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


__magic_name__								=get_logger(__name__)







def  __UpperCamelCase    (						A ,							A ,							A ,							A ,							A=0							):
     os.makedirs(A ,							exist_ok=A							)
     with FSDP.state_dict_type(
         A ,							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(A ,							A							)
               if accelerator.process_index == 0:
                    logger.info(f"Saving model to {output_model_file}"							)
                    torch.save(A ,							A							)
                    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(A ,							A							)
               logger.info(f"Saving model to {output_model_file}"							)
               torch.save(A ,							A							)
               logger.info(f"Model saved to {output_model_file}"							)
          elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
               UpperCamelCase__										=      os.path.join(A ,							f"{MODEL_NAME}_{model_index}"							)
               os.makedirs(A ,							exist_ok=A							)
               logger.info(f"Saving model to {ckpt_dir}"							)
               UpperCamelCase__										=      {'''model''': state_dict}

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







def  __UpperCamelCase    (						A ,							A ,							A ,							A ,							A=0							):
     accelerator.wait_for_everyone()
     with FSDP.state_dict_type(
         A ,							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(A							) != 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(A ,							A							)
               logger.info(f"Loading model from {input_model_file}"							)
               UpperCamelCase__										=      torch.load(A							)
               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(A ,							A							)
               logger.info(f"Loading model from {input_model_file}"							)
               UpperCamelCase__										=      torch.load(A							)
               logger.info(f"Model loaded from {input_model_file}"							)
          elif fsdp_plugin.state_dict_type == StateDictType.SHARDED_STATE_DICT:
               UpperCamelCase__										=      (
                   os.path.join(A ,							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=A ,							storage_reader=dist_cp.FileSystemReader(A							) ,							planner=DefaultLoadPlanner() ,							)
               UpperCamelCase__										=      state_dict['''model''']
               logger.info(f"Model loaded from {ckpt_dir}"							)
          model.load_state_dict(A							)







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







def  __UpperCamelCase    (						A ,							A ,							A ,							A ,							A ,							A=0							):
     accelerator.wait_for_everyone()
     with FSDP.state_dict_type(
         A ,							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(A ,							A							)
               logger.info(f"Loading Optimizer state from {input_optimizer_file}"							)
               UpperCamelCase__										=      torch.load(A							)
               logger.info(f"Optimizer state loaded from {input_optimizer_file}"							)
          else:
               UpperCamelCase__										=      (
                   os.path.join(A ,							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(A							) ,							)
               UpperCamelCase__										=      optim_state['''optimizer''']
               logger.info(f"Optimizer loaded from {ckpt_dir}"							)
          UpperCamelCase__										=      FSDP.optim_state_dict_to_load(A ,							A ,							A							)
          optimizer.load_state_dict(A							)




__magic_name__								={
    '''Pillow''': '''Pillow<10.0.0''',
    '''accelerate''': '''accelerate>=0.20.3''',
    '''av''': '''av==9.2.0''',
    '''beautifulsoup4''': '''beautifulsoup4''',
    '''black''': '''black~=23.1''',
    '''codecarbon''': '''codecarbon==1.2.0''',
    '''cookiecutter''': '''cookiecutter==1.7.3''',
    '''dataclasses''': '''dataclasses''',
    '''datasets''': '''datasets!=2.5.0''',
    '''decord''': '''decord==0.6.0''',
    '''deepspeed''': '''deepspeed>=0.9.3''',
    '''diffusers''': '''diffusers''',
    '''dill''': '''dill<0.3.5''',
    '''evaluate''': '''evaluate>=0.2.0''',
    '''fairscale''': '''fairscale>0.3''',
    '''faiss-cpu''': '''faiss-cpu''',
    '''fastapi''': '''fastapi''',
    '''filelock''': '''filelock''',
    '''flax''': '''flax>=0.4.1,<=0.7.0''',
    '''ftfy''': '''ftfy''',
    '''fugashi''': '''fugashi>=1.0''',
    '''GitPython''': '''GitPython<3.1.19''',
    '''hf-doc-builder''': '''hf-doc-builder>=0.3.0''',
    '''huggingface-hub''': '''huggingface-hub>=0.14.1,<1.0''',
    '''importlib_metadata''': '''importlib_metadata''',
    '''ipadic''': '''ipadic>=1.0.0,<2.0''',
    '''isort''': '''isort>=5.5.4''',
    '''jax''': '''jax>=0.2.8,!=0.3.2,<=0.4.13''',
    '''jaxlib''': '''jaxlib>=0.1.65,<=0.4.13''',
    '''jieba''': '''jieba''',
    '''kenlm''': '''kenlm''',
    '''keras-nlp''': '''keras-nlp>=0.3.1''',
    '''librosa''': '''librosa''',
    '''nltk''': '''nltk''',
    '''natten''': '''natten>=0.14.6''',
    '''numpy''': '''numpy>=1.17''',
    '''onnxconverter-common''': '''onnxconverter-common''',
    '''onnxruntime-tools''': '''onnxruntime-tools>=1.4.2''',
    '''onnxruntime''': '''onnxruntime>=1.4.0''',
    '''opencv-python''': '''opencv-python''',
    '''optuna''': '''optuna''',
    '''optax''': '''optax>=0.0.8,<=0.1.4''',
    '''packaging''': '''packaging>=20.0''',
    '''parameterized''': '''parameterized''',
    '''phonemizer''': '''phonemizer''',
    '''protobuf''': '''protobuf''',
    '''psutil''': '''psutil''',
    '''pyyaml''': '''pyyaml>=5.1''',
    '''pydantic''': '''pydantic<2''',
    '''pytest''': '''pytest>=7.2.0''',
    '''pytest-timeout''': '''pytest-timeout''',
    '''pytest-xdist''': '''pytest-xdist''',
    '''python''': '''python>=3.8.0''',
    '''ray[tune]''': '''ray[tune]''',
    '''regex''': '''regex!=2019.12.17''',
    '''requests''': '''requests''',
    '''rhoknp''': '''rhoknp>=1.1.0,<1.3.1''',
    '''rjieba''': '''rjieba''',
    '''rouge-score''': '''rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1''',
    '''ruff''': '''ruff>=0.0.241,<=0.0.259''',
    '''sacrebleu''': '''sacrebleu>=1.4.12,<2.0.0''',
    '''sacremoses''': '''sacremoses''',
    '''safetensors''': '''safetensors>=0.3.1''',
    '''sagemaker''': '''sagemaker>=2.31.0''',
    '''scikit-learn''': '''scikit-learn''',
    '''sentencepiece''': '''sentencepiece>=0.1.91,!=0.1.92''',
    '''sigopt''': '''sigopt''',
    '''starlette''': '''starlette''',
    '''sudachipy''': '''sudachipy>=0.6.6''',
    '''sudachidict_core''': '''sudachidict_core>=20220729''',
    '''tensorflow-cpu''': '''tensorflow-cpu>=2.6,<2.14''',
    '''tensorflow''': '''tensorflow>=2.6,<2.14''',
    '''tensorflow-text''': '''tensorflow-text<2.14''',
    '''tf2onnx''': '''tf2onnx''',
    '''timeout-decorator''': '''timeout-decorator''',
    '''timm''': '''timm''',
    '''tokenizers''': '''tokenizers>=0.11.1,!=0.11.3,<0.14''',
    '''torch''': '''torch>=1.9,!=1.12.0''',
    '''torchaudio''': '''torchaudio''',
    '''torchvision''': '''torchvision''',
    '''pyctcdecode''': '''pyctcdecode>=0.4.0''',
    '''tqdm''': '''tqdm>=4.27''',
    '''unidic''': '''unidic>=1.0.2''',
    '''unidic_lite''': '''unidic_lite>=1.0.7''',
    '''urllib3''': '''urllib3<2.0.0''',
    '''uvicorn''': '''uvicorn''',
}



