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28f87b9cf9
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/78297 Clone followed by expand/expand_as due to memoryOverlap check on copy_ native method. Refer to T118519310 for more details. Crashing test case: a = tensor(3,1) // strides = (1,1) B = tensor(3,2) // strides = (2,1) Temp = a.expand_as(b). // creates temp with shape as (3,2) and strides as (1,0) temp.clone() // crashe on copy_ due to memoryOverlap Fix: Disable the out variant for the expanded tensor. - Calls native clone instead of out variant for clone dealing with expanded tensors - Added test case for both clone variants (out and native clones) - Increased the tensor size for memory planner test case to trigger dynamic allocation Test Plan: buck test caffe2/benchmarks/static_runtime/fb:test_fb_operators buck test caffe2/benchmarks/static_runtime:static_runtime_cpptest Differential Revision: D36672180 Pull Request resolved: https://github.com/pytorch/pytorch/pull/78322 Approved by: https://github.com/mikeiovine |
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| .. | ||
| cpp | ||
| distributed | ||
| fastrnns | ||
| framework_overhead_benchmark | ||
| functional_autograd_benchmark | ||
| fuser | ||
| 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