Function __set_floats

external/ggml/examples/python/ggml/utils.py:152–165

(tensor: TensorLike, f32_data: ffi.CData)

      return floats

def __set_floats(tensor: TensorLike, f32_data: ffi.CData) -> None:
    data, type, nbytes = __get_data(tensor), __get_type(tensor), __get_nbytes(tensor)
    if type == lib.GGML_TYPE_F32:
        ffi.memmove(data, f32_data, nbytes)
    else:
      nelements = __get_nelements(tensor)
      if type == lib.GGML_TYPE_F16:
          lib.ggml_fp32_to_fp16_row(f32_data, ffi.cast('uint16_t*', data), nelements)
      elif lib.ggml_is_quantized(type):
          qtype = lib.ggml_internal_get_type_traits(type)
          assert qtype.from_float, f"Type {__type_name(type)} is not supported by ggml"
          qtype.from_float(f32_data, data, nelements)
      else:
          raise NotImplementedError(f'Cannot write floats to {__describe(tensor)}')

def __expect_same_layout(name1: str, tensor1: TensorLike, name2: str, tensor2: TensorLike):
    shape1, shape2 = __get_shape(tensor1), __get_shape(tensor2)