perf: reduce redundant CUDA initialization and synchronization - #190
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Chamberlain0w0
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kilinchange
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kilinchange
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- defer loss host synchronization until after backward across training paths - skip zero fills when CUDA kernels or cuBLAS fully overwrite outputs - retain and document initialization required by partial-write paths - add CPU and CUDA numerical tests for affected operators
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| // such as reductions, normalization, softmax, and loss calculations. The tolerance is not relative. | ||
| // This overload checks the element count and flat order, but not the tensor shape. | ||
| inline void ExpectTensorNear(const std::shared_ptr<Tensor> &tensor, const std::vector<float> &expected, | ||
| float tolerance) { |
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建议函数参数名也跟 gtest 对齐，tolerance 改成 abs_error，能更直观地看出表示的是绝对误差。下面的 Near 函数同理。
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已修改为参数名对齐。另外ExpectTensorEqual改成ExpectTensorFloatEqual，因为功能上对齐的其实是gtest EXPECT_FLOAT_EQ
- rename the FP32 equality helper to ExpectTensorFloatEqual - align assertion parameters with GoogleTest naming - strengthen LayerNorm numerical coverage
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