repo_description: MindSpore +  🤗Huggingface: Run any Transformers/Diffusers model on MindSpore with seamless compatibility and acceleration.
repo_topics: deep-learning diffusion-models huggingface large-language-models llm mindspore natural-language-processing nlp nlp-library python vlm
code: from builtins import (  # noqa: F401
      bool as _bool,
      bytes as _bytes,
      complex as _complex,
      float as _float,
      int as _int,
      str as _str,
  )
  import mindspore
  from typing import Any, IO, TYPE_CHECKING, Union, Dict, Sequence
  from typing_extensions import Self, TypeAlias
  
  import mindtorch
  from mindtorch import Tensor
  from ._dtype import dtype
  from ._C import device as _device
  
  _TensorOrTensors: TypeAlias = Union[Tensor, Sequence[Tensor]]  # noqa: PYI047
  
  Device: TypeAlias = Union[_device, str, int, None]
  
  # Meta-type for "numeric" things; matches our docs
  Number: TypeAlias = Union[int, float, bool]
  # tuple for isinstance(x, Number) checks.
  # FIXME: refactor once python 3.9 support is dropped.
  _Number = (int, float, bool)
  
  # Storage protocol implemented by ${Type}StorageBase classes
  class Storage:
      _cdata: int
      device: _device
      dtype: dtype
      _torch_load_uninitialized: bool
  
      def __deepcopy__(self, memo: Dict[int, Any]) -> "Storage":
          raise NotImplementedError
  
      def _new_shared(self, size: int) -> "Storage":
          raise NotImplementedError
  
      def _write_file(
          self,
          f: Any,
          is_real_file: bool,
          save_size: bool,
          element_size: int,
      ) -> None:
          raise NotImplementedError
  
      def element_size(self) -> int:
          raise NotImplementedError
  
      def is_shared(self) -> bool:
          raise NotImplementedError
  
      def share_memory_(self) -> "Storage":
          raise NotImplementedError
  
      def nbytes(self) -> int:
          raise NotImplementedError
  
      def cpu(self) -> "Storage":
          raise NotImplementedError
  
      def data_ptr(self) -> int:
          raise NotImplementedError
  
      def from_file(
          self,
          filename: str,
          shared: bool = False,
          nbytes: int = 0,
      ) -> "Storage":
          raise NotImplementedError
  
      def _new_with_file(
          self,
          f: Any,
          element_size: int,
      ) -> "Storage":
          raise NotImplementedError
  
  _dtype = dtype
  _size = tuple