120 lines
4.3 KiB
ReStructuredText
120 lines
4.3 KiB
ReStructuredText
Binarycrossentropy
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=================
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计算二元交叉熵损失。用于衡量二分类问题中预测值 (`input_x`) 和目标值 (`input_y`) 之间的差距。
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.. math::
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L_n = -w_n [y_n \cdot \log(x_n) + (1 - y_n) \cdot \log(1 - x_n)]
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其中 :math:`x_n` 是预测值, :math:`y_n` 是目标值, :math:`w_n` 是可选的样本权重。最终输出由 `reduction` 参数决定：
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- **None (0):** 不进行规约，输出每个元素的损失 :math:`L_n`。
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- **Mean (1):** 输出所有元素损失的平均值。
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- **Sum (2):** 输出所有元素损失的总和。
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输入：
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- **input_x** - 预测值的张量数据地址，通常是Sigmoid函数的输出。
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- **input_y** - 目标值（标签）的张量数据地址。
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- **weight** - (可选) 权重张量的数据地址，维度与 `input_x` 相同。
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- **params** - 其他参数打包成数组。
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- **core_mask** - 核掩码。
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输出：
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- **loss** - 写入最终损失值的数据地址。
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支持平台：
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``FT78NE``
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``MT7004``
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.. note::
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- FT78NE 支持fp32, int8
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- MT7004 支持fp16, fp32
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**参数数组结构：**
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.. code-block:: c
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:linenos:
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long long params[4];
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params[0] = (long long)input_size; 输入张量的总元素数量
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params[1] = (long long)reduction; 规约类型 (0: None, 1: Mean, 2: Sum)。
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params[2] = (long long)tmp_loss; 用于存储逐元素损失的临时工作空间地址，大小必须为 `input_size`。
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params[3] = (long long)weight_defined; 权重是否有效的标志。若为非0，则`weight`参数必须提供。
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**共享存储版本:**
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.. c:function:: void fp_binary_cross_entropy_s(float* input_x, float* input_y, float* weight, float* loss, long long *params, int core_mask)
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.. c:function:: void hp_binary_cross_entropy_s(half* input_x, half* input_y, half* weight, half* loss, long long *params, int core_mask)
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.. c:function:: void i8_binary_cross_entropy_s(int8_t* input_x, int8_t* input_y, int8_t* weight, int8_t* loss, long long *params, int core_mask)
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**C调用示例：**
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.. code-block:: c
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:linenos:
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:emphasize-lines: 16
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//FT78NE示例
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#include <stdio.h>
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#include <binarycrossentropy.h>
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int main(int argc, char* argv[]) {
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float *input_x = (float *)0xA0000000; // input_x 在DDR空间
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float *input_y = (float *)0xB0000000; // input_y
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float *weight = (float *)0xC0000000; // weight
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float *loss = (float *)0xD0000000; // loss output
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float *tmp_loss = (float *)0xE0000000; // temp workspace
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int input_size = 1024;
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int reduction = 1; // Mean
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int weight_defined = 1; // true
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int core_mask = 0xff;
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long long params[4];
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params[0] = (long long)input_size;
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params[1] = (long long)reduction;
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params[2] = (long long)(uintptr_t)tmp_loss;
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params[3] = (long long)weight_defined;
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fp_binary_cross_entropy_s(input_x, input_y, weight, loss, params, core_mask);
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return 0;
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}
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**私有存储版本:**
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.. c:function:: void fp_binary_cross_entropy_p(float* input_x, float* input_y, float* weight, float* loss, long long *params)
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.. c:function:: void hp_binary_cross_entropy_p(half* input_x, half* input_y, half* weight, half* loss, long long *params)
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.. c:function:: void i8_binary_cross_entropy_p(int8_t* input_x, int8_t* input_y, int8_t* weight, int8_t* loss, long long *params)
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**C调用示例：**
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.. code-block:: c
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:linenos:
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:emphasize-lines: 15
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//FT78NE示例
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#include <stdio.h>
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#include <binarycrossentropy.h>
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int main(int argc, char* argv[]) {
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float *input_x = (float *)0x10000000; // input_x 在L2空间
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float *input_y = (float *)0x11000000; // input_y
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float *weight = (float *)0x12000000; // weight
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float *loss = (float *)0x13000000; // loss output
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float *tmp_loss = (float *)0x14000000; // temp workspace
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int input_size = 1024;
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int reduction = 1; // Mean
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int weight_defined = 0; // false
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long long params[4];
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params[0] = (long long)input_size;
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params[1] = (long long)reduction;
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params[2] = (long long)(uintptr_t)tmp_loss;
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params[3] = (long long)weight_defined;
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fp_binary_cross_entropy_p(input_x, input_y, weight, loss, params);
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return 0;
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} |