perf: reduce redundant CUDA initialization and synchronization - #190
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chen2021673 wants to merge 2 commits into
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perf: reduce redundant CUDA initialization and synchronization#190chen2021673 wants to merge 2 commits into
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Chamberlain0w0
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Jul 31, 2026
kilinchange
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kilinchange
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这个文件里的几个比较函数的使用场景分别是什么呢？（主要是带/不带 Near 的函数），建议注释说明一下，我看测例里对于浮点数的比较，两种函数都有使用。
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这里与 GoogleTest 的比较函数对应（https://google.github.io/googletest/reference/assertions.html#EXPECT_EQ）
ExpectTensorEqual(a, b)：不指定误差，对于浮点数允许最多 4 ULP 的差异（对应EXPECT_FLOAT_EQ），适合预期结果应被精确保留的场景，例如 Fill、Copy等；
ExpectTensorNear(a, b, tolerance)：使用显式绝对误差（对应EXPECT_NEAR），适合存在累积误差的场景。
已补充在注释里。
- 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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