mirror of https://github.com/llvm/torch-mlir
43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
# -*- 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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# CHECK-LABEL: func private @__torch__.TestModule.forward
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# CHECK-SAME: (%[[ARG0:.*]]: !torch.nn.Module<"__torch__.TestModule">, %[[ARG1:.*]]: !torch.tensor) -> !torch.tensor {
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# CHECK: %[[VAL_2:.*]] = constant @__torch__.identity : (!torch.tensor) -> !torch.tensor
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# CHECK: %[[VAL_3:.*]] = call_indirect %[[VAL_2]](%[[ARG1]]) : (!torch.tensor) -> !torch.tensor
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# CHECK: return %[[VAL_3]] : !torch.tensor
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# CHECK: }
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# CHECK-LABEL: func private @__torch__.identity
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# CHECK-SAME: (%[[ARG:.*]]: !torch.tensor) -> !torch.tensor {
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# CHECK: return %[[ARG]] : !torch.tensor
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# CHECK: }
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# CHECK-LABEL: torch.class_type @__torch__.TestModule {
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# CHECK: torch.method "forward", @__torch__.TestModule.forward
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# CHECK: }
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def identity(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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def forward(self, x):
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return identity(x)
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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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