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/************************************************************
*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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
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* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
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#ifndef SINGA_UTILS_MATH_KERNEL_H_
#define SINGA_UTILS_MATH_KERNEL_H_
namespace singa {
extern "C" {
void singa_gpu_softmaxloss_forward(int n, int dim, const float *prob,
const int *label, float *loss);
void singa_gpu_softmaxloss_backward(int n, int dim, float scale,
const int *label, float *grad);
void singa_gpu_sum_vec(float *data, float *sum , int n);
void singa_gpu_sum_col(const float *src_mat_data, float *dst_vec_data,
int rows, int cols, int stride);
void singa_gpu_sum_row(const float *src_mat_data, float *dst_vec_data,
int rows, int cols, int stride);
void singa_gpu_add_vec_row(const float *src_vec_data,
const float *src_mat_data, float *des_mat_data,
int rows, int cols, int stride);
void singa_gpu_exp(const float *src_data, float *des_data, int n);
void singa_gpu_log(const float *src_data, float *des_data, int n);
void singa_gpu_sigmoid(const float *src_data, float *des_data, int n);
void singa_gpu_sigmoid_grad(const float *src_data, float *des_data, int n);
void singa_gpu_relu(const float *src_data, float *des_data, int n);
void singa_gpu_relu_grad(const float *src_data, float *des_data, int n);
void singa_gpu_tanh(const float *src_data, float *des_data, int n);
void singa_gpu_tanh_grad(const float *src_data, float *des_data, int n);
void singa_gpu_softplus(const float *src_data, float *des_data, int n);
void singa_gpu_softplus_grad(const float *src_data, float *des_data, int n);
void singa_gpu_square(const float *src_data, float *des_data, int n);
void singa_gpu_square_grad(const float *src_data, float *des_data, int n);
void singa_gpu_sqrt(const float *src_data, float *des_data, int n);
void singa_gpu_pow(const float *src_data_a, const float *src_data_b,
float *des_data, int n);
void singa_gpu_mult(const float *src_data_a, const float *src_data_b,
float *des_data, int n);
void singa_gpu_div(const float *src_data_a, const float *src_data_b,
float *des_data, int n);
void singa_gpu_set_value(float *data, float value, int n);
void singa_gpu_threshold(const float *src_data, float *des_data,
float alpha, int n);
};
} // namespace singa
#endif // SINGA_UTILS_MATH_KERNEL_H_