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add winograd hlb_cifar10 back to tinybox benchmark (#3300)
* add winograd hlb_cifar10 back to tinybox benchmark * LATEWINO * use wino for the full run to save benchmark time
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15
.github/workflows/benchmark.yml
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15
.github/workflows/benchmark.yml
vendored
@@ -138,17 +138,14 @@ jobs:
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HIP=1 JIT=0 python3 examples/gpt2.py --prompt "Hello." --count 10 --temperature 0 --timing | tee gpt2_unjitted.txt
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HIP=1 JIT=1 python3 examples/gpt2.py --prompt "Hello." --count 10 --temperature 0 --timing | tee gpt2_jitted.txt
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- name: Run 10 CIFAR training steps
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run: STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar.txt
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run: HIP=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar.txt
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- name: Run 10 CIFAR training steps w HALF
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run: HIP=1 STEPS=10 HALF=1 python3 examples/hlb_cifar10.py | tee train_cifar_half.txt
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# # TODO: enable this. it took 3 minutes in CI and made the full training one more than 5 minutes
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# - name: Run 10 CIFAR training steps w HALF and 6 GPUS
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# - name: Run 10 CIFAR training steps w 6 GPUS
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# run: time HALF=1 STEPS=10 BS=1536 GPUS=6 python3 examples/hlb_cifar10.py
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- name: Run full CIFAR training w HALF
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run: time HALF=1 STEPS=1000 python3 examples/hlb_cifar10.py | tee train_cifar_half.txt
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# # TODO: make wino faster so we can enable both
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# - name: Run 10 CIFAR training steps w winograd
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# run: WINO=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar_wino.txt
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# - name: Run 10 CIFAR training steps w WINO/HALF/HIP
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# run: HALF=1 WINO=1 STEPS=10 python3 examples/hlb_cifar10.py | tee train_cifar_wino_half_hip.txt
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- name: Run full CIFAR training
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run: time HIP=1 HALF=1 LATEWINO=1 STEPS=1000 python3 examples/hlb_cifar10.py | tee train_cifar_one_gpu.py
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- uses: actions/upload-artifact@v4
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with:
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name: Speed (AMD)
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