mirror of https://github.com/llvm/torch-mlir
44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
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# -*- Python -*-
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# This file is licensed under a pytorch-style license
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# See frontends/pytorch/LICENSE for license information.
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import typing
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import torch
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import torch_mlir
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# RUN: %PYTHON %s | npcomp-opt | FileCheck %s
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mb = torch_mlir.ModuleBuilder()
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class Submodule(torch.nn.Module):
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def forward(self, x):
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return x
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class TestModule(torch.nn.Module):
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def __init__(self):
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super().__init__()
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self.s = Submodule()
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def forward(self, x, y):
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return x * y
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# The symbol name of the function is NOT load-bearing and cannot be relied upon.
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# However, we do make an attempt to ensure that the names are debuggable.
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#
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# The names have the following structure:
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# - `__npcomp_priv_fn`: marker that this symbol name is private to npcomp
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# - `__torch__.Submodule.forward`: the name that TorchScript gives the function
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# - For those curious, the `__torch__` would be the Python module name, but in
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# the case that the name is `__main__` Torch replaces it with `__torch__` to
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# avoid collisions.
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# CHECK: func private @__npcomp_priv_fn.__torch__.Submodule.forward
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# CHECK: func private @__npcomp_priv_fn.__torch__.TestModule.forward
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test_module = TestModule()
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recursivescriptmodule = torch.jit.script(test_module)
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# TODO: Automatically handle unpacking Python class RecursiveScriptModule into the underlying ScriptModule.
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mb.import_module(recursivescriptmodule._c)
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mb.module.operation.print()
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