Function __get_floats

external/ggml/examples/python/ggml/utils.py:135–150

(tensor: TensorLike)

def __is_contiguous(tensor: TensorLike): return tensor.flags['C_CONTIGUOUS'] if isinstance(tensor, np.ndarray) else lib.ggml_is_contiguous(tensor)

def __get_floats(tensor: TensorLike) -> ffi.CData:
    data, type = __get_data(tensor), __get_type(tensor)
    if type == lib.GGML_TYPE_F32:
        return ffi.cast('float*', data)
    else:
      nelements = __get_nelements(tensor)
      floats = ffi.new('float[]', nelements)
      if type == lib.GGML_TYPE_F16:
          lib.ggml_fp16_to_fp32_row(ffi.cast('uint16_t*', data), floats, nelements)
      elif lib.ggml_is_quantized(type):
          qtype = lib.ggml_internal_get_type_traits(type)
          assert qtype.to_float, f"Type {__type_name(type)} is not supported by ggml"
          qtype.to_float(data, floats, nelements)
      else:
          raise NotImplementedError(f'Cannot read floats from {__describe(tensor)}')
      return floats

def __set_floats(tensor: TensorLike, f32_data: ffi.CData) -> None:
    data, type, nbytes = __get_data(tensor), __get_type(tensor), __get_nbytes(tensor)