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https://github.com/zebrajr/pytorch.git
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f3806094d5
Summary: Breakup test_misc so that a test for a file is in test_filename. I think we might want to wait on moving test files into the source directory, since that would involve moving some tests over to the C10 folder, and this goes 99% of the way for test discoverability IMO anyway. I added a file test_utils for common functions invoked in the tests. Pull Request resolved: https://github.com/pytorch/pytorch/pull/18071 Differential Revision: D14485787 Pulled By: eellison fbshipit-source-id: dcb20d1978d490999d435ea20c1d0503413a5c80
64 lines
1.8 KiB
C++
64 lines
1.8 KiB
C++
#pragma once
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#include <ATen/ATen.h>
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#include "ATen/core/ivalue.h"
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#include "test/cpp/jit/test_base.h"
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#include "test/cpp/jit/test_utils.h"
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namespace torch {
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namespace jit {
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namespace {
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using Var = SymbolicVariable;
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using namespace torch::autograd;
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void testIValue() {
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Shared<IntList> foo = IntList::create({3, 4, 5});
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ASSERT_EQ(foo.use_count(), 1);
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IValue bar{foo};
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ASSERT_EQ(foo.use_count(), 2);
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auto baz = bar;
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ASSERT_EQ(foo.use_count(), 3);
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auto foo2 = std::move(bar);
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ASSERT_EQ(foo.use_count(), 3);
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ASSERT_TRUE(foo2.isIntList());
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ASSERT_TRUE(bar.isNone());
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foo2 = IValue(4.0);
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ASSERT_TRUE(foo2.isDouble());
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ASSERT_EQ(foo2.toDouble(), 4.0);
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ASSERT_EQ(foo.use_count(), 2);
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ASSERT_TRUE(ArrayRef<int64_t>(baz.toIntList()->elements()).equals({3, 4, 5}));
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auto move_it = std::move(baz).toIntList();
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ASSERT_EQ(foo.use_count(), 2);
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ASSERT_TRUE(baz.isNone());
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IValue i(4);
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ASSERT_TRUE(i.isInt());
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ASSERT_EQ(i.toInt(), 4);
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IValue dlist(DoubleList::create({3.5}));
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ASSERT_TRUE(dlist.isDoubleList());
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ASSERT_TRUE(ArrayRef<double>(std::move(dlist).toDoubleList()->elements())
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.equals({3.5}));
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ASSERT_TRUE(dlist.isNone());
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dlist = IValue(DoubleList::create({3.4}));
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ASSERT_TRUE(ArrayRef<double>(dlist.toDoubleList()->elements()).equals({3.4}));
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IValue the_list(Tuple::create({IValue(3.4), IValue(4), IValue(foo)}));
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ASSERT_EQ(foo.use_count(), 3);
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ASSERT_TRUE(the_list.isTuple());
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auto first = std::move(the_list).toTuple()->elements().at(1);
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ASSERT_EQ(first.toInt(), 4);
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at::Tensor tv = at::rand({3, 4});
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IValue ten(tv);
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ASSERT_EQ(tv.use_count(), 2);
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auto ten2 = ten;
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ASSERT_EQ(tv.use_count(), 3);
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ASSERT_TRUE(ten2.toTensor().equal(ten.toTensor()));
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std::move(ten2).toTensor();
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ASSERT_EQ(tv.use_count(), 2);
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}
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} // namespace
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} // namespace jit
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} // namespace torch
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