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416f593080
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/65517 This change retrofits `GetAlwaysAliveValues` into `ValueGroup` to group the values used by a graph into three groups as follows: - input_aliases: values that are either inputs or contain aliases of inputs or constants. - output_aliases: values that are either outputs or contain aliases of outputs and are not in input_aliases. - Values that dont't show up in input_aliases and output_aliases are internally created consumed within the graph. `output_aliases` is the only new group introduced by this change, and a following diff will use this to preallocate output Tensors to accelerate Static Runtime's performance. Test Plan: Added `ValueGroup.Init` to cover the updated code path. Note that there was no test for `GetAlwaysAliveValues` before. Reviewed By: hlu1 Differential Revision: D30940955 fbshipit-source-id: 2cb065ecda0f447a61e64a7cf70cc7c6947f7dfc |
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| .. | ||
| cpp | ||
| distributed | ||
| fastrnns | ||
| framework_overhead_benchmark | ||
| functional_autograd_benchmark | ||
| instruction_counts | ||
| operator_benchmark | ||
| overrides_benchmark | ||
| profiler_benchmark | ||
| record_function_benchmark | ||
| serialization | ||
| sparse | ||
| static_runtime | ||
| tensorexpr | ||
| compare-fastrnn-results.py | ||
| compare.sh | ||
| README.md | ||
| upload_scribe.py | ||
PyTorch Benchmarks
This folder contains scripts that produce reproducible timings of various PyTorch features.
It also provides mechanisms to compare PyTorch with other frameworks.
Setup environment
Make sure you're on a machine with CUDA, torchvision, and pytorch installed. Install in the following order:
# Install torchvision. It comes with the pytorch stable release binary
conda install pytorch torchvision -c pytorch
# Install the latest pytorch master from source.
# It should supersede the installation from the release binary.
cd $PYTORCH_HOME
python setup.py build develop
# Check the pytorch installation version
python -c "import torch; print(torch.__version__)"
Benchmark List
Please refer to each subfolder to discover each benchmark suite