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  1. Feb 13, 2019
  2. Feb 11, 2019
    • Guy Jacob's avatar
      Post-train quant based on stats + additional modules quantized (#136) · 28a8ee18
      Guy Jacob authored
      Summary of changes:
      (1) Post-train quantization based on pre-collected statistics
      (2) Quantized concat, element-wise addition / multiplication and embeddings
      (3) Move post-train quantization command line args out of sample code
      (4) Configure post-train quantization from YAML for more fine-grained control
      
      (See PR #136 for more detailed changes descriptions)
      28a8ee18
  3. Feb 10, 2019
    • Guy Jacob's avatar
      Load different random subset of dataset on each epoch (#149) · 4b1d0c89
      Guy Jacob authored
      * For CIFAR-10 / ImageNet only
      * Refactor data_loaders.py, reduce code duplication
      * Implemented custom sampler
      * Integrated in image classification sample
      * Since we now shuffle the test set, had to update expected results
        in 2 full_flow_tests that do evaluation
      4b1d0c89
  4. Jan 31, 2019
  5. Jan 16, 2019
    • Bar's avatar
      compress_classifier.py refactoring (#126) · cfbc3798
      Bar authored
      * Support for multi-phase activations logging
      
      Enable logging activation both durning training and validation at
      the same session.
      
      * Refactoring: Move parser to its own file
      
      * Parser is moved from compress_classifier into its own file.
      * Torch version check is moved to precede main() call.
      * Move main definition to the top of the file.
      * Modify parser choices to case-insensitive
      cfbc3798
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