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Add missing tests for Neg kernel.

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Also add tests for LogicalNot.

PiperOrigin-RevId: 346955795
Change-Id: I79409b967ca0bf8b03499b7247c40fe245427850
This commit is contained in:
Adrian Kuegel 2020-12-11 01:43:52 -08:00 committed by TensorFlower Gardener
parent 06b99811c1
commit 32d5b268e2
1 changed files with 48 additions and 11 deletions
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59
tensorflow/core/kernels/mlir_generated/gpu_unary_ops_test.cc
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@ -49,18 +49,20 @@ class GpuUnaryOpTest : public OpsTestBase {
// function. In most cases it is enough to just provide the input type, // function. In most cases it is enough to just provide the input type,
// because all the types are the same. // because all the types are the same.
template <typename T, typename RT = T, typename OutT = T, typename ROutT = RT> template <typename T, typename RT = T, typename OutT = T, typename ROutT = RT>
void Run(std::vector<int64> input_shape, std::vector<T> input, void Run(std::vector<int64> input_shape, absl::InlinedVector<T, 10> input,
const std::string op_name, ROutT (*expected_callback)(RT), const std::string op_name, ROutT (*expected_callback)(RT),
bool expect_equal = true, bool add_tout = false, bool expect_equal = true, bool add_tout = false,
bool expect_buffer_reuse = true) { bool expect_buffer_reuse = true, bool add_t = true) {
assert(std::accumulate(input_shape.begin(), input_shape.end(), 1, assert(std::accumulate(input_shape.begin(), input_shape.end(), 1,
std::multiplies<int64>()) == input.size() && std::multiplies<int64>()) == input.size() &&
"Expected input length to equal to shape's number of elements."); "Expected input length to equal to shape's number of elements.");
TensorShape shape(input_shape); TensorShape shape(input_shape);
NodeDefBuilder builder("some_name", op_name); NodeDefBuilder builder("some_name", op_name);
builder.Input(FakeInput(DataTypeToEnum<T>::v())) builder.Input(FakeInput(DataTypeToEnum<T>::v()));
.Attr("T", DataTypeToEnum<T>::v()); if (add_t) {
builder.Attr("T", DataTypeToEnum<T>::v());
}
if (add_tout) { if (add_tout) {
builder.Attr("Tout", DataTypeToEnum<OutT>::v()); builder.Attr("Tout", DataTypeToEnum<OutT>::v());
} }
@ -98,15 +100,15 @@ class GpuUnaryOpTest : public OpsTestBase {
std::vector<int64> DefaultInputShape() { return std::vector<int64>{2, 7}; } std::vector<int64> DefaultInputShape() { return std::vector<int64>{2, 7}; }
template <typename T> template <typename T>
std::vector<T> DefaultInput() { absl::InlinedVector<T, 10> DefaultInput() {
return InputAsVector<T>({-18.0, -9.0, -1e-6, -0.0, 0.0, 1e-6, 0.1, 0.2, 0.3, return InputAsVector<T>({-18.0, -9.0, -1e-6, -0.0, 0.0, 1e-6, 0.1, 0.2, 0.3,
0.5, 0.7, 0.9, 9.0, 18.0}); 0.5, 0.7, 0.9, 9.0, 18.0});
} }
template <typename T> template <typename T>
std::vector<std::complex<T>> DefaultComplexInput() { absl::InlinedVector<std::complex<T>, 10> DefaultComplexInput() {
auto input = DefaultInput<T>(); auto input = DefaultInput<T>();
std::vector<std::complex<T>> complex_input; absl::InlinedVector<std::complex<T>, 10> complex_input;
for (T value : input) { for (T value : input) {
complex_input.emplace_back(value, -value); complex_input.emplace_back(value, -value);
} }
@ -114,21 +116,22 @@ class GpuUnaryOpTest : public OpsTestBase {
} }
template <typename T> template <typename T>
std::vector<T> DefaultInputGreaterThanZero() { absl::InlinedVector<T, 10> DefaultInputGreaterThanZero() {
return InputAsVector<T>({18.0, 9.0, 1e-6, 1.0, 0.1, 1e-6, 0.1, 0.2, 0.3, return InputAsVector<T>({18.0, 9.0, 1e-6, 1.0, 0.1, 1e-6, 0.1, 0.2, 0.3,
0.5, 0.7, 0.9, 9.0, 18.0}); 0.5, 0.7, 0.9, 9.0, 18.0});
} }
template <typename T> template <typename T>
std::vector<T> DefaultInputGreaterOrEqualToZero() { absl::InlinedVector<T, 10> DefaultInputGreaterOrEqualToZero() {
return InputAsVector<T>({18.0, 9.0, 1e-6, 0.0, 0.1, 1e-6, 0.1, 0.2, 0.3, return InputAsVector<T>({18.0, 9.0, 1e-6, 0.0, 0.1, 1e-6, 0.1, 0.2, 0.3,
0.5, 0.7, 0.9, 9.0, 18.0}); 0.5, 0.7, 0.9, 9.0, 18.0});
} }
private: private:
template <typename T> template <typename T>
std::vector<T> InputAsVector(std::initializer_list<double> input) { absl::InlinedVector<T, 10> InputAsVector(
std::vector<T> result; std::initializer_list<double> input) {
absl::InlinedVector<T, 10> result;
result.reserve(input.size()); result.reserve(input.size());
for (const auto& value : input) { for (const auto& value : input) {
result.push_back(static_cast<T>(value)); result.push_back(static_cast<T>(value));
@ -386,6 +389,19 @@ TEST_F(GpuUnaryOpTest, LogHalf) {
/*expect_equal=*/false); /*expect_equal=*/false);
} }
/// Test `tf.LogicalNot`
TEST_F(GpuUnaryOpTest, LogicalNot) {
Run<bool, bool, bool, bool>(
DefaultInputShape(), DefaultInput<bool>(),
/*op_name=*/"LogicalNot",
/*expected_callback=*/[](bool v) { return !v; },
/*expect_equal=*/true,
/*add_tout=*/false,
/*expect_buffer_reuse=*/true,
/*add_t=*/false);
}
/// Test `tf.Neg`. /// Test `tf.Neg`.
/// Reference implementation. /// Reference implementation.
@ -415,6 +431,27 @@ TEST_F(GpuUnaryOpTest, NegHalf) {
/*expect_equal=*/false); /*expect_equal=*/false);
} }
TEST_F(GpuUnaryOpTest, NegInt8) {
Run<int8>(DefaultInputShape(), DefaultInput<int8>(),
/*op_name=*/"Neg",
/*expected_callback=*/expected_neg,
/*expect_equal=*/true);
}
TEST_F(GpuUnaryOpTest, NegInt16) {
Run<int16>(DefaultInputShape(), DefaultInput<int16>(),
/*op_name=*/"Neg",
/*expected_callback=*/expected_neg,
/*expect_equal=*/true);
}
TEST_F(GpuUnaryOpTest, NegInt64) {
Run<int64>(DefaultInputShape(), DefaultInput<int64>(),
/*op_name=*/"Neg",
/*expected_callback=*/expected_neg,
/*expect_equal=*/true);
}
/// Test `tf.Real`. /// Test `tf.Real`.
TEST_F(GpuUnaryOpTest, RealFloat) { TEST_F(GpuUnaryOpTest, RealFloat) {