forked from ROCm/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
batch_matmul_op_test.cc
82 lines (72 loc) · 2.47 KB
/
batch_matmul_op_test.cc
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
#include <memory>
#include <vector>
#include <gtest/gtest.h>
#include "caffe2/operators/batch_matmul_op.h"
namespace caffe2 {
namespace {
class BatchMatMulOpTest : public testing::Test {
protected:
void SetUp() override {
cpu_context_ = make_unique<CPUContext>(option_);
def_.set_name("test");
def_.set_type("BatchMatMul");
def_.add_input("A");
def_.add_input("B");
def_.add_output("Y");
}
void AddConstInput(
const std::vector<int64_t>& dims,
const float value,
const string& name) {
Blob* blob = ws_.CreateBlob(name);
auto* tensor = BlobGetMutableTensor(blob, CPU);
tensor->Resize(dims);
math::Set<float, CPUContext>(
tensor->numel(),
value,
tensor->template mutable_data<float>(),
cpu_context_.get());
}
void VerifyOutput(const std::vector<int64_t>& dims, const float value) const {
const Blob* Y_blob = ws_.GetBlob("Y");
ASSERT_NE(nullptr, Y_blob);
const auto& Y = Y_blob->Get<TensorCPU>();
const auto Y_dims = Y.sizes();
ASSERT_EQ(dims.size(), Y_dims.size());
for (std::size_t i = 0; i < dims.size(); ++i) {
ASSERT_EQ(dims[i], Y_dims[i]);
}
for (int i = 0; i < Y.numel(); ++i) {
EXPECT_FLOAT_EQ(value, Y.data<float>()[i]);
}
}
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
DeviceOption option_;
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
std::unique_ptr<CPUContext> cpu_context_;
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
Workspace ws_;
// NOLINTNEXTLINE(cppcoreguidelines-non-private-member-variables-in-classes)
OperatorDef def_;
};
TEST_F(BatchMatMulOpTest, BatchMatMulOpNormalTest) {
AddConstInput(std::vector<int64_t>{3, 5, 10}, 1.0f, "A");
AddConstInput(std::vector<int64_t>{3, 10, 6}, 1.0f, "B");
std::unique_ptr<OperatorBase> op(CreateOperator(def_, &ws_));
ASSERT_NE(nullptr, op);
ASSERT_TRUE(op->Run());
VerifyOutput(std::vector<int64_t>{3, 5, 6}, 10.0f);
}
TEST_F(BatchMatMulOpTest, BatchMatMulOpBroadcastTest) {
auto* arg = def_.add_arg();
arg->set_name("broadcast");
arg->set_i(1);
AddConstInput(std::vector<int64_t>{3, 5, 10}, 1.0f, "A");
AddConstInput(std::vector<int64_t>{2, 3, 10, 6}, 1.0f, "B");
std::unique_ptr<OperatorBase> op(CreateOperator(def_, &ws_));
ASSERT_NE(nullptr, op);
ASSERT_TRUE(op->Run());
VerifyOutput(std::vector<int64_t>{2, 3, 5, 6}, 10.0f);
}
} // namespace
} // namespace caffe2