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Fix torch._C.Node attribute access (#372) 

Attribute access with subscripting would previously work
due to patching in https://github.com/pytorch/pytorch/pull/82511
but this has been removed.

This commit uses the fix proposed in https://github.com/pytorch/pytorch/pull/82628
to define a helper method to call the appropriate access method.
This commit is contained in:
James Thewlis 2023-07-08 10:26:30 +01:00 committed by GitHub
parent a9b1bf5920
commit a1d071733d
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1 changed files with 10 additions and 2 deletions
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12
clip/clip.py
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@ -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_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] 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): def patch_device(module):
try: try:
graphs = [module.graph] if hasattr(module, "graph") else [] graphs = [module.graph] if hasattr(module, "graph") else []
@ -156,7 +164,7 @@ def load(name: str, device: Union[str, torch.device] = "cuda" if torch.cuda.is_a
for graph in graphs: for graph in graphs:
for node in graph.findAllNodes("prim::Constant"): 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) node.copyAttributes(device_node)
model.apply(patch_device) model.apply(patch_device)
@ -182,7 +190,7 @@ def load(name: str, device: Union[str, torch.device] = "cuda" if torch.cuda.is_a
for node in graph.findAllNodes("aten::to"): for node in graph.findAllNodes("aten::to"):
inputs = list(node.inputs()) inputs = list(node.inputs())
for i in [1, 2]: # dtype can be the second or third argument to aten::to() 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) inputs[i].node().copyAttributes(float_node)
model.apply(patch_float) model.apply(patch_float)