
import inspect
import os
import unittest

import torch

import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment







class        lowercase	(      unittest.TestCase	):




							def 				A__   (       self):
												lowercase					=		inspect.getfile(accelerate.test_utils)
												lowercase					=		os.path.sep.join(mod_file.split(os.path.sep)[:-1] + ['''scripts''', '''test_script.py'''])
												lowercase					=		os.path.sep.join(
												    mod_file.split(os.path.sep)[:-1] + ['''scripts''', '''test_distributed_data_loop.py'''])
												lowercase					=		os.path.sep.join(mod_file.split(os.path.sep)[:-1] + ['''scripts''', '''test_ops.py'''])




							@require_multi_gpu
							def 				A__   (       self):
												print(f'Found {torch.cuda.device_count()} devices.')
												lowercase					=		['''torchrun''', f'--nproc_per_node={torch.cuda.device_count()}', self.test_file_path]
												with patch_environment(omp_num_threads=1):
																	execute_subprocess_async(A__     ,env=os.environ.copy())




							@require_multi_gpu
							def 				A__   (       self):
												print(f'Found {torch.cuda.device_count()} devices.')
												lowercase					=		['''torchrun''', f'--nproc_per_node={torch.cuda.device_count()}', self.operation_file_path]
												print(f'Command: {cmd}')
												with patch_environment(omp_num_threads=1):
																	execute_subprocess_async(A__     ,env=os.environ.copy())




							@require_multi_gpu
							def 				A__   (       self):
												lowercase					=		['''torchrun''', f'--nproc_per_node={torch.cuda.device_count()}', inspect.getfile(self.__class__)]
												with patch_environment(omp_num_threads=1):
																	execute_subprocess_async(A__     ,env=os.environ.copy())





							@require_multi_gpu
							def 				A__   (       self):
												print(f'Found {torch.cuda.device_count()} devices, using 2 devices only')
												lowercase					=		['''torchrun''', f'--nproc_per_node={torch.cuda.device_count()}', self.data_loop_file_path]
												with patch_environment(omp_num_threads=1     ,cuda_visible_devices='''0,1'''):
																	execute_subprocess_async(A__     ,env=os.environ.copy())


if __name__ == "__main__":
							lowercase__	:int										=							Accelerator()
							lowercase__	:Optional[int]										=							(accelerator.state.process_index + 2, 10)
							lowercase__	:List[str]										=							torch.randint(0, 10, shape).to(accelerator.device)

							lowercase__	:Any										=							""

							lowercase__	:List[str]										=							accelerator.pad_across_processes(tensor)
							if tensora.shape[0] != accelerator.state.num_processes + 1:
														error_msg += F"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
							if not torch.equal(tensora[: accelerator.state.process_index + 2], tensor):
														error_msg += "Tensors have different values."
							if not torch.all(tensora[accelerator.state.process_index + 2 :] == 0):
														error_msg += "Padding was not done with the right value (0)."

							lowercase__	:Dict										=							accelerator.pad_across_processes(tensor, pad_first=True)
							if tensora.shape[0] != accelerator.state.num_processes + 1:
														error_msg += F"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
							lowercase__	:Tuple										=							accelerator.state.num_processes - accelerator.state.process_index - 1
							if not torch.equal(tensora[index:], tensor):
														error_msg += "Tensors have different values."
							if not torch.all(tensora[:index] == 0):
														error_msg += "Padding was not done with the right value (0)."

							# Raise error at the end to make sure we don't stop at the first failure.
							if len(error_msg) > 0:
														raise ValueError(error_msg)






import argparse
from collections import defaultdict

import yaml


lowercase__	:Optional[int]										=					"docs/source/en/_toctree.yml"



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		defaultdict(lowerCAmelCase__	)
					for doc in model_doc:
										counts[doc["local"]] += 1
					lowercase					=		[key for key, value in counts.items() if value > 1]

					lowercase					=		[]
					for duplicate_key in duplicates:
										lowercase					=		list({doc['''title'''] for doc in model_doc if doc['''local'''] == duplicate_key}	)
										if len(lowerCAmelCase__	) > 1:
															raise ValueError(
															    f'{duplicate_key} is present several times in the documentation table of content at '
															    '''`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '''
															    '''others.'''	)
										# Only add this once
										new_doc.append({'''local''': duplicate_key, '''title''': titles[0]}	)

					# Add none duplicate-keys
					new_doc.extend([doc for doc in model_doc if counts[doc['''local''']] == 1]	)

					# Sort
					return sorted(lowerCAmelCase__				,    key=lambda lowerCAmelCase__	: s["title"].lower()	)



def  UpperCamelCase					(							lowerCAmelCase__=False	):
					'''simple docstring'''
					with open(lowerCAmelCase__				,    encoding='''utf-8'''	) as f:
										lowercase					=		yaml.safe_load(f.read()	)

					# Get to the API doc
					lowercase					=		0
					while content[api_idx]["title"] != "API":
										api_idx += 1
					lowercase					=		content[api_idx]['''sections''']

					# Then to the model doc
					lowercase					=		0
					while api_doc[model_idx]["title"] != "Models":
										model_idx += 1

					lowercase					=		api_doc[model_idx]['''sections''']

					lowercase					=		[(idx, section) for idx, section in enumerate(lowerCAmelCase__	) if '''sections''' in section]
					lowercase					=		False
					for idx, modality_doc in modalities_docs:
										lowercase					=		modality_doc['''sections''']
										lowercase					=		clean_model_doc_toc(lowerCAmelCase__	)

										if old_modality_doc != new_modality_doc:
															lowercase					=		True
															if overwrite:
																				lowercase					=		new_modality_doc

					if diff:
										if overwrite:
															lowercase					=		model_doc
															lowercase					=		api_doc
															with open(lowerCAmelCase__				,    '''w'''				,    encoding='''utf-8'''	) as f:
																				f.write(yaml.dump(lowerCAmelCase__				,    allow_unicode=lowerCAmelCase__	)	)
										else:
															raise ValueError(
															    '''The model doc part of the table of content is not properly sorted, run `make style` to fix this.'''	)


if __name__ == "__main__":
							lowercase__	:Any										=					argparse.ArgumentParser()
							parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
							lowercase__	:int										=					parser.parse_args()

							check_model_doc(args.fix_and_overwrite)




