Skip to content
Snippets Groups Projects
  1. May 30, 2019
    • Neta Zmora's avatar
      MNIST support · f8085cf4
      Neta Zmora authored
      -Added a test for MNIST
      -Added classification_get_dummy_input() to apputils/data_loaders.py
      and wrapped it with get_dummy_input() for (temporary) backward
      compatibility.
      - Changed simplenet_mnist so that it supports thinning
      f8085cf4
  2. May 16, 2019
    • Neta Zmora's avatar
      Refactoring: utils.get_dummy_input() · bf1e6a0d
      Neta Zmora authored
      Remove the multiple instances of code that generates
      dummy input per dataset.
      bf1e6a0d
    • Bar's avatar
      Refactor export to ONNX functionality (#258) · 54304810
      Bar authored
      Introduced a new utility function to export image-classifiers
      to ONNX: export_img_classifier_to_onnx.
      The functionality is not new, just refactored.
      
      In the sample application compress_classifier.py added 
      --export-onnx as a stand-alone cmd-line flag for specifically exporting 
      ONNX models.
      This new flag can take an optional argument which is used to name the
      exported onnx model file.
      The option to export models was removed from the –summary argument.
      Now we allow multiple --summary options be called together.
      
      Added a basic test for exporting ONNX.
      54304810
  3. Apr 09, 2019
  4. Apr 08, 2019
  5. Feb 26, 2019
  6. Jul 13, 2018
    • Neta Zmora's avatar
      ADC (Automatic Deep Compression) example + features, tests, bug fixes (#28) · 718f777b
      Neta Zmora authored
      This is a merge of the ADC branch and master.
      ADC (using a DDPG RL agent to compress image classifiers) is still WiP and requires
      An unreleased version of Coach (https://github.com/NervanaSystems/coach).
      
      Small features in this commit:
      -Added model_find_module() - find module object given its name
      - Add channel ranking and pruning: pruning/ranked_structures_pruner.py
      - Add a CIFAR10 VGG16 model: models/cifar10/vgg_cifar.py
      - Thinning: change the level of some log messages – some of the messages were
      moved to ‘debug’ level because they are not usually interesting.
      - Add a function to print nicely formatted integers - distiller/utils.py
      - Sensitivity analysis for channels-removal
      - compress_classifier.py – handle keyboard interrupts
      - compress_classifier.py – fix re-raise of exceptions, so they maintain call-stack
      
      -Added tests:
      -- test_summarygraph.py: test_simplenet() - Added a regression test to target a bug that occurs when taking the predecessor of the first node in a graph
      -- test_ranking.py - test_ch_ranking, test_ranked_channel_pruning
      -- test_model_summary.py - test_png_generation, test_summary (sparsity/ compute/model/modules)
      
      - Bug fixes in this commit:
      -- Thinning bug fix: handle zero-sized 'indices' tensor
      During the thinning process, the 'indices' tensor can become zero-sized,
      and will have an undefiend length. Therefore, we need to check for this
      situation when assessing the number of elements in 'indices'
      -- Language model: adjust main.py to new distiller.model_summary API
      Unverified
      718f777b
Loading