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Mike Iovine 873585da2b [SR] Improve set_inputs (#69087) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69087
This diff includes a variety of improvements to `set_inputs` to unify behavior with `torch::jit::Module`:

1. Eliminate code duplication between rvalue/lvalue overloads
2. Add type checks
3. Make input length check a `TORCH_CHECK` instead of a debug check - we have to fail when the wrong number of inputs are passed.
4. `schema` now always includes `self`, even if we release `module_`. This is consistent with `torch::jit::Module`.|
ghstack-source-id: 145599837

Test Plan: `buck test caffe2/benchmarks/static_runtime:static_runtime_cpptest`

Reviewed By: hlu1

Differential Revision: D32711705

fbshipit-source-id: fe97c10b4f03801ba59868b452e7d02b26b3106b
2021-12-15 09:31:19 -08:00
..
cpp use irange for loops 2 (#66746) 2021-12-10 04:26:23 -08:00
distributed Remove .data from benchmarks and tensorboard (#65389) 2021-09-22 11:16:59 -07:00
fastrnns Remove .data from benchmarks and tensorboard (#65389) 2021-09-22 11:16:59 -07:00
framework_overhead_benchmark
functional_autograd_benchmark Prefer mT and mH over transpose(-2, -1) and transpose(-2, -1).conj() (#64181) 2021-10-18 13:02:25 -07:00
fuser Benchmarks for various fusers (#67622) 2021-11-04 18:57:17 -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][embedding qat] Add benchmarks for QAT Embedding+EmbeddingBag (#66560) 2021-11-19 06:29:19 -08:00
overrides_benchmark Use classmethods for overrides (#64841) 2021-09-17 08:32:49 -07:00
profiler_benchmark
record_function_benchmark
serialization
sparse
static_runtime [SR] Improve set_inputs (#69087) 2021-12-15 09:31:19 -08:00
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
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