|
- # Copyright 2019 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
-
- """operator dsl function: sum"""
-
- import _akg.topi
- import _akg.tvm
- from _akg.utils import format_transform as ft_util
- from _akg.utils import validation_check as vc_util
-
-
- @vc_util.check_input_type(_akg.tvm.tensor.Tensor, (list, tuple, int, type(None)), (bool, type(None)))
- def sum_value(inputs, axis=None, keepdims=False):
- """
- Compute the sum of elements across dimensions of a tensor.
-
- Args:
- inputs (tvm.tensor.Tensor): Tensor.
- axis (Union[list, tuple, int, None]): If the list or tuple is empty, the axis equal to None.
- keepdims (bool): If keepdims equal to True, the result shape length is same to input shape length.
-
- Returns:
- tvm.tensor.Tensor, has same type as input. If keepdims is True, all reduced dimensions are retained
- with length 1, else these reduced axis will be eliminate.
- """
- axis = ft_util.refine_reduce_axis(inputs, axis)
- vc_util.check_shape(inputs.shape)
-
- if not axis:
- output = _akg.topi.identity(inputs)
- else:
- output = _akg.topi.sum(inputs, axis=axis, keepdims=keepdims)
-
- return output
|
