mirror of https://github.com/llvm/torch-mlir
40 lines
1.4 KiB
Python
40 lines
1.4 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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from typing import Dict, Optional
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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.d = {"key1": torch.tensor(1)}
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# CHECK: torch.class_type @[[CLASSTYPE:.*]] {
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# CHECK: torch.attr "training" : !torch.bool
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# CHECK: torch.attr "_is_full_backward_hook" : !torch.optional<!torch.bool>
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# CHECK: torch.attr "d" : !torch.dict<!torch.str, !torch.tensor>
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# CHECK: }
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# CHECK: %[[K:.*]] = torch.constant.str "key1"
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# CHECK: %[[TENSOR:.*]] = torch.tensor.literal(dense<1> : tensor<si64>) : !torch.tensor<[],si64>
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# CHECK: %[[DICT:.*]] = torch.prim.DictConstruct
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# CHECK-SAME keys(%[[K]] : !torch.str) values(%[[TENSOR]] : !torch.tensor<[],si64>)
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# CHECK-SAME: -> !torch.dict<!torch.str, !torch.tensor>
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# CHECK: torch.nn_module {
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# CHECK: torch.slot "d", %[[DICT]] : !torch.dict<!torch.str, !torch.tensor>
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# CHECK: } : !torch.nn.Module<"[[CLASSTYPE]]">
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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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