未验证 提交 757aa470 编写于 作者: Y ykkk2333 提交者: GitHub

update xpu.cmake to 20230408 (#52409)

上级 e041ffca
......@@ -8,7 +8,7 @@ set(XPU_API_LIB_NAME "libxpuapi.so")
set(XPU_RT_LIB_NAME "libxpurt.so")
set(XPU_XFT_LIB_NAME "libxft.so")
set(XPU_BASE_DATE "20230323")
set(XPU_BASE_DATE "20230408")
set(XPU_XCCL_BASE_VERSION "1.0.13")
set(XPU_XFT_BASE_VERSION "latest")
......
......@@ -114,8 +114,6 @@ void Pool2dGradKernel(const Context& ctx,
} else if (pooling_type == "avg") {
// When output dim is 1 * 1 (1 * 1 * 1 in pool_3d), use scale
// and broadcast kernels to get same output, but better performance.
// Since the dim is special in particular models,
// use 'export XPU_POOLING_GRAD_SPECIAL=1' to open this path
if (out_h == 1 && out_w == 1 && std::is_same<T, float>::value) {
xpu::ctx_guard RAII_GUARD(ctx.x_context());
float scale = 1.0 / (in_h * in_w);
......
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