[fx] supported data-dependent control flow in model tracing #1185
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FrankLeeeee
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feifeibear
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Jun 29, 2022
colossalai/fx/tracer/tracer.py
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| _TORCH_METHODS_TO_PATCH = ["arange", "zeros", "ones", "full", "full_like", "eye", "empty", "tensor"] | ||
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| def create_proxy(self, kind, target, args, kwargs, name=None, type_expr=None, proxy_factory_fn=None): |
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return value hint
-> 'Proxy'
feifeibear
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Jun 29, 2022
feifeibear
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Jun 29, 2022
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| _TORCH_METHODS_TO_PATCH = ["arange", "zeros", "ones", "full", "full_like", "eye", "empty", "tensor"] | ||
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| def create_proxy(self, kind, target, args, kwargs, name=None, type_expr=None, proxy_factory_fn=None) -> ColoProxy: |
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why not *args, **kwargs,
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These arguments are guaranteed to be backward compatible by PyTorch and some of them are needed for meta-tensor-related logic.
YuliangLiu0306
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Jun 29, 2022
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Supported data-dependent control flow with meta-tensor based proxy. This PR contains in-line documentation and a unit test case.