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#include <functional>
#include <memory>
#include <vector>
#include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/fake_input.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/kernels/ops_testutil.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/public/tensor.h"
#include "tensorflow/core/lib/strings/strcat.h"
#include <gtest/gtest.h>
#include "tensorflow/core/lib/core/status_test_util.h"
namespace tensorflow {
namespace {
class DynamicStitchOpTest : public OpsTestBase {
protected:
void MakeOp(int n, DataType dt) {
RequireDefaultOps();
ASSERT_OK(NodeDefBuilder("myop", "DynamicStitch")
.Input(FakeInput(n, DT_INT32))
.Input(FakeInput(n, dt))
.Finalize(node_def()));
ASSERT_OK(InitOp());
}
};
TEST_F(DynamicStitchOpTest, Simple_OneD) {
MakeOp(2, DT_FLOAT);
// Feed and run
AddInputFromArray<int32>(TensorShape({3}), {0, 4, 7});
AddInputFromArray<int32>(TensorShape({5}), {1, 6, 2, 3, 5});
AddInputFromArray<float>(TensorShape({3}), {0, 40, 70});
AddInputFromArray<float>(TensorShape({5}), {10, 60, 20, 30, 50});
ASSERT_OK(RunOpKernel());
// Check the output.
Tensor expected(allocator(), DT_FLOAT, TensorShape({8}));
test::FillValues<float>(&expected, {0, 10, 20, 30, 40, 50, 60, 70});
test::ExpectTensorEqual<float>(expected, *GetOutput(0));
}
TEST_F(DynamicStitchOpTest, Simple_TwoD) {
MakeOp(3, DT_FLOAT);
// Feed and run
AddInputFromArray<int32>(TensorShape({3}), {0, 4, 7});
AddInputFromArray<int32>(TensorShape({2}), {1, 6});
AddInputFromArray<int32>(TensorShape({3}), {2, 3, 5});
AddInputFromArray<float>(TensorShape({3, 2}), {0, 1, 40, 41, 70, 71});
AddInputFromArray<float>(TensorShape({2, 2}), {10, 11, 60, 61});
AddInputFromArray<float>(TensorShape({3, 2}), {20, 21, 30, 31, 50, 51});
ASSERT_OK(RunOpKernel());
// Check the output.
Tensor expected(allocator(), DT_FLOAT, TensorShape({8, 2}));
test::FillValues<float>(&expected, {0, 1, 10, 11, 20, 21, 30, 31, 40, 41, 50,
51, 60, 61, 70, 71});
test::ExpectTensorEqual<float>(expected, *GetOutput(0));
}
TEST_F(DynamicStitchOpTest, Error_IndicesMultiDimensional) {
MakeOp(2, DT_FLOAT);
// Feed and run
AddInputFromArray<int32>(TensorShape({3}), {0, 4, 7});
AddInputFromArray<int32>(TensorShape({1, 5}), {1, 6, 2, 3, 5});
AddInputFromArray<float>(TensorShape({3}), {0, 40, 70});
AddInputFromArray<float>(TensorShape({5}), {10, 60, 20, 30, 50});
Status s = RunOpKernel();
EXPECT_TRUE(StringPiece(s.ToString())
.contains("data[1].shape = [5] does not start with "
"indices[1].shape = [1,5]"))
<< s;
}
TEST_F(DynamicStitchOpTest, Error_DataNumDimsMismatch) {
MakeOp(2, DT_FLOAT);
// Feed and run
AddInputFromArray<int32>(TensorShape({3}), {0, 4, 7});
AddInputFromArray<int32>(TensorShape({5}), {1, 6, 2, 3, 5});
AddInputFromArray<float>(TensorShape({3}), {0, 40, 70});
AddInputFromArray<float>(TensorShape({1, 5}), {10, 60, 20, 30, 50});
Status s = RunOpKernel();
EXPECT_TRUE(StringPiece(s.ToString())
.contains("data[1].shape = [1,5] does not start with "
"indices[1].shape = [5]"))
<< s;
}
TEST_F(DynamicStitchOpTest, Error_DataDimSizeMismatch) {
MakeOp(2, DT_FLOAT);
// Feed and run
AddInputFromArray<int32>(TensorShape({3}), {0, 4, 5});
AddInputFromArray<int32>(TensorShape({4}), {1, 6, 2, 3});
AddInputFromArray<float>(TensorShape({3, 1}), {0, 40, 70});
AddInputFromArray<float>(TensorShape({4, 2}),
{10, 11, 60, 61, 20, 21, 30, 31});
Status s = RunOpKernel();
EXPECT_TRUE(StringPiece(s.ToString())
.contains("Need data[0].shape[1:] = data[1].shape[1:], "
"got data[0].shape = [3,1], data[1].shape = [4,2]"))
<< s;
}
TEST_F(DynamicStitchOpTest, Error_DataAndIndicesSizeMismatch) {
MakeOp(2, DT_FLOAT);
// Feed and run
AddInputFromArray<int32>(TensorShape({3}), {0, 4, 7});
AddInputFromArray<int32>(TensorShape({5}), {1, 6, 2, 3, 5});
AddInputFromArray<float>(TensorShape({3}), {0, 40, 70});
AddInputFromArray<float>(TensorShape({4}), {10, 60, 20, 30});
Status s = RunOpKernel();
EXPECT_TRUE(
StringPiece(s.ToString())
.contains(
"data[1].shape = [4] does not start with indices[1].shape = [5]"))
<< s;
}
} // namespace
} // namespace tensorflow
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