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Update github workflow for PyTorch 2.0.1 #1

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Update github workflow for PyTorch 2.0.1 #1

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a1d0717
Fix torch._C.Node attribute access (#372)
jamt9000 Jul 8, 2023
2f34bc4
Update github workflow for PyTorch 2.0.1
jamt9000 Jul 8, 2023
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12 changes: 7 additions & 5 deletions .github/workflows/test.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -11,18 +11,20 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: [3.8]
pytorch-version: [1.7.1, 1.9.1, 1.10.1]
pytorch-version: [1.7.1, 1.9.1, 1.10.1, 2.0.1]
include:
- python-version: 3.8
- python-version: '3.8'
pytorch-version: 1.7.1
torchvision-version: 0.8.2
- python-version: 3.8
- python-version: '3.8'
pytorch-version: 1.9.1
torchvision-version: 0.10.1
- python-version: 3.8
- python-version: '3.8'
pytorch-version: 1.10.1
torchvision-version: 0.11.2
- python-version: '3.11'
pytorch-version: 2.0.1
torchvision-version: 0.15.2
steps:
- uses: conda-incubator/setup-miniconda@v2
- run: conda install -n test python=${{ matrix.python-version }} pytorch=${{ matrix.pytorch-version }} torchvision=${{ matrix.torchvision-version }} cpuonly -c pytorch
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12 changes: 10 additions & 2 deletions clip/clip.py
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Expand Up @@ -145,6 +145,14 @@ def load(name: str, device: Union[str, torch.device] = "cuda" if torch.cuda.is_a
device_holder = torch.jit.trace(lambda: torch.ones([]).to(torch.device(device)), example_inputs=[])
device_node = [n for n in device_holder.graph.findAllNodes("prim::Constant") if "Device" in repr(n)][-1]

def _node_get(node: torch._C.Node, key: str):
"""Gets attributes of a node which is polymorphic over return type.

From https://github.com/pytorch/pytorch/pull/82628
"""
sel = node.kindOf(key)
return getattr(node, sel)(key)

def patch_device(module):
try:
graphs = [module.graph] if hasattr(module, "graph") else []
Expand All @@ -156,7 +164,7 @@ def patch_device(module):

for graph in graphs:
for node in graph.findAllNodes("prim::Constant"):
if "value" in node.attributeNames() and str(node["value"]).startswith("cuda"):
if "value" in node.attributeNames() and str(_node_get(node, "value")).startswith("cuda"):
node.copyAttributes(device_node)

model.apply(patch_device)
Expand All @@ -182,7 +190,7 @@ def patch_float(module):
for node in graph.findAllNodes("aten::to"):
inputs = list(node.inputs())
for i in [1, 2]: # dtype can be the second or third argument to aten::to()
if inputs[i].node()["value"] == 5:
if _node_get(inputs[i].node(), "value") == 5:
inputs[i].node().copyAttributes(float_node)

model.apply(patch_float)
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