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Introduce DataBufferFromCallback Class #54
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📝 TAOS-CI Version: 1.4.20191203. Thank you for submitting PR #54. Please a submit 1commit/1PR (one commit per one PR) policy to get comments quickly from reviewers. Your PR must pass all verificiation processes of cibot before starting a review process from reviewers. If you are new member to join this project, please read manuals in documentation folder and wiki page. In order to monitor a progress status of your PR in more detail, visit http://ec2-54-180-96-14.ap-northeast-2.compute.amazonaws.com/. |
cibot: @jijoongmoon, A builder checker could not be completed because one of the checkers is not completed. In order to find out a reason, please go to http://ec2-54-180-96-14.ap-northeast-2.compute.amazonaws.com/nntrainer/ci/repo-workers/pr-checker/54-202004231550260.47635102272034-8329b0b84881c066c4c0592f560cb17981497d85/. |
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cibot: @jijoongmoon, A builder checker could not be completed because one of the checkers is not completed. In order to find out a reason, please go to http://ec2-54-180-96-14.ap-northeast-2.compute.amazonaws.com/nntrainer/ci/repo-workers/pr-checker/54-202004231601090.43018293380737-09289474f086c915369b0f1ec4b045949257d99c/. |
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cibot: @jijoongmoon, A builder checker could not be completed because one of the checkers is not completed. In order to find out a reason, please go to http://ec2-54-180-96-14.ap-northeast-2.compute.amazonaws.com/nntrainer/ci/repo-workers/pr-checker/54-202004231610010.526447057724-18aaf743a24717a7d1c597dc1473961f148d3d53/. |
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With this class, it is possible to train with user specific data generation callback funciton. This is the default to get training data unless there is [DataSet] key in configuration file. - in Application/Classification/jni/main_func.cpp NN.train(getMiniBatch_train, getMiniBatch_val, getMiniBatch_train) Then, data buffer thread call these functions to get newest data with size of mini batch. The format this function should be : /* * @brief Callback function to get user specific data * @param[in] X data 3D float vector type * @param[in] Y label 3D float vector type * @param[out] status status for error handle * @RetVal true / false generate all data for this epoch */ bool func(std::vector<std::vector<std::vector<float>>>& X, std::vector<std::vector<std::vector<float>>>& Y, int &status) **Self evaluation:** 1. Build test: [X]Passed [ ]Failed [ ]Skipped 2. Run test: [X]Passed [ ]Failed [ ]Skipped Signed-off-by: jijoong.moon <jijoong.moon@samsung.com>
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LGTM
With this class, it is possible to train with user specific data
generation callback function. This is the default to get training
data unless there is [DataSet] key in configuration file.
NN.train(getMiniBatch_train, getMiniBatch_val, getMiniBatch_train)
Then, data buffer thread call these functions to get newest data with
size of mini batch.
The format this function should be :
/*
*/
bool func(std::vector<std::vector<std::vector>>& X,
std::vector<std::vector<std::vector>>& Y, int &status)
Self evaluation:
Signed-off-by: jijoong.moon jijoong.moon@samsung.com