mindspore2022/mindspore/_akg/gpu/relu6_grad.py

# 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.

"""relu6 grad"""
import _akg.topi as topi
import _akg.tvm as tvm

def ReLU6Grad(y_grad, x):
    """
    Computes Gradients of Rectified Linear 6.

    Args:
        y_grad (tvm.tensor.Tensor): Tensor of type float16, float32, gradients backpropagated to the ReLU6 op.
        x (tvm.tensor.Tensor): Tensor of type float16/float32, inputs that where passed to the ReLU6 op, or its outputs.

    Returns:
        tvm.tensor.Tensor, has same type and shape as x.
    """
    shape = x.shape
    dtype = x.dtype

    zero = tvm.const(0, dtype)
    six = tvm.const(6, dtype)

    res0 = tvm.compute(shape, lambda *i: tvm.if_then_else(x(*i) >= zero, x(*i), zero))
    res6 = tvm.compute(shape, lambda *i: tvm.if_then_else(x(*i) >= six, zero, res0(*i)))
    res = tvm.compute(shape, lambda *i: tvm.if_then_else(res6(*i) == zero, zero, y_grad(*i)))
    return res


def gpu_schedule_ReLU6Grad(outs):
    """
    gpu schedule ReLU6Grad.

    Args:
        outs (tvm.tensor.Tensor): outputs of compute.

    Returns:
        sch (schedule.Schedule): The created schedule.
    """
    device = 'cuda'
    ctx = tvm.context(device, 0)
    if not ctx.exist:
        raise SystemError("Skip because %s is not enabled" % device)

    with tvm.target.create(device):
        sch = topi.cuda.schedule_elemwise(outs)
    return sch