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Rong Rong (AI Infra) 7f1b672b7a Revert D29952381: [Static Runtime] Ensure that unittests only use out variants or native ops 
Test Plan: revert-hammer

Differential Revision:
D29952381 (8737e17af2)

Original commit changeset: e60e70b80ccf

fbshipit-source-id: 59dc2f920b7ceaf94ba8f5f36024e7cc710f6645
2021-08-04 14:25:11 -07:00
..
cpp Disable avoid-non-const-global-variables lint check (#62008) 2021-07-22 18:04:40 -07:00
distributed [DDP Communication Hook] Update get_tensor and set_tensor to be cleaner naming conventions (buffer() and set_buffer()) (#62662) 2021-08-04 09:27:31 -07:00
fastrnns Add lint for unqualified noqa (#56272) 2021-04-19 13:16:18 -07:00
framework_overhead_benchmark
functional_autograd_benchmark faster generate_square_subsequent_mask in nn.Transformer (#60631) 2021-06-25 16:07:01 -07:00
instruction_counts Allow instruction counting to use shared memory as a staging ground. (And a couple other tweaks.) (#56711) 2021-05-12 20:37:41 -07:00
operator_benchmark [quant] update FakeQuant modules to use tensor qparams (#61318) 2021-07-10 19:43:02 -07:00
overrides_benchmark Remove legacy constructor calls from pytorch codebase. (#54142) 2021-04-11 15:45:17 -07:00
profiler_benchmark
record_function_benchmark
serialization
sparse Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
static_runtime Revert D29952381: [Static Runtime] Ensure that unittests only use out variants or native ops 2021-08-04 14:25:11 -07:00
tensorexpr [nnc] Added micro-benchmark to show perf improvement with cat subgraph optimization (#59581) 2021-06-18 14:32:09 -07:00
compare-fastrnn-results.py
compare.sh
README.md Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
upload_scribe.py Fix benchmark's import module and remove its usage of tools.stats.scribe (#61808) 2021-07-19 09:45:05 -07:00

README.md

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