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Speed-up torch.compile PyG models #6980

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Mar 20, 2023
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Speed-up torch.compile PyG models #6980

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65eceef
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rusty1s Mar 20, 2023
aeedd64
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rusty1s Mar 20, 2023
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2 changes: 1 addition & 1 deletion CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
- Added `Pad` transform ([#5940](https://github.com/pyg-team/pytorch_geometric/pull/5940), [#6697](https://github.com/pyg-team/pytorch_geometric/pull/6697), [#6731](https://github.com/pyg-team/pytorch_geometric/pull/6731), [#6758](https://github.com/pyg-team/pytorch_geometric/pull/6758))
- Added full batch mode to the inference benchmark ([#6631](https://github.com/pyg-team/pytorch_geometric/pull/6631))
- Added `cat` aggregation type to the `HeteroConv` class so that features can be concatenated during grouping ([#6634](https://github.com/pyg-team/pytorch_geometric/pull/6634))
- Added `torch.compile` support and benchmark study ([#6610](https://github.com/pyg-team/pytorch_geometric/pull/6610), [#6952](https://github.com/pyg-team/pytorch_geometric/pull/6952), [#6953](https://github.com/pyg-team/pytorch_geometric/pull/6953))
- Added `torch.compile` support and benchmark study ([#6610](https://github.com/pyg-team/pytorch_geometric/pull/6610), [#6952](https://github.com/pyg-team/pytorch_geometric/pull/6952), [#6953](https://github.com/pyg-team/pytorch_geometric/pull/6953), [#6980](https://github.com/pyg-team/pytorch_geometric/pull/6980))
- Added the `AntiSymmetricConv` layer ([#6577](https://github.com/pyg-team/pytorch_geometric/pull/6577))
- Added a mixin for Huggingface model hub integration ([#5930](https://github.com/pyg-team/pytorch_geometric/pull/5930), [#6591](https://github.com/pyg-team/pytorch_geometric/pull/6591))
- Added support for accelerated GNN layers in `nn.conv.cugraph` via `cugraph-ops` ([#6278](https://github.com/pyg-team/pytorch_geometric/pull/6278), [#6388](https://github.com/pyg-team/pytorch_geometric/pull/6388), [#6412](https://github.com/pyg-team/pytorch_geometric/pull/6412))
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20 changes: 17 additions & 3 deletions test/nn/test_compile_conv.py
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Expand Up @@ -50,14 +50,28 @@ def test_compile_conv(device, Conv):
x = torch.randn(num_nodes, 64, device=args.device)
edge_index = torch.randint(num_nodes, (2, num_edges), device=args.device)

for Conv in [GCNConv, SAGEConv, MySAGEConv, GATConv]:
conv = MySAGEConv(64, 64).to(args.device)
benchmark(
funcs=[conv, torch.compile(enable_compile()(conv))],
func_names=['Vanilla', 'Compiled'],
args=(x, edge_index),
num_steps=50 if args.device == 'cpu' else 500,
num_warmups=10 if args.device == 'cpu' else 100,
backward=args.backward,
)

for Conv in [GCNConv, SAGEConv]:
print(f'Conv: {Conv.__name__}')

conv = Conv(64, 64).to(args.device)
compiled_conv = torch.compile(enable_compile()(conv))

jit_conv = Conv(64, 64).jittable().to(args.device)
compiled_jit_conv = torch.compile(enable_compile()(jit_conv))

benchmark(
funcs=[conv, torch.compile(enable_compile()(conv))],
func_names=['Vanilla', 'Compiled'],
funcs=[conv, compiled_conv, jit_conv, compiled_jit_conv],
func_names=['Vanilla', 'Compiled', 'JIT', 'JIT Compiled'],
args=(x, edge_index),
num_steps=50 if args.device == 'cpu' else 500,
num_warmups=10 if args.device == 'cpu' else 100,
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