- 10 8月, 2017 6 次提交
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由 qingqing01 提交于
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由 Yu Yang 提交于
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由 qingqing01 提交于
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由 Superjom 提交于
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由 Superjom 提交于
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- 09 8月, 2017 10 次提交
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由 qingqing01 提交于
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由 Yu Yang 提交于
* Give which parameter, which element are wrong. And what max_diff is.
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由 Yu Yang 提交于
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由 Yu Yang 提交于
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由 Yu Yang 提交于
* No POD instance is forbidden in global scope. See https://google.github.io/styleguide/cppguide.html#Static_and_Global_Variables
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由 dongzhihong 提交于
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由 Yu Yang 提交于
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由 Qiao Longfei 提交于
* merge InferShapeContext and OperatorContext * OperatorBase& instead of OperatorBase*
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由 Yan Chunwei 提交于
* add lodtensor * add reshape of lod * add details * rename Elements/Levels * size_t and vector reserve * add details * add const& std::shared_ptr * add lod_tensor_impl.h * remove a shared_ptr
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由 Yi Wang 提交于
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- 08 8月, 2017 9 次提交
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由 Qiao Longfei 提交于
* init grad op checker * can run * add GradeChecker class * use get_numeric_gradient * refine code * add softmax and cross entropy auto grad test * use close to judge op_grad and numeric_grad * add cpu and gpu compare * add comments * add support_gpu * fix allclose * fix name error and symplify code * optimize gradient checker * add test_cross_entropy_op * update gradient_checker.py * optimize code * use random.uniform instead of random.random * fix type bug * optimize check_grad * put SupportGPU into OperatorBase * typo
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由 Yu Yang 提交于
* Although backward_test/rnn_test is not pass, just comment them.
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由 dongzhihong 提交于
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由 dongzhihong 提交于
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由 Yu Yang 提交于
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由 gongweibao 提交于
Fix C-API Compilation Error
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由 Yan Chunwei 提交于
* fix some enforce * remove compatible_type to avoid compile error * remove shared_ptr * fix tensor error msg
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由 Yi Wang 提交于
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由 Yi Wang 提交于
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- 07 8月, 2017 6 次提交
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由 Qiao Longfei 提交于
* check INFINITY in cross_entropy * fix error * use onehot_cross_entropy without GPU kernel * add support_gpu * fix allclose * fix name error and symplify code
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由 Qiao Longfei 提交于
* add support_gpu * fix allclose * fix name error and symplify code
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由 dongzhihong 提交于
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由 Yan Chunwei 提交于
* finish forward debug
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由 Yu Yang 提交于
It can be run both CPU/GPU. configure attributes are: * min: the min value of uniform random * max: the max value of uniform random * dims: the dimension of output tensor * seed: the random seed of uniform random. 0 means generate a seed each time.
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由 dongzhihong 提交于
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- 06 8月, 2017 1 次提交
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由 Yi Wang 提交于
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- 05 8月, 2017 3 次提交
- 04 8月, 2017 5 次提交