






"""simple docstring"""





import baseaa
import io
import json
import os
from copy import deepcopy

from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler


class      _lowercase :


      def __init__(    self				:	Optional[Any]							,   a				:	str						):





            """simple docstring"""







            if isinstance(lowerCAmelCase_							,   lowerCAmelCase_						):
                  # Don't modify user's data should they want to reuse it (e.g. in tests), because once we
                  # modified it, it will not be accepted here again, since `auto` values would have been overridden
                  __snake_case      :    Dict  			=deepcopy(lowerCAmelCase_						)
            elif os.path.exists(lowerCAmelCase_						):
                  with io.open(lowerCAmelCase_							,   '''r'''							,   encoding='''utf-8'''						) as f:
                        __snake_case      :    List[str]  			=json.load(lowerCAmelCase_						)
            else:
                  try:
                        __snake_case      :    str  			=baseaa.urlsafe_baadecode(lowerCAmelCase_						).decode('''utf-8'''						)
                        __snake_case      :    List[Any]  			=json.loads(lowerCAmelCase_						)
                  except (UnicodeDecodeError, AttributeError, ValueError):
                        raise ValueError(
                            f'''Expected a string path to an existing deepspeed config, or a dictionary, or a base64 encoded string. Received: {config_file_or_dict}'''						)

            __snake_case      :    Any  			=config

            self.set_stage_and_offload()


      def _UpperCamelCase						(    self				:	Any						):





            """simple docstring"""







            __snake_case      :    List[Any]  			=self.get_value('''zero_optimization.stage'''							,   -1						)

            # offload
            __snake_case      :    str  			=False
            if self.is_zeroa() or self.is_zeroa():
                  __snake_case      :    int  			=set(['''cpu''', '''nvme''']						)
                  __snake_case      :    List[Any]  			=set(
                      [
                          self.get_value('''zero_optimization.offload_optimizer.device'''						),
                          self.get_value('''zero_optimization.offload_param.device'''						),
                      ]						)
                  if len(offload_devices & offload_devices_valid						) > 0:
                        __snake_case      :    Optional[int]  			=True


      def _UpperCamelCase						(    self				:	Optional[Any]							,   a				:	Any						):





            """simple docstring"""







            __snake_case      :    Tuple  			=self.config

            # find the config node of interest if it exists
            __snake_case      :    Optional[Any]  			=ds_key_long.split('''.'''						)
            __snake_case      :    Any  			=nodes.pop()
            for node in nodes:
                  __snake_case      :    Tuple  			=config.get(lowerCAmelCase_						)
                  if config is None:
                        return None, ds_key

            return config, ds_key


      def _UpperCamelCase						(    self				:	Tuple							,   a				:	Dict							,   a				:	Tuple=None						):





            """simple docstring"""







            __snake_case			,				__snake_case      :    Union[str, Any]  			=self.find_config_node(lowerCAmelCase_						)
            if config is None:
                  return default
            return config.get(lowerCAmelCase_							,   lowerCAmelCase_						)


      def _UpperCamelCase						(    self				:	Dict							,   a				:	Optional[Any]							,   a				:	Optional[Any]=False						):





            """simple docstring"""







            __snake_case      :    str  			=self.config

            # find the config node of interest if it exists
            __snake_case      :    List[Any]  			=ds_key_long.split('''.'''						)
            for node in nodes:
                  __snake_case      :    Any  			=config
                  __snake_case      :    Tuple  			=config.get(lowerCAmelCase_						)
                  if config is None:
                        if must_exist:
                              raise ValueError(f'''Can\'t find {ds_key_long} entry in the config: {self.config}'''						)
                        else:
                              return

                  # if found remove it
            if parent_config is not None:
                  parent_config.pop(lowerCAmelCase_						)


      def _UpperCamelCase						(    self				:	Union[str, Any]							,   a				:	Tuple						):





            """simple docstring"""







            __snake_case      :    Union[str, Any]  			=self.get_value(lowerCAmelCase_						)
            return False if value is None else bool(lowerCAmelCase_						)


      def _UpperCamelCase						(    self				:	List[Any]							,   a				:	Tuple						):





            """simple docstring"""







            __snake_case      :    List[Any]  			=self.get_value(lowerCAmelCase_						)
            return False if value is None else not bool(lowerCAmelCase_						)


      def _UpperCamelCase						(    self				:	List[Any]						):





            """simple docstring"""







            return self._stage == 2


      def _UpperCamelCase						(    self				:	str						):





            """simple docstring"""







            return self._stage == 3







      def _UpperCamelCase						(    self				:	Any						):





            """simple docstring"""







            return self._offload



class      _lowercase :


      def __init__(    self				:	Any							,   a				:	str						):





            """simple docstring"""







            __snake_case      :    int  			=engine







      def _UpperCamelCase						(    self				:	Any							,   a				:	str							,   **a				:	str						):





            """simple docstring"""







            self.engine.backward(lowerCAmelCase_							,   **lowerCAmelCase_						)

            # Deepspeed's `engine.step` performs the following operations:
            # - gradient accumulation check
            # - gradient clipping
            # - optimizer step
            # - zero grad
            # - checking overflow
            # - lr_scheduler step (only if engine.lr_scheduler is not None)
            self.engine.step()
            # and this plugin overrides the above calls with no-ops when Accelerate runs under
            # Deepspeed, but allows normal functionality for non-Deepspeed cases thus enabling a simple
            # training loop that works transparently under many training regimes.



class      _lowercase (     __UpperCAmelCase ):


      def __init__(    self				:	List[Any]							,   a				:	str						):





            """simple docstring"""







            super().__init__(lowerCAmelCase_							,   device_placement=lowerCAmelCase_							,   scaler=lowerCAmelCase_						)
            __snake_case      :    Optional[int]  			=hasattr(self.optimizer							,   '''overflow'''						)


      def _UpperCamelCase						(    self				:	Any							,   a				:	List[Any]=None						):





            """simple docstring"""







            pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed


      def _UpperCamelCase						(    self				:	Tuple						):





            """simple docstring"""







            pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed







      @property
      def _UpperCamelCase						(    self				:	Optional[Any]						):





            """simple docstring"""







            if self.__has_overflow__:
                  return self.optimizer.overflow
            return False



class      _lowercase (     __UpperCAmelCase ):


      def __init__(    self				:	Optional[Any]							,   a				:	Union[str, Any]							,   a				:	int						):





            """simple docstring"""







            super().__init__(lowerCAmelCase_							,   lowerCAmelCase_						)







      def _UpperCamelCase						(    self				:	Tuple						):





            """simple docstring"""







            pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed



class      _lowercase :


      def __init__(    self				:	Union[str, Any]							,   a				:	Any							,   a				:	Any=0.0_0_1							,   a				:	Optional[int]=0							,   **a				:	Optional[int]						):





            """simple docstring"""







            __snake_case      :    Dict  			=params
            __snake_case      :    Any  			=lr
            __snake_case      :    Optional[Any]  			=weight_decay
            __snake_case      :    Tuple  			=kwargs



class      _lowercase :


      def __init__(    self				:	str							,   a				:	Dict							,   a				:	str=None							,   a				:	Dict=0							,   **a				:	Optional[Any]						):





            """simple docstring"""







            __snake_case      :    str  			=optimizer
            __snake_case      :    Optional[Any]  			=total_num_steps
            __snake_case      :    Optional[int]  			=warmup_num_steps
            __snake_case      :    Optional[int]  			=kwargs










"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase_	:				Any										= {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ReformerConfig"""]}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase_	:				List[str]										= ["""ReformerTokenizer"""]

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase_	:				List[str]										= ["""ReformerTokenizerFast"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase_	:				Optional[int]										= [
        """REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """ReformerAttention""",
        """ReformerForMaskedLM""",
        """ReformerForQuestionAnswering""",
        """ReformerForSequenceClassification""",
        """ReformerLayer""",
        """ReformerModel""",
        """ReformerModelWithLMHead""",
        """ReformerPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_reformer import ReformerTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_reformer_fast import ReformerTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_reformer import (
            REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            ReformerAttention,
            ReformerForMaskedLM,
            ReformerForQuestionAnswering,
            ReformerForSequenceClassification,
            ReformerLayer,
            ReformerModel,
            ReformerModelWithLMHead,
            ReformerPreTrainedModel,
        )

else:
    import sys

    UpperCamelCase_	:				Tuple										= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


