c++ Sigmoid/Softmax/Argmax

Sigmoid

float sigmoid(float x)
{
    return (1 / (1 + exp(-x)));
}

float sigmoid_dy_dz(float x)
{
    return (x * (1.0 - x));
}

float tanh_dy_dz(float x)
{
    return (1.0 - x*x);
}

static inline float Sigmoid(float x) {
return (1 / (1 + exp(-x)));
}

static inline float * Sigmoid(float array[], int32_t size)[] {
float output_array[size];
for (int32_t i = 0; i < size; i++) {
    float x = array[i];
    output_array[i] = (1 / (1 + exp(-x)));
}
return output_array;
}

static inline int32_t ActivationT(int32_t value, int32_t threshold) {
return value > threshold ? 1 : 0;
}

Softmax

//对每一行进行softmax
void softmax(float *x, int row, int column)
{
    for (int j = 0; j < row; ++j)
    {
        float max = 0.0;
        float sum = 0.0;
        for (int k = 0; k < column; ++k)
            if (max < x[k + j*column])
                max = x[k + j*column];
        for (int k = 0; k < column; ++k)
        {
            x[k + j*column] = exp(x[k + j*column] - max);    // prevent data overflow
            sum += x[k + j*column];
        }
        for (int k = 0; k < column; ++k) x[k + j*column] /= sum;
    }
}   //row*column

Argmax

static inline int32_t Argmax(float array[], int32_t size) {
float max_value = 0.0f;
int32_t max_index = -1;
for (int32_t i = 0; i < size; i++) {
    if (array[i] > max_value) {
    max_value = array[i];
    max_index = i;
    }
}
return max_index;
}