softmax.py 文件源码

def forward(self, x):
        xp = cuda.get_array_module(*x)
        if (xp != numpy and cuda.cudnn_enabled and self.use_cudnn and
                (_cudnn_version >= 3000 or x[0].dtype != numpy.float16)):
            oz_dtype = 'd' if x[0].dtype == 'd' else 'f'
            one = numpy.array(1, dtype=oz_dtype).ctypes
            zero = numpy.array(0, dtype=oz_dtype).ctypes
            handle = cudnn.get_handle()
            x_cube = x[0].reshape(x[0].shape[:2] + (-1, 1))
            desc = cudnn.create_tensor_descriptor(x_cube)
            self.y = xp.empty_like(x[0])
            libcudnn.softmaxForward(
                handle, _algorithm, _mode, one.data, desc.value,
                x_cube.data.ptr, zero.data, desc.value,
                self.y.data.ptr)
        else:
            self.y = x[0] - x[0].max(axis=1, keepdims=True)
            xp.exp(self.y, out=self.y)
            self.y /= self.y.sum(axis=1, keepdims=True)

        return self.y,