mirror of https://github.com/llvm/torch-mlir
35 lines
1.1 KiB
Python
35 lines
1.1 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 TestModule(torch.nn.Module):
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def __init__(self):
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super().__init__()
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self.i = 3
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self.f = 42.5
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# CHECK: %[[TRUE:.*]] = basicpy.bool_constant true
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# CHECK: %[[N3:.*]] = basicpy.numeric_constant 3 : i64
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# CHECK: %[[N42:.*]] = basicpy.numeric_constant 4.250000e+01 : f64
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# CHECK: %[[MODULE:.*]] = torch.nn_module {
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# Note: for some reason, Torch always adds a "training" property to all modules.
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# CHECK: torch.attr "training", %[[TRUE]] : !basicpy.BoolType
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# CHECK: torch.attr "i", %[[N3]] : i64
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# CHECK: torch.attr "f", %[[N42]] : f64
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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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