- 07 5月, 2018 1 次提交
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由 Yu Yang 提交于
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- 24 2月, 2018 1 次提交
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由 Luo Tao 提交于
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- 13 2月, 2018 1 次提交
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由 Xin Pan 提交于
Currently, our tests run with 2 GPUs, the init time is absurdly long: about 4s for each process. Currently, we run each OP test on different processes. This PR: 1. create cmake function py_test_modules which will generate the Makefile that runs a list of Python unittest module in a single Python process. 2. move all "python unittest compatible" (e.g., used the unittest package, not just a regular python file). from fluid/tests to fluid/tests/unittests. 3. cmake now will run all OP tests in fluid/tests/unittests in a single process, except the time-consuming tests, they are separated into different processes to utilize parallelism. Please make sure to use the unittest package if you put the python test file in fluid/tests/unittests 4. remove all exit(0) from fluid/tests/unittests/*.py, exit(0) is used to disable unittest, we can not do it when running all tests in a single process since it will terminate the process without running the other tests. Instead, the test is disabled in fluid/tests/unittests/CMakeLists.txt. FIXME is added for each disabled item. Please disable the unittest from fluid/tests/unittests/CMakeLists.txt, instead of adding exit(0) to the Python file, for all Python file in fluid/tests/unittests/. 5. add an option WITH_FAST_BUNDLE_TEST. When OFF, will run the unit tests in separate process so that they can be tested individually.
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- 12 2月, 2018 1 次提交
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由 qingqing01 提交于
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- 21 1月, 2018 2 次提交
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由 dzhwinter 提交于
* "fix decode bug" * "follow commnet" * "fix error" * "fix hook bug" * fix based comment * fix copyright * fix based on comment
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由 chengduoZH 提交于
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- 19 1月, 2018 1 次提交
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由 chengduoZH 提交于
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- 18 1月, 2018 1 次提交
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由 chengduoZH 提交于
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- 17 1月, 2018 1 次提交
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由 guosheng 提交于
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- 15 1月, 2018 1 次提交
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由 dzhwinter 提交于
* add copyright hook * add copyright hook * refine copyright hook * "test copyright hook" * fix check style * fix ci
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- 14 11月, 2017 1 次提交
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由 Qiao Longfei 提交于
* init commit * change some dir name
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- 18 10月, 2017 1 次提交
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由 Markus Kliegl 提交于
* initial matmul operator Similar to np.matmul, but also has transpose_X and transpose_Y flags, and only supports tensors from rank 1 to 3 inclusive. For GPU, uses cublas?gemmStridedBatched. For CPU, uses cblas_?gemm_batch if available via MKL; otherwise a simple serial implementation that loops over the batch dimension is employed for now.
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