

import os

import torch

from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version


if is_torch_version(""">=""", FSDP_PYTORCH_VERSION):
     import torch.distributed.checkpoint as dist_cp
     from torch.distributed.checkpoint.default_planner import DefaultLoadPlanner, DefaultSavePlanner
     from torch.distributed.checkpoint.optimizer import load_sharded_optimizer_state_dict
     from torch.distributed.fsdp.fully_sharded_data_parallel import FullyShardedDataParallel as FSDP
     from torch.distributed.fsdp.fully_sharded_data_parallel import StateDictType


_UpperCAmelCase	:     Union[str, Any]		       = get_logger(__name__)





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__=0   ):







       '''simple docstring'''






       os.makedirs(_snake_case     ,							exist_ok=_snake_case   )
       with FSDP.state_dict_type(
           _snake_case     ,							fsdp_plugin.state_dict_type     ,							fsdp_plugin.state_dict_config     ,							fsdp_plugin.optim_state_dict_config   ):
              snake_case_           =					model.state_dict()
              if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
                     snake_case_           =					F'''{MODEL_NAME}.bin''' if model_index == 0 else F'''{MODEL_NAME}_{model_index}.bin'''
                     snake_case_           =					os.path.join(_snake_case     ,							_snake_case   )
                     if accelerator.process_index == 0:
                            logger.info(F'''Saving model to {output_model_file}'''   )
                            torch.save(_snake_case     ,							_snake_case   )
                            logger.info(F'''Model saved to {output_model_file}'''   )
              elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
                     snake_case_           =					(
                         F'''{MODEL_NAME}_rank{accelerator.process_index}.bin'''
                         if model_index == 0
                         else F'''{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'''
                     )
                     snake_case_           =					os.path.join(_snake_case     ,							_snake_case   )
                     logger.info(F'''Saving model to {output_model_file}'''   )
                     torch.save(_snake_case     ,							_snake_case   )
                     logger.info(F'''Model saved to {output_model_file}'''   )
              elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
                     snake_case_           =					os.path.join(_snake_case     ,							F'''{MODEL_NAME}_{model_index}'''   )
                     os.makedirs(_snake_case     ,							exist_ok=_snake_case   )
                     logger.info(F'''Saving model to {ckpt_dir}'''   )
                     snake_case_           =					{'model': state_dict}

                     dist_cp.save_state_dict(
                         state_dict=_snake_case     ,							storage_writer=dist_cp.FileSystemWriter(_snake_case   )     ,							planner=DefaultSavePlanner()     ,							)
                     logger.info(F'''Model saved to {ckpt_dir}'''   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__=0   ):







       '''simple docstring'''






       accelerator.wait_for_everyone()
       with FSDP.state_dict_type(
           _snake_case     ,							fsdp_plugin.state_dict_type     ,							fsdp_plugin.state_dict_config     ,							fsdp_plugin.optim_state_dict_config   ):
              if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
                     if type(_snake_case   ) != FSDP and accelerator.process_index != 0:
                            if not fsdp_plugin.sync_module_states:
                                   raise ValueError(
                                       'Set the `sync_module_states` flag to `True` so that model states are synced across processes when '
                                       'initializing FSDP object'   )
                            return
                     snake_case_           =					F'''{MODEL_NAME}.bin''' if model_index == 0 else F'''{MODEL_NAME}_{model_index}.bin'''
                     snake_case_           =					os.path.join(_snake_case     ,							_snake_case   )
                     logger.info(F'''Loading model from {input_model_file}'''   )
                     snake_case_           =					torch.load(_snake_case   )
                     logger.info(F'''Model loaded from {input_model_file}'''   )
              elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
                     snake_case_           =					(
                         F'''{MODEL_NAME}_rank{accelerator.process_index}.bin'''
                         if model_index == 0
                         else F'''{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin'''
                     )
                     snake_case_           =					os.path.join(_snake_case     ,							_snake_case   )
                     logger.info(F'''Loading model from {input_model_file}'''   )
                     snake_case_           =					torch.load(_snake_case   )
                     logger.info(F'''Model loaded from {input_model_file}'''   )
              elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
                     snake_case_           =					(
                         os.path.join(_snake_case     ,							F'''{MODEL_NAME}_{model_index}'''   )
                         if F'''{MODEL_NAME}''' not in input_dir
                         else input_dir
                     )
                     logger.info(F'''Loading model from {ckpt_dir}'''   )
                     snake_case_           =					{'model': model.state_dict()}
                     dist_cp.load_state_dict(
                         state_dict=_snake_case     ,							storage_reader=dist_cp.FileSystemReader(_snake_case   )     ,							planner=DefaultLoadPlanner()     ,							)
                     snake_case_           =					state_dict['model']
                     logger.info(F'''Model loaded from {ckpt_dir}'''   )
              model.load_state_dict(_snake_case   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__=0   ):







       '''simple docstring'''






       os.makedirs(_snake_case     ,							exist_ok=_snake_case   )
       with FSDP.state_dict_type(
           _snake_case     ,							fsdp_plugin.state_dict_type     ,							fsdp_plugin.state_dict_config     ,							fsdp_plugin.optim_state_dict_config   ):
              snake_case_           =					FSDP.optim_state_dict(_snake_case     ,							_snake_case   )
              if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
                     if accelerator.process_index == 0:
                            snake_case_           =					(
                                F'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else F'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
                            )
                            snake_case_           =					os.path.join(_snake_case     ,							_snake_case   )
                            logger.info(F'''Saving Optimizer state to {output_optimizer_file}'''   )
                            torch.save(_snake_case     ,							_snake_case   )
                            logger.info(F'''Optimizer state saved in {output_optimizer_file}'''   )
              else:
                     snake_case_           =					os.path.join(_snake_case     ,							F'''{OPTIMIZER_NAME}_{optimizer_index}'''   )
                     os.makedirs(_snake_case     ,							exist_ok=_snake_case   )
                     logger.info(F'''Saving Optimizer state to {ckpt_dir}'''   )
                     dist_cp.save_state_dict(
                         state_dict={'optimizer': optim_state}     ,							storage_writer=dist_cp.FileSystemWriter(_snake_case   )     ,							planner=DefaultSavePlanner()     ,							)
                     logger.info(F'''Optimizer state saved in {ckpt_dir}'''   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__=0   ):







       '''simple docstring'''






       accelerator.wait_for_everyone()
       with FSDP.state_dict_type(
           _snake_case     ,							fsdp_plugin.state_dict_type     ,							fsdp_plugin.state_dict_config     ,							fsdp_plugin.optim_state_dict_config   ):
              if fsdp_plugin.state_dict_type == StateDictType.FULL_STATE_DICT:
                     snake_case_           =					None
                     # below check should work but currently it isn't working (mostly opytorch issue),
                     # in the meantime disabling it at the cost of excess memory usage
                     # if accelerator.process_index == 0 or not fsdp_plugin.optim_state_dict_config.rank0_only:
                     snake_case_           =					(
                         F'''{OPTIMIZER_NAME}.bin''' if optimizer_index == 0 else F'''{OPTIMIZER_NAME}_{optimizer_index}.bin'''
                     )
                     snake_case_           =					os.path.join(_snake_case     ,							_snake_case   )
                     logger.info(F'''Loading Optimizer state from {input_optimizer_file}'''   )
                     snake_case_           =					torch.load(_snake_case   )
                     logger.info(F'''Optimizer state loaded from {input_optimizer_file}'''   )
              else:
                     snake_case_           =					(
                         os.path.join(_snake_case     ,							F'''{OPTIMIZER_NAME}_{optimizer_index}'''   )
                         if F'''{OPTIMIZER_NAME}''' not in input_dir
                         else input_dir
                     )
                     logger.info(F'''Loading Optimizer from {ckpt_dir}'''   )
                     snake_case_           =					load_sharded_optimizer_state_dict(
                         model_state_dict=model.state_dict()     ,							optimizer_key='optimizer'     ,							storage_reader=dist_cp.FileSystemReader(_snake_case   )     ,							)
                     snake_case_           =					optim_state['optimizer']
                     logger.info(F'''Optimizer loaded from {ckpt_dir}'''   )
              snake_case_           =					FSDP.optim_state_dict_to_load(_snake_case     ,							_snake_case     ,							_snake_case   )
              optimizer.load_state_dict(_snake_case   )







# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    """stable diffusion controlnet""",
    """0.22.0""",
    """Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diffusion.flax_pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import FlaxStableDiffusionControlNetPipeline` instead.""",
    standard_warn=False,
    stacklevel=3,
)




