






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


snake_case__   :						List[str]													=   get_logger(__name__)






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

         dist_cp.save_state_dict(
             state_dict=__lowercase     ,   storage_writer=dist_cp.FileSystemWriter(__lowercase)     ,   planner=DefaultSavePlanner()     ,   )
         logger.info(f"""Model saved to {ckpt_dir}""")






def      _snake_case     (__lowercase     ,   __lowercase     ,   __lowercase     ,   __lowercase     ,   __lowercase=0):
   accelerator.wait_for_everyone()
   with FSDP.state_dict_type(
       __lowercase     ,   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(__lowercase) != 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
         UpperCamelCase_						=  f"""{MODEL_NAME}.bin""" if model_index == 0 else f"""{MODEL_NAME}_{model_index}.bin"""
         UpperCamelCase_						=  os.path.join(__lowercase     ,   __lowercase)
         logger.info(f"""Loading model from {input_model_file}""")
         UpperCamelCase_						=  torch.load(__lowercase)
         logger.info(f"""Model loaded from {input_model_file}""")
      elif fsdp_plugin.state_dict_type == StateDictType.LOCAL_STATE_DICT:
         UpperCamelCase_						=  (
             f"""{MODEL_NAME}_rank{accelerator.process_index}.bin"""
             if model_index == 0
             else f"""{MODEL_NAME}_{model_index}_rank{accelerator.process_index}.bin"""
         )
         UpperCamelCase_						=  os.path.join(__lowercase     ,   __lowercase)
         logger.info(f"""Loading model from {input_model_file}""")
         UpperCamelCase_						=  torch.load(__lowercase)
         logger.info(f"""Model loaded from {input_model_file}""")
      elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
         UpperCamelCase_						=  (
             os.path.join(__lowercase     ,   f"""{MODEL_NAME}_{model_index}""")
             if f"""{MODEL_NAME}""" not in input_dir
             else input_dir
         )
         logger.info(f"""Loading model from {ckpt_dir}""")
         UpperCamelCase_						=  {'model': model.state_dict()}
         dist_cp.load_state_dict(
             state_dict=__lowercase     ,   storage_reader=dist_cp.FileSystemReader(__lowercase)     ,   planner=DefaultLoadPlanner()     ,   )
         UpperCamelCase_						=  state_dict['model']
         logger.info(f"""Model loaded from {ckpt_dir}""")
      model.load_state_dict(__lowercase)






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






def      _snake_case     (__lowercase     ,   __lowercase     ,   __lowercase     ,   __lowercase     ,   __lowercase     ,   __lowercase=0):
   accelerator.wait_for_everyone()
   with FSDP.state_dict_type(
       __lowercase     ,   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:
         UpperCamelCase_						=  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:
         UpperCamelCase_						=  (
             f"""{OPTIMIZER_NAME}.bin""" if optimizer_index == 0 else f"""{OPTIMIZER_NAME}_{optimizer_index}.bin"""
         )
         UpperCamelCase_						=  os.path.join(__lowercase     ,   __lowercase)
         logger.info(f"""Loading Optimizer state from {input_optimizer_file}""")
         UpperCamelCase_						=  torch.load(__lowercase)
         logger.info(f"""Optimizer state loaded from {input_optimizer_file}""")
      else:
         UpperCamelCase_						=  (
             os.path.join(__lowercase     ,   f"""{OPTIMIZER_NAME}_{optimizer_index}""")
             if f"""{OPTIMIZER_NAME}""" not in input_dir
             else input_dir
         )
         logger.info(f"""Loading Optimizer from {ckpt_dir}""")
         UpperCamelCase_						=  load_sharded_optimizer_state_dict(
             model_state_dict=model.state_dict()     ,   optimizer_key='optimizer'     ,   storage_reader=dist_cp.FileSystemReader(__lowercase)     ,   )
         UpperCamelCase_						=  optim_state['optimizer']
         logger.info(f"""Optimizer loaded from {ckpt_dir}""")
      UpperCamelCase_						=  FSDP.optim_state_dict_to_load(__lowercase     ,   __lowercase     ,   __lowercase)
      optimizer.load_state_dict(__lowercase)













import numpy as np






def      _snake_case     (__lowercase):
   return 1 / (1 + np.exp(-vector))






def      _snake_case     (__lowercase):
   return vector * sigmoid(__lowercase)


if __name__ == "__main__":
 import doctest

 doctest.testmod()





