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Don Jang cbfec02007 [Static Runtime] Add native op for aten::expand_as (#64024) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64024

`aten::expand_as` creates a view of the input tensor. This change adds its native op implementation for the static runtime.

Test Plan: - Added `StaticRuntime.IndividualOps_ExpandAs`

Reviewed By: hlu1

Differential Revision: D30546851

fbshipit-source-id: e53483048af890bc41b6192a1ab0c5ba0ee2bdc0
2021-08-26 13:05:53 -07:00
..
cpp [TensorExpr] Nuke KernelArena and KernelScope. (#63587) 2021-08-24 00:32:16 -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 Remove py2 compatible future imports (#44735) 2020-09-16 12:55:57 -07:00
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 Microbenchmarking matrix mult (einsum, torch.mult, torch.mm) (#63654) 2021-08-24 16:26:26 -07:00
overrides_benchmark Remove legacy constructor calls from pytorch codebase. (#54142) 2021-04-11 15:45:17 -07:00
profiler_benchmark Use libkineto in profiler (#46470) 2020-11-25 04:32:16 -08:00
record_function_benchmark Fix D23995953 import. 2020-09-29 19:30:23 -07:00
serialization [JIT] Make new zip serialization for torch save/load significantly (~70%) faster (#38379) 2020-05-29 01:56:18 -07:00
sparse Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
static_runtime [Static Runtime] Add native op for aten::expand_as (#64024) 2021-08-26 13:05:53 -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 Benchmarks: add scripts for FastRNNs results comparison. (#44134) 2020-09-03 13:44:42 -07:00
compare.sh Benchmarks: add scripts for FastRNNs results comparison. (#44134) 2020-09-03 13:44:42 -07:00
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