Tacotron2+Waveglow/PyT * AMP support * Data preprocessing for Tacotron 2 training * Fixed dropouts on LSTMCells SSD/PyT * script and notebook for inference * AMP support * README update * updates to examples/* BERT/PyT * initial release GNMT/PyT * Default container updated to NGC PyTorch 19.05-py3 * Mixed precision training implemented using APEX AMP * Added inference throughput and latency results on NVIDIA Tesla V100 16G * Added option to run inference on user-provided raw input text from command line NCF/PyT * Updated performance tables. * Default container changed to PyTorch 19.06-py3. * Caching validation negatives between runs Transformer/PyT * new README * jit support added UNet Medical/TF * inference example scripts added * inference benchmark measuring latency added * TRT/TF-TRT support added * README updated GNMT/TF * Performance improvements Small updates (mostly README) for other models. |
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.. | ||
inference.sh | ||
reference_inference_performance | ||
reference_performance | ||
reference_training_performance | ||
train_1epoch.sh | ||
train_1epoch_fp16.sh | ||
train_1epoch_fp32.sh | ||
train_6epoch_fp16.sh | ||
train_6epoch_fp32.sh | ||
train_bench.sh | ||
train_full.sh |