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Random in nntrainer #167
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cibot: Thank you for posting issue #167. The person in charge will reply soon. |
Setting seeds seems great idea to me (also related to #133 ) |
That's good idea and it will make nntrainer more deterministic. I tried to do this in other ways like #148 which has python code to generate the input, output and golden data. It is used for testing conv2d and pooling layer for forwarding and compared with output from nntrainer. (Tensorflow is used to generate the golden data). However, we do not have tensorflow for tizen so that tar file is used. |
Current major issue is initialization. I will for now make the seed fixed. |
Adding determinism to the random number generators in the library DataBuffer has multiple threads but single thread of train/valid/test which run in sequence in my understanding Resolves nnstreamer#167 Signed-off-by: Parichay Kapoor <pk.kapoor@samsung.com>
Adding determinism to the random number generators in the library DataBuffer has multiple threads but single thread of train/valid/test which run in sequence in my understanding Resolves nnstreamer#167 Signed-off-by: Parichay Kapoor <pk.kapoor@samsung.com>
Adding determinism to the random number generators in the library DataBuffer has multiple threads but single thread of train/valid/test which run in sequence in my understanding Resolves nnstreamer#167 Signed-off-by: Parichay Kapoor <pk.kapoor@samsung.com>
Adding determinism to the random number generators in the library DataBuffer has multiple threads but single thread of train/valid/test which run in sequence in my understanding Resolves nnstreamer#167 Signed-off-by: Parichay Kapoor <pk.kapoor@samsung.com>
Adding determinism to the random number generators in the library DataBuffer has multiple threads but single thread of train/valid/test which run in sequence in my understanding Resolves nnstreamer#167 Signed-off-by: Parichay Kapoor <pk.kapoor@samsung.com>
Adding determinism to the random number generators in the library DataBuffer has multiple threads but single thread of train/valid/test which run in sequence in my understanding Resolves #167 Signed-off-by: Parichay Kapoor <pk.kapoor@samsung.com>
random() returns random value in nntrainer.
This results in the indeterministic training of the models in the unit tests.
How about fixing the seed in testing so that we can ensure that the training result stays the same with newer changes.
@jijoongmoon please advise if there should be an API function for this?
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