torch-mlir/frontends/pytorch/test/ivalue_import/prim.py

40 lines
1.4 KiB
Python

# -*- Python -*-
# This file is licensed under a pytorch-style license
# See frontends/pytorch/LICENSE for license information.
import typing
import torch
import torch_mlir
# RUN: %PYTHON %s | npcomp-opt | FileCheck %s
mb = torch_mlir.ModuleBuilder()
class TestModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.t1 = torch.ones(1)
self.t2 = torch.ones(1)
# CHECK-LABEL: func private @__torch__.TestModule.forward(
# CHECK-SAME: %[[SELF:.*]]: !torch.nn.Module<"{{.*}}">) -> !basicpy.NoneType {
def forward(self):
# CHECK: %[[T2:.*]] = torch.prim.GetAttr %[[SELF]]["t2"]
# CHECK: torch.prim.SetAttr %[[SELF]]["t1"] = %[[T2]]
self.t1 = self.t2
# CHECK: torch.prim.CallMethod %[[SELF]]["callee"] (%{{.*}}, %{{.*}})
self.callee(self.t1, self.t2)
# CHECK-LABEL: func private @__torch__.TestModule.callee(
# CHECK-SAME: %[[SELF:.*]]: !torch.nn.Module<"{{.*}}">,
# CHECK-SAME: %[[X:.*]]: !torch.tensor,
# CHECK-SAME: %[[Y:.*]]: !torch.tensor
def callee(self, x, y):
pass
test_module = TestModule()
recursivescriptmodule = torch.jit.script(test_module)
# TODO: Automatically handle unpacking Python class RecursiveScriptModule into the underlying ScriptModule.
mb.import_module(recursivescriptmodule._c)
mb.module.operation.print()