import inspect
import os

import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed

import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils.testing import (
    AccelerateTestCase,
    TempDirTestCase,
    execute_subprocess_async,
    require_cuda,
    require_fsdp,
    require_multi_gpu,
    slow,
)
from accelerate.utils.constants import (
    FSDP_AUTO_WRAP_POLICY,
    FSDP_BACKWARD_PREFETCH,
    FSDP_SHARDING_STRATEGY,
    FSDP_STATE_DICT_TYPE,
)
from accelerate.utils.dataclasses import FullyShardedDataParallelPlugin
from accelerate.utils.other import patch_environment


set_seed(4_2)

_lowercase				:   List[str]   				='bert-base-cased'
_lowercase				:   Optional[int]   				='fp16'
_lowercase				:   str   				='bf16'
_lowercase				:   List[str]   				=[FPaa, BFaa]



@require_fsdp
@require_cuda
class 			SCREAMING_SNAKE_CASE_			(       _lowerCamelCase      ):
  '''simple docstring'''


  def 		SCREAMING_SNAKE_CASE_		(					self     :       Optional[int]  )     ->					Optional[int]:
         super().setUp()

         A    :  List[Any]								=dict(
             ACCELERATE_USE_FSDP='true'   ,						MASTER_ADDR='localhost'   ,						MASTER_PORT='10999'   ,						RANK='0'   ,						LOCAL_RANK='0'   ,						WORLD_SIZE='1'   ,						)







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Tuple  )     ->					List[Any]:
         from torch.distributed.fsdp.fully_sharded_data_parallel import ShardingStrategy

         for i, strategy in enumerate(_SCREAMING_SNAKE_CASE  ):
                A    :  Optional[Any]								=self.dist_env.copy()
                A    :  Dict								=f'{i + 1}'
                A    :  Tuple								=strategy
                with mockenv_context(**_SCREAMING_SNAKE_CASE  ):
                       A    :  List[str]								=FullyShardedDataParallelPlugin()
                       self.assertEqual(fsdp_plugin.sharding_strategy   ,						ShardingStrategy(i + 1  )  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       List[Any]  )     ->					Dict:
         from torch.distributed.fsdp.fully_sharded_data_parallel import BackwardPrefetch

         for i, prefetch_policy in enumerate(_SCREAMING_SNAKE_CASE  ):
                A    :  str								=self.dist_env.copy()
                A    :  List[str]								=prefetch_policy
                with mockenv_context(**_SCREAMING_SNAKE_CASE  ):
                       A    :  List[Any]								=FullyShardedDataParallelPlugin()
                       if prefetch_policy == "NO_PREFETCH":
                              self.assertIsNone(fsdp_plugin.backward_prefetch  )
                       else:
                              self.assertEqual(fsdp_plugin.backward_prefetch   ,						BackwardPrefetch(i + 1  )  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Union[str, Any]  )     ->					str:
         from torch.distributed.fsdp.fully_sharded_data_parallel import StateDictType

         for i, state_dict_type in enumerate(_SCREAMING_SNAKE_CASE  ):
                A    :  Any								=self.dist_env.copy()
                A    :  Optional[Any]								=state_dict_type
                with mockenv_context(**_SCREAMING_SNAKE_CASE  ):
                       A    :  Optional[Any]								=FullyShardedDataParallelPlugin()
                       self.assertEqual(fsdp_plugin.state_dict_type   ,						StateDictType(i + 1  )  )
                       if state_dict_type == "FULL_STATE_DICT":
                              self.assertTrue(fsdp_plugin.state_dict_config.offload_to_cpu  )
                              self.assertTrue(fsdp_plugin.state_dict_config.ranka_only  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Any  )     ->					Dict:
         A    :  Any								=AutoModel.from_pretrained(_SCREAMING_SNAKE_CASE  )
         for policy in FSDP_AUTO_WRAP_POLICY:
                A    :  Optional[Any]								=self.dist_env.copy()
                A    :  Union[str, Any]								=policy
                if policy == "TRANSFORMER_BASED_WRAP":
                       A    :  Tuple								='BertLayer'
                elif policy == "SIZE_BASED_WRAP":
                       A    :  Union[str, Any]								='2000'
                with mockenv_context(**_SCREAMING_SNAKE_CASE  ):
                       A    :  Optional[Any]								=FullyShardedDataParallelPlugin()
                       fsdp_plugin.set_auto_wrap_policy(_SCREAMING_SNAKE_CASE  )
                       if policy == "NO_WRAP":
                              self.assertIsNone(fsdp_plugin.auto_wrap_policy  )
                       else:
                              self.assertIsNotNone(fsdp_plugin.auto_wrap_policy  )

         A    :  int								=self.dist_env.copy()
         A    :  Any								='TRANSFORMER_BASED_WRAP'
         A    :  str								='T5Layer'
         with mockenv_context(**_SCREAMING_SNAKE_CASE  ):
                A    :  List[Any]								=FullyShardedDataParallelPlugin()
                with self.assertRaises(_SCREAMING_SNAKE_CASE  ) as cm:
                       fsdp_plugin.set_auto_wrap_policy(_SCREAMING_SNAKE_CASE  )
                self.assertTrue('Could not find the transformer layer class to wrap in the model.' in str(cm.exception  )  )

         A    :  Optional[Any]								=self.dist_env.copy()
         A    :  Optional[int]								='SIZE_BASED_WRAP'
         A    :  List[Any]								='0'
         with mockenv_context(**_SCREAMING_SNAKE_CASE  ):
                A    :  List[Any]								=FullyShardedDataParallelPlugin()
                fsdp_plugin.set_auto_wrap_policy(_SCREAMING_SNAKE_CASE  )
                self.assertIsNone(fsdp_plugin.auto_wrap_policy  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       int  )     ->					str:
         from torch.distributed.fsdp.fully_sharded_data_parallel import MixedPrecision
         from torch.distributed.fsdp.sharded_grad_scaler import ShardedGradScaler

         for mp_dtype in dtypes:
                A    :  int								=self.dist_env.copy()
                A    :  List[Any]								=mp_dtype
                with mockenv_context(**_SCREAMING_SNAKE_CASE  ):
                       A    :  Any								=Accelerator()
                       if mp_dtype == "fp16":
                              A    :  int								=torch.floataa
                       elif mp_dtype == "bf16":
                              A    :  int								=torch.bfloataa
                       A    :  Tuple								=MixedPrecision(param_dtype=_SCREAMING_SNAKE_CASE   ,						reduce_dtype=_SCREAMING_SNAKE_CASE   ,						buffer_dtype=_SCREAMING_SNAKE_CASE  )
                       self.assertEqual(accelerator.state.fsdp_plugin.mixed_precision_policy   ,						_SCREAMING_SNAKE_CASE  )
                       if mp_dtype == FPaa:
                              self.assertTrue(isinstance(accelerator.scaler   ,						_SCREAMING_SNAKE_CASE  )  )
                       elif mp_dtype == BFaa:
                              self.assertIsNone(accelerator.scaler  )
                       AcceleratorState._reset_state(_SCREAMING_SNAKE_CASE  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Tuple  )     ->					str:
         from torch.distributed.fsdp.fully_sharded_data_parallel import CPUOffload

         for flag in [True, False]:
                A    :  Optional[int]								=self.dist_env.copy()
                A    :  List[Any]								=str(_SCREAMING_SNAKE_CASE  ).lower()
                with mockenv_context(**_SCREAMING_SNAKE_CASE  ):
                       A    :  Optional[int]								=FullyShardedDataParallelPlugin()
                       self.assertEqual(fsdp_plugin.cpu_offload   ,						CPUOffload(offload_params=_SCREAMING_SNAKE_CASE  )  )







@require_fsdp
@require_multi_gpu
@slow
class 			SCREAMING_SNAKE_CASE_			(       _lowerCamelCase      ):
  '''simple docstring'''


  def 		SCREAMING_SNAKE_CASE_		(					self     :       List[str]  )     ->					Dict:
         super().setUp()
         A    :  Dict								=0.8_2
         A    :  Union[str, Any]								=[
             'fsdp_shard_grad_op_transformer_based_wrap',
             'fsdp_full_shard_transformer_based_wrap',
         ]
         A    :  Tuple								={
             'multi_gpu_fp16': 32_00,
             'fsdp_shard_grad_op_transformer_based_wrap_fp16': 20_00,
             'fsdp_full_shard_transformer_based_wrap_fp16': 19_00,
             # Disabling below test as it overwhelms the RAM memory usage
             # on CI self-hosted runner leading to tests getting killed.
             # "fsdp_full_shard_cpu_offload_transformer_based_wrap_fp32": 1500,  # fp16 was leading to indefinite hang
         }
         A    :  Optional[Any]								=1_60
         A    :  Tuple								=1_60

         A    :  List[str]								=inspect.getfile(accelerate.test_utils  )
         A    :  Dict								=os.path.sep.join(mod_file.split(os.path.sep  )[:-1] + ['scripts', 'external_deps']  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Optional[int]  )     ->					Dict:
         A    :  List[str]								=os.path.join(self.test_scripts_folder   ,						'test_performance.py'  )
         A    :  List[str]								=['accelerate', 'launch', '--num_processes=2', '--num_machines=1', '--machine_rank=0', '--use_fsdp']
         for config in self.performance_configs:
                A    :  int								=cmd.copy()
                for i, strategy in enumerate(_SCREAMING_SNAKE_CASE  ):
                       if strategy.lower() in config:
                              cmd_config.append(f'--fsdp_sharding_strategy={i+1}'  )
                              break

                if "fp32" in config:
                       cmd_config.append('--mixed_precision=no'  )
                else:
                       cmd_config.append('--mixed_precision=fp16'  )

                if "cpu_offload" in config:
                       cmd_config.append('--fsdp_offload_params=True'  )

                for policy in FSDP_AUTO_WRAP_POLICY:
                       if policy.lower() in config:
                              cmd_config.append(f'--fsdp_auto_wrap_policy={policy}'  )
                              break

                if policy == "TRANSFORMER_BASED_WRAP":
                       cmd_config.append('--fsdp_transformer_layer_cls_to_wrap=BertLayer'  )
                elif policy == "SIZE_BASED_WRAP":
                       cmd_config.append('--fsdp_min_num_params=2000'  )

                cmd_config.extend(
                    [
                        self.test_file_path,
                        f'--output_dir={self.tmpdir}',
                        f'--performance_lower_bound={self.performance_lower_bound}',
                    ]  )
                with patch_environment(omp_num_threads=1  ):
                       execute_subprocess_async(_SCREAMING_SNAKE_CASE   ,						env=os.environ.copy()  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Optional[int]  )     ->					Any:
         A    :  Any								=os.path.join(self.test_scripts_folder   ,						'test_checkpointing.py'  )
         A    :  Any								=[
             'accelerate',
             'launch',
             '--num_processes=2',
             '--num_machines=1',
             '--machine_rank=0',
             '--use_fsdp',
             '--mixed_precision=fp16',
             '--fsdp_transformer_layer_cls_to_wrap=BertLayer',
         ]

         for i, strategy in enumerate(_SCREAMING_SNAKE_CASE  ):
                A    :  int								=cmd.copy()
                cmd_config.append(f'--fsdp_sharding_strategy={i+1}'  )
                if strategy != "FULL_SHARD":
                       continue
                A    :  Optional[int]								=len(_SCREAMING_SNAKE_CASE  )
                for state_dict_type in FSDP_STATE_DICT_TYPE:
                       A    :  Dict								=cmd_config[:state_dict_config_index]
                       cmd_config.append(f'--fsdp_state_dict_type={state_dict_type}'  )
                       cmd_config.extend(
                           [
                               self.test_file_path,
                               f'--output_dir={self.tmpdir}',
                               '--partial_train_epoch=1',
                           ]  )
                       with patch_environment(omp_num_threads=1  ):
                              execute_subprocess_async(_SCREAMING_SNAKE_CASE   ,						env=os.environ.copy()  )

                       A    :  Tuple								=cmd_config[:-1]
                       A    :  str								=os.path.join(self.tmpdir   ,						'epoch_0'  )
                       cmd_config.extend(
                           [
                               f'--resume_from_checkpoint={resume_from_checkpoint}',
                           ]  )
                       with patch_environment(omp_num_threads=1  ):
                              execute_subprocess_async(_SCREAMING_SNAKE_CASE   ,						env=os.environ.copy()  )







  def 		SCREAMING_SNAKE_CASE_		(					self     :       str  )     ->					str:
         A    :  Tuple								=os.path.join(self.test_scripts_folder   ,						'test_peak_memory_usage.py'  )
         A    :  str								=[
             'accelerate',
             'launch',
             '--num_processes=2',
             '--num_machines=1',
             '--machine_rank=0',
         ]
         for spec, peak_mem_upper_bound in self.peak_memory_usage_upper_bound.items():
                A    :  Union[str, Any]								=cmd.copy()
                if "fp16" in spec:
                       cmd_config.extend(['--mixed_precision=fp16']  )
                else:
                       cmd_config.extend(['--mixed_precision=no']  )

                if "multi_gpu" in spec:
                       continue
                else:
                       cmd_config.extend(['--use_fsdp']  )
                       for i, strategy in enumerate(_SCREAMING_SNAKE_CASE  ):
                              if strategy.lower() in spec:
                                     cmd_config.append(f'--fsdp_sharding_strategy={i+1}'  )
                                     break

                       if "cpu_offload" in spec:
                              cmd_config.append('--fsdp_offload_params=True'  )

                       for policy in FSDP_AUTO_WRAP_POLICY:
                              if policy.lower() in spec:
                                     cmd_config.append(f'--fsdp_auto_wrap_policy={policy}'  )
                                     break

                       if policy == "TRANSFORMER_BASED_WRAP":
                              cmd_config.append('--fsdp_transformer_layer_cls_to_wrap=BertLayer'  )
                       elif policy == "SIZE_BASED_WRAP":
                              cmd_config.append('--fsdp_min_num_params=2000'  )

                cmd_config.extend(
                    [
                        self.test_file_path,
                        f'--output_dir={self.tmpdir}',
                        f'--peak_memory_upper_bound={peak_mem_upper_bound}',
                        f'--n_train={self.n_train}',
                        f'--n_val={self.n_val}',
                    ]  )
                with patch_environment(omp_num_threads=1  ):
                       execute_subprocess_async(_SCREAMING_SNAKE_CASE   ,						env=os.environ.copy()  )











"""simple docstring"""

def  __snake_case							(	__A      :						list							,		__A      :						int							,		__A      :						int = 0							,		__A      :						int = 0     )     ->       int:






				'''simple docstring'''
				SCREAMING_SNAKE_CASE						:							Any							=     right or len(__A     ) - 1
				if left > right:
								return -1
				elif list_data[left] == key:
								return left
				elif list_data[right] == key:
								return right
				else:
								return search(__A							,		__A							,		left + 1							,		right - 1     )


if __name__ == "__main__":
							import doctest

							doctest.testmod()





