MindSpore-AKG/python/akg/ops/math_gpu/reduce_sum.py

# Copyright 2020 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 reduce_sum(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)

    in_dtype = inputs.dtype
    if in_dtype == 'float16':
        inputs = akg.topi.cast(inputs, 'float32')

    output = akg.topi.sum(inputs, axis=axis, keepdims=keepdims)
    
    if in_dtype == 'float16':
        output = akg.topi.cast(output, 'float16')

    return output