Python-稀疏学习库和稀疏动量资源
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2019-08-11
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Python-稀疏学习库和稀疏动量资源.zip （65个子文件） 
TimDettmers-sparse_learning-952a28d results 
feature_data.tar.gz 1.07MB dynamic_sparse 
calc_confidence_intervals.py 657B
results.zip 3KB MNIST_compression_comparison_lenet5.csv 849B sensitivity_prune_rate_vgg-d.csv 382B WRN-28-2_results_summary.csv 406B sensitivity_momentum_alexnet-s.csv 435B sensitivity_momentum_vgg-d.csv 431B MNIST_sparse_summary.csv 671B sensitivity_prune_rate_alexnet-s.csv 384B MNIST_compression_comparison_lenet300-100.csv 846B graphs.py 4KB plot_graphs.py 16KB
requirements.txt 17B imagenet fully_sparse multiproc.py 4KB smoothing.py 762B img 
validation_accuracy.png 21KB training_accuracy.png 15KB training_loss.png 8KB scripts extract_summary.py 2KB main.py 28KB sparse_momentum_logs.tar.gz 419KB examples RN50_FP16_8GPU.sh 368B RN50_FP32_INFERENCE_BENCHMARK.sh 171B RN50_FP16_INFERENCE_BENCHMARK.sh 178B RN50_FP32_EVAL.sh 242B RN50_FP32_4GPU.sh 365B RN50_FP16_1GPU.sh 339B RN50_FP32_1GPU.sh 308B RN50_FP16_EVAL.sh 249B RN50_FP32_8GPU.sh 337B RN50_FP16_4GPU.sh 377B LICENSE 1KB README.md 12KB resnet.py 7KB partially_dense experiments resnet_experiments.yaml 9KB wrnet_experiments.yaml 29KB reparameterized_layers.py 4KB parameterized_tensors.py 10KB main.py 37KB model.py 17KB requirements.txt 431B LICENSE 11KB README.md 9KB learning_schedules resnet_schedule.yaml 1KB wrnet_schedule_long.yaml 993B wrnet_schedule.yaml 992B resnet_prune_schedule.yaml 998B resnet_schedule_long.yaml 1KB wrnet_prune_schedule.yaml 998B LICENSE 1KB setup.py 880B README.md 3KB mnist_cifar get_results_from_logs.py 4KB main.py 12KB extensions.py 5KB plot_feature_histograms.py 4KB sparselearning utils.py 8KB __init__.py 77B models.py 19KB funcs.py 12KB core.py 23KB .gitignore 1KB CHANGELOG.md 2KB How_to_add_your_own_algorithms.md 9KB资源评论
