Jijoong Moon
Jijoong Moon
## In this PR This PR add loss scale parameter in RunLayerContext and use it to update mse loss. . Add Loss Scale Parameter in RunLayerContext Constructor . Add applyLossScale...
## In this PR This PR adds the is_NaN function to check if the tensor has a NaN value. This is for the check of NaN during mixed precision training....
## In this PR This PR includes the mixed precision test case. . Input - FC - MSE : "batch_size=2", "model_tensor_type=FP16-FP16", "loss_scale=128" **Self evaluation:** 1. Build test: [X]Passed [ ]Failed...
## In this PR This PR enables the FP16 support for the layers below: . input layer . mse loss layer Resolves: **Self evaluation:** 1. Build test: [X]Passed [ ]Failed...
## In this PR This PR finalizes the mixed precision support in NNTrainer. It modifies the network grap and layer node, and layer implementations. However, it does not support mixed...
## In this PR This PR modify conv2d, lstm, batch normalization layer to support mixed precision. We need FP16 to read and copy to FP32 tensors to support inference and...
## In this PR This PR includes more unittest and fixes for mixed precision. . Model Unittest . 2 fc layer which generates NaN or Inf Gradient from Troch. ....
## In this PR This PR adds torch mixed precision golden data generation and input and output for the test. . some fixes to test. Resolves: **Self evaluation:** 1. Build...
## In this PR This PR implements rms prop optimizer. unittest for rms prop is required. . implementation of RMSProp Class . Separate the optimizer properties into optimizer common properties....
This PR enables meson build with opencl for X86. Also, fix some unittest case errors and types. Resolves: **Self evaluation:** 1. Build test: [X]Passed [ ]Failed [ ]Skipped 2. Run...