index:line_index]
														a__    =  ''.join(__lowerCAmelCase     )

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

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

						check_copies(args.fix_and_overwrite)








import os
import tempfile
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
						import torch
						from torch import nn

						from transformers import (
						    Adafactor,
						    AdamW,
						    get_constant_schedule,
						    get_constant_schedule_with_warmup,
						    get_cosine_schedule_with_warmup,
						    get_cosine_with_hard_restarts_schedule_with_warmup,
						    get_inverse_sqrt_schedule,
						    get_linear_schedule_with_warmup,
						    get_polynomial_decay_schedule_with_warmup,
						)






def 							__lowercase     (				__lowerCAmelCase							:       str      ,					__lowerCAmelCase							:       Any=1_0     ):
							a__    =  []
							for _ in range(__lowerCAmelCase     ):
														lrs.append(scheduler.get_lr()[0]     )
														scheduler.step()
							return lrs






def 							__lowercase     (				__lowerCAmelCase							:       Optional[int]      ,					__lowerCAmelCase							:       List[str]=1_0     ):
							a__    =  []
							for step in range(__lowerCAmelCase     ):
														lrs.append(scheduler.get_lr()[0]     )
														scheduler.step()
														if step == num_steps // 2:
																					with tempfile.TemporaryDirectory() as tmpdirname:
																												a__    =  os.path.join(__lowerCAmelCase      ,					'schedule.bin'     )
																												torch.save(scheduler.state_dict()      ,					__lowerCAmelCase     )

																												a__    =  torch.load(__lowerCAmelCase     )
																												scheduler.load_state_dict(__lowerCAmelCase     )
							return lrs







@require_torch
class  snake_case_     (unittest.TestCase   ):
					def 				lowerCamelCase__(   self     :Optional[int]    ,__snake_case     :List[Any]    ,__snake_case     :int    ,__snake_case     :Union[str, Any]   )      ->					int:
												self.assertEqual(len(__snake_case   )    ,len(__snake_case   )   )
												for a, b in zip(__snake_case    ,__snake_case   ):
																			self.assertAlmostEqual(__snake_case    ,__snake_case    ,delta=__snake_case   )
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					str:
												a__    =  torch.tensor([0.1, -0.2, -0.1]    ,requires_grad=__snake_case   )
												a__    =  torch.tensor([0.4, 0.2, -0.5]   )
												a__    =  nn.MSELoss()
												# No warmup, constant schedule, no gradient clipping
												a__    =  AdamW(params=[w]    ,lr=2E-1    ,weight_decay=0.0   )
												for _ in range(1_00   ):
																			a__    =  criterion(__snake_case    ,__snake_case   )
																			loss.backward()
																			optimizer.step()
																			w.grad.detach_()  # No zero_grad() function on simple tensors. we do it ourselves.
																			w.grad.zero_()
												self.assertListAlmostEqual(w.tolist()    ,[0.4, 0.2, -0.5]    ,tol=1E-2   )



					def 				lowerCamelCase__(   self     :Tuple   )      ->					int:
												a__    =  torch.tensor([0.1, -0.2, -0.1]    ,requires_grad=__snake_case   )
												a__    =  torch.tensor([0.4, 0.2, -0.5]   )
												a__    =  nn.MSELoss()
												# No warmup, constant schedule, no gradient clipping
												a__    =  Adafactor(
												    params=[w]    ,lr=1E-2    ,eps=(1E-30, 1E-3)    ,clip_threshold=1.0    ,decay_rate=-0.8    ,betaa=__snake_case    ,weight_decay=0.0    ,relative_step=__snake_case    ,scale_parameter=__snake_case    ,warmup_init=__snake_case    ,)
												for _ in range(10_00   ):
																			a__    =  criterion(__snake_case    ,__snake_case   )
																			loss.backward()
																			optimizer.step()
																			w.grad.detach_()  # No zero_grad() function on simple tensors. we do it ourselves.
																			w.grad.zero_()
												self.assertListAlmostEqual(w.tolist()    ,[0.4, 0.2, -0.5]    ,tol=1E-2   )







@require_torch
class  snake_case_     (unittest.TestCase   ):
					UpperCAmelCase__      :					str					   =    nn.Linear(5_0			,		5_0   ) if is_torch_available() else None
					UpperCAmelCase__      :					Dict					   =    AdamW(m.parameters()			,		lr=1_0.0   ) if is_torch_available() else None
					UpperCAmelCase__      :					Optional[Any]					   =    1_0
					def 				lowerCamelCase__(   self     :Optional[Any]    ,__snake_case     :Optional[int]    ,__snake_case     :Tuple    ,__snake_case     :int    ,__snake_case     :Any=None   )      ->					Optional[Any]:
												self.assertEqual(len(__snake_case   )    ,len(__snake_case   )   )
												for a, b in zip(__snake_case    ,__snake_case   ):
																			self.assertAlmostEqual(__snake_case    ,__snake_case    ,delta=__snake_case    ,msg=__snake_case   )



					def 				lowerCamelCase__(   self     :Tuple   )      ->					List[Any]:
												a__    =  {'num_warmup_steps': 2, 'num_training_steps': 10}
												# schedulers doct format
												# function: (sched_args_dict, expected_learning_rates)
												a__    =  {
												    get_constant_schedule: ({}, [10.0] * self.num_steps),
												    get_constant_schedule_with_warmup: (
												        {'num_warmup_steps': 4},
												        [0.0, 2.5, 5.0, 7.5, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0],
												    ),
												    get_linear_schedule_with_warmup: (
												        {**common_kwargs},
												        [0.0, 5.0, 10.0, 8.75, 7.5, 6.25, 5.0, 3.75, 2.5, 1.25],
												    ),
												    get_cosine_schedule_with_warmup: (
												        {**common_kwargs},
												        [0.0, 5.0, 10.0, 9.61, 8.53, 6.91, 5.0, 3.08, 1.46, 0.38],
												    ),
												    get_cosine_with_hard_restarts_schedule_with_warmup: (
												        {**common_kwargs, 'num_cycles': 2},
												        [0.0, 5.0, 10.0, 8.53, 5.0, 1.46, 10.0, 8.53, 5.0, 1.46],
												    ),
												    get_polynomial_decay_schedule_with_warmup: (
												        {**common_kwargs, 'power': 2.0, 'lr_end': 1E-7},
												        [0.0, 5.0, 10.0, 7.6_56, 5.6_25, 3.9_06, 2.5, 1.4_06, 0.6_25, 0.1_56],
												    ),
												    get_inverse_sqrt_schedule: (
												        {'num_warmup_steps': 2},
												        [0.0, 5.0, 10.0, 8.1_65, 7.0_71, 6.3_25, 5.7_74, 5.3_45, 5.0, 4.7_14],
												    ),
												}

												for scheduler_func, data in scheds.items():
																			a__   ,      a__    =  data

																			a__    =  scheduler_func(self.optimizer    ,**__snake_case   )
																			self.assertEqual(len([scheduler.get_lr()[0]]   )    ,1   )
																			a__    =  unwrap_schedule(__snake_case    ,self.num_steps   )
																			self.assertListAlmostEqual(
																			    __snake_case    ,__snake_case    ,tol=1E-2    ,msg=F'failed for {scheduler_func} in normal scheduler'    ,)

																			a__    =  scheduler_func(self.optimizer    ,**__snake_case   )
																			if scheduler_func.__name__ != "get_constant_schedule":
																										LambdaScheduleWrapper.wrap_scheduler(__snake_case   )  # wrap to test picklability of the schedule
																			a__    =  unwrap_and_save_reload_schedule(__snake_case    ,self.num_steps   )
																			self.assertListEqual(__snake_case    ,__snake_case    ,msg=F'failed for {scheduler_func} in save and reload'   )







class  snake_case_     :
					def __init__(   self     :Tuple    ,__snake_case     :str   )      ->					Any:
												a__    =  fn
					def __call__(   self     :List[str]    ,*__snake_case     :Optional[Any]    ,**__snake_case     :Optional[int]   )      ->					Union[str, Any]:
												return self.fn(*__snake_case    ,**__snake_case   )



					@classmethod
					def 				lowerCamelCase__(   self     :Tuple    ,__snake_case     :Union[str, Any]   )      ->					Dict:
												a__    =  list(map(self    ,scheduler.lr_lambdas   )   )




