wehub-resource-sync
144 lines
5.6 KiB
C++
144 lines
5.6 KiB
C++
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/phi/common/scalar.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/infermeta/unary.h"
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namespace phi {
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#define DECLARE_ACTIVATION_KERNEL(name) \
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template <typename T, typename Context> \
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void name##Kernel( \
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const Context& dev_ctx, const DenseTensor& x, DenseTensor* out);
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#define DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(name, attr) \
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template <typename T, typename Context> \
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void name##Kernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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float attr, \
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DenseTensor* out);
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#define DECLARE_ACTIVATION_KERNEL_WITH_ONE_DOUBLE_ATTRS(name, attr) \
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template <typename T, typename Context> \
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void name##Kernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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double attr, \
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DenseTensor* out);
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#define DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(name, attr1, attr2) \
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template <typename T, typename Context> \
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void name##Kernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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float attr1, \
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float attr2, \
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DenseTensor* out);
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#define DECLARE_ACTIVATION_KERNEL_WITH_TWO_DOUBLE_ATTRS(name, attr1, attr2) \
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template <typename T, typename Context> \
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void name##Kernel(const Context& dev_ctx, \
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const DenseTensor& x, \
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double attr1, \
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double attr2, \
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DenseTensor* out);
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DECLARE_ACTIVATION_KERNEL(Sin)
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DECLARE_ACTIVATION_KERNEL(Cos)
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DECLARE_ACTIVATION_KERNEL(Tan)
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DECLARE_ACTIVATION_KERNEL(Asin)
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DECLARE_ACTIVATION_KERNEL(Atan)
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DECLARE_ACTIVATION_KERNEL(Acos)
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DECLARE_ACTIVATION_KERNEL(Sinh)
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DECLARE_ACTIVATION_KERNEL(Cosh)
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DECLARE_ACTIVATION_KERNEL(Asinh)
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DECLARE_ACTIVATION_KERNEL(Acosh)
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DECLARE_ACTIVATION_KERNEL(Atanh)
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DECLARE_ACTIVATION_KERNEL(Relu)
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DECLARE_ACTIVATION_KERNEL(Tanh)
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DECLARE_ACTIVATION_KERNEL(TanhShrink)
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DECLARE_ACTIVATION_KERNEL(Silu)
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DECLARE_ACTIVATION_KERNEL(Exp)
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DECLARE_ACTIVATION_KERNEL(Expm1)
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DECLARE_ACTIVATION_KERNEL(Reciprocal)
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DECLARE_ACTIVATION_KERNEL(Square)
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DECLARE_ACTIVATION_KERNEL(Sqrt)
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DECLARE_ACTIVATION_KERNEL(Rsqrt)
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DECLARE_ACTIVATION_KERNEL(Softsign)
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DECLARE_ACTIVATION_KERNEL(Sigmoid)
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DECLARE_ACTIVATION_KERNEL(LogSigmoid)
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DECLARE_ACTIVATION_KERNEL(Log)
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DECLARE_ACTIVATION_KERNEL(Log2)
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DECLARE_ACTIVATION_KERNEL(Log10)
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DECLARE_ACTIVATION_KERNEL(Log1p)
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DECLARE_ACTIVATION_KERNEL(Floor)
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DECLARE_ACTIVATION_KERNEL(Ceil)
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DECLARE_ACTIVATION_KERNEL(Negative)
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DECLARE_ACTIVATION_KERNEL_WITH_ONE_DOUBLE_ATTRS(LeakyRelu, alpha)
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DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(SoftShrink, lambda)
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DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(Mish, threshold)
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DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(HardShrink, threshold)
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DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(SoftShrink, lambda)
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DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(Elu, alpha)
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DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(Celu, alpha)
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DECLARE_ACTIVATION_KERNEL_WITH_ONE_DOUBLE_ATTRS(Logit, eps)
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DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(HardTanh, t_min, t_max)
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DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(Stanh, scale_a, scale_b)
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DECLARE_ACTIVATION_KERNEL_WITH_TWO_DOUBLE_ATTRS(Softplus, beta, threshold)
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DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(HardSigmoid, slope, offset)
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DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(ThresholdedRelu, threshold, value)
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template <typename T, typename Context>
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void HardSwishKernel(const Context& dev_ctx,
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const DenseTensor& x,
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DenseTensor* out);
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template <typename T, typename Context>
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void Relu6Kernel(const Context& dev_ctx,
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const DenseTensor& x,
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DenseTensor* out);
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template <typename T, typename Context>
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void RoundKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const int decimals,
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DenseTensor* out);
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template <typename T, typename Context>
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void SwishKernel(const Context& dev_ctx,
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const DenseTensor& x,
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DenseTensor* out);
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template <typename T, typename Context>
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void PowKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const Scalar& factor,
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DenseTensor* out);
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template <typename T, typename Context>
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DenseTensor Pow(const Context& dev_ctx,
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const DenseTensor& x,
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const Scalar& factor) {
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DenseTensor out;
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MetaTensor meta_out(out);
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UnchangedInferMeta(x, &meta_out);
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PowKernel<T, Context>(dev_ctx, x, factor, &out);
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return out;
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}
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} // namespace phi
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