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    • 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
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