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[CoreML EP] Limit input shapes to at most rank 5 (#17086)
When considering nodes for the CoreML EP, limit input shapes to at most rank 5.
This commit is contained in:
Edward Chen
GitHub
parent
3426954525
commit
2b4cc24d5c
4 changed files with 154 additions and 95 deletions
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@ -64,12 +64,21 @@ bool IsInputSupported(const NodeArg& input, const std::string& parent_name,
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// input has dimension > 16384
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// See this issue, https://github.com/apple/coremltools/issues/1003
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if (dim > 16384) {
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LOGS(logger, WARNING) << "CoreML does not support input dim > 16384, input:" << input_name
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<< ", actual dim: " << dim;
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LOGS(logger, WARNING) << "CoreML does not support input dim > 16384. Input:" << input_name
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<< ", shape: " << Shape2String(shape);
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return false;
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}
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}
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// Limit input shape rank to 5.
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// CoreML doesn't currently support shapes with rank greater that 5.
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// https://github.com/apple/coremltools/issues/832
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if (shape.size() > 5) {
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LOGS(logger, VERBOSE) << "CoreML EP doesn't allow input shapes with rank greater than 5. Input: "
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<< input_name << ", shape: " << Shape2String(shape);
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return false;
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}
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return true;
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}
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@ -76,18 +76,17 @@ Status ReshapeOpBuilder::AddToModelBuilderImpl(ModelBuilder& model_builder,
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bool ReshapeOpBuilder::IsOpSupportedImpl(const Node& node, const OpBuilderInputParams& input_params,
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const logging::Logger& logger) const {
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const auto& input_defs = node.InputDefs();
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const auto& perm_name = input_defs[1]->Name();
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const auto& new_shape_name = input_defs[1]->Name();
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const auto& initializers = input_params.graph_viewer.GetAllInitializedTensors();
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if (!Contains(initializers, perm_name)) {
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if (!Contains(initializers, new_shape_name)) {
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LOGS(logger, VERBOSE) << "New shape of reshape must be a constant initializer";
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return false;
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}
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const auto& perm_tensor = *initializers.at(perm_name);
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Initializer unpacked_tensor(perm_tensor);
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auto raw_perm = unpacked_tensor.DataAsSpan<int64_t>();
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const auto& perm_dims = perm_tensor.dims();
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if (perm_dims.empty() || perm_dims[0] == 0) {
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const auto& new_shape_tensor = *initializers.at(new_shape_name);
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Initializer unpacked_tensor(new_shape_tensor);
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auto new_shape = unpacked_tensor.DataAsSpan<int64_t>();
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if (new_shape.empty()) {
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LOGS(logger, VERBOSE) << "New shape of reshape cannot be empty";
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return false;
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}
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@ -101,15 +100,22 @@ bool ReshapeOpBuilder::IsOpSupportedImpl(const Node& node, const OpBuilderInputP
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return false;
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}
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// CoreML reshape doesn't support new shape with more than 5 dimensions
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if (new_shape.size() > 5) {
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LOGS(logger, VERBOSE) << "Reshape does not support new shape with rank greater than 5. Input shape: "
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<< Shape2String(input_shape) << ", new shape: " << Shape2String(new_shape);
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return false;
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}
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// CoreML reshape does not support 0 as dimension
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NodeAttrHelper helper(node);
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const bool allow_zero = helper.Get("allowzero ", 0) == 1;
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if (allow_zero) {
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for (int64_t i = 0; i < perm_dims[0]; i++) {
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if (raw_perm[i] == 0) {
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LOGS_DEFAULT(VERBOSE) << "Reshape doesn't support 0 reshape dimension when allowzero is enabled";
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return false;
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}
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if (std::find(new_shape.begin(), new_shape.end(), int64_t{0}) != new_shape.end()) {
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LOGS(logger, VERBOSE) << "Reshape does not support new shape with 0 as dimension when allowzero is enabled. "
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"Input shape: "
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<< Shape2String(input_shape) << ", new shape: " << Shape2String(new_shape);
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return false;
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}
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}
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@ -162,6 +162,28 @@ TEST(TensorOpTest, Reshape_UnknownDimWithAllowZero) {
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test.Run();
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}
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TEST(TensorOpTest, ReshapeSixDimNewShape) {
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// CoreML has a 5D limit for the new shape. With the CoreML EP enabled, this should fall back to the CPU EP.
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OpTester test("Reshape", 14);
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test.AddInput<float>("data", {8, 8, 8}, std::vector<float>(8 * 8 * 8, 1.0f));
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const auto target_shape = std::vector<int64_t>{2, 4, 4, 2, 8, 1};
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test.AddInput<int64_t>("shape", {static_cast<int64_t>(target_shape.size())}, target_shape, true);
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test.AddOutput<float>("reshaped", target_shape, std::vector<float>(8 * 8 * 8, 1.0f));
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test.Run();
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}
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TEST(TensorOpTest, ReshapeSixDimInputShape) {
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// CoreML has a 5D limit for the new shape. With the CoreML EP enabled, this should fall back to the CPU EP.
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OpTester test("Reshape", 14);
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test.AddInput<float>("data", {2, 4, 4, 2, 8, 1}, std::vector<float>(8 * 8 * 8, 1.0f));
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const auto target_shape = std::vector<int64_t>{8, 8, 8};
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test.AddInput<int64_t>("shape", {static_cast<int64_t>(target_shape.size())}, target_shape, true);
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test.AddOutput<float>("reshaped", target_shape, std::vector<float>(8 * 8 * 8, 1.0f));
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test.Run();
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}
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#if defined(USE_DNNL)
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TEST(TensorOpTest, Reshape_bfloat16) {
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#ifdef USE_DNNL
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@ -44,29 +44,19 @@ TEST(TransposeOpTest, PermRankDoesNotMatchTensorRank) {
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// Those tests will fallback to other EPs.
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template <class T>
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void TransposeTest(std::vector<int64_t>& input_shape,
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std::vector<T>& input_vals,
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std::vector<int64_t>* p_perm,
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std::vector<int64_t> expected_shape,
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std::initializer_list<T>& expected_vals,
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bool is_tensorrt_supported = true,
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bool is_openvino_supported = true) {
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void TransposeTest(const std::vector<int64_t>& input_shape,
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const std::vector<T>& input_vals,
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const std::vector<int64_t>* p_perm,
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const std::vector<int64_t>& expected_shape,
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const std::vector<T>& expected_vals,
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const std::unordered_set<std::string>& excluded_provider_types = {}) {
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OpTester test("Transpose");
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if (nullptr != p_perm)
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test.AddAttribute("perm", *p_perm);
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test.AddInput<T>("X", input_shape, input_vals);
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test.AddOutput<T>("Y", expected_shape, expected_vals);
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// Disable TensorRT on unsupported tests
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std::unordered_set<std::string> excluded_providers;
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if (!is_tensorrt_supported) {
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excluded_providers.insert(kTensorrtExecutionProvider);
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}
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if (!is_openvino_supported) {
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excluded_providers.insert(kOpenVINOExecutionProvider);
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}
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test.Run(OpTester::ExpectResult::kExpectSuccess, "", excluded_providers);
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test.Run(OpTester::ExpectResult::kExpectSuccess, "", excluded_provider_types);
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}
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// Test 2 dimensional transpose, with no permutation attribute specified
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@ -77,12 +67,13 @@ TEST(TransposeOpTest, TwoDimNoAttr) {
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4.0f, 5.0f, 6.0f};
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std::vector<int64_t> expected_shape({3, 2});
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auto expected_vals = {
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std::vector<float> expected_vals = {
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1.0f, 4.0f,
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2.0f, 5.0f,
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3.0f, 6.0f};
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TransposeTest(input_shape, input_vals, nullptr, expected_shape, expected_vals, false); // TensorRT: SegFault error
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TransposeTest(input_shape, input_vals, nullptr, expected_shape, expected_vals,
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{kTensorrtExecutionProvider}); // TensorRT: SegFault error
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}
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TEST(TransposeOpTest, TwoDimNoAttrStr) {
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@ -92,7 +83,7 @@ TEST(TransposeOpTest, TwoDimNoAttrStr) {
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"4", "5", "6"};
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std::vector<int64_t> expected_shape({3, 2});
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std::initializer_list<std::string> expected_vals = {
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std::vector<std::string> expected_vals = {
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"1", "4",
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"2", "5",
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"3", "6"};
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@ -108,9 +99,9 @@ TEST(TransposeOpTest, TwoDim) {
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std::vector<int64_t> perm = {1, 0};
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std::vector<int64_t> expected_shape({3, 2});
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auto expected_vals = {1.0f, 4.0f,
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2.0f, 5.0f,
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3.0f, 6.0f};
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std::vector<float> expected_vals = {1.0f, 4.0f,
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2.0f, 5.0f,
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3.0f, 6.0f};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals);
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}
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@ -122,9 +113,9 @@ TEST(TransposeOpTest, TwoDim_double) {
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std::vector<int64_t> perm = {1, 0};
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std::vector<int64_t> expected_shape({3, 2});
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std::initializer_list<double> expected_vals = {1.0, 4.0,
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2.0, 5.0,
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3.0, 6.0};
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std::vector<double> expected_vals = {1.0, 4.0,
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2.0, 5.0,
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3.0, 6.0};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals);
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}
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@ -136,9 +127,9 @@ TEST(TransposeOpTest, TwoDim_int32) {
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std::vector<int64_t> perm = {1, 0};
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std::vector<int64_t> expected_shape({3, 2});
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std::initializer_list<int32_t> expected_vals = {1, 4,
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2, 5,
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3, 6};
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std::vector<int32_t> expected_vals = {1, 4,
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2, 5,
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3, 6};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals);
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}
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@ -151,12 +142,12 @@ TEST(TransposeOpTest, TwoDim_int16) {
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std::vector<int64_t> perm = {1, 0};
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std::vector<int64_t> expected_shape({3, 2});
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std::initializer_list<int16_t> expected_vals = {
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std::vector<int16_t> expected_vals = {
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1, 4,
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2, 5,
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3, 6};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, true, false);
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, {kOpenVINOExecutionProvider});
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}
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TEST(TransposeOpTest, TwoDim_mlfloat16) {
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@ -167,12 +158,12 @@ TEST(TransposeOpTest, TwoDim_mlfloat16) {
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std::vector<int64_t> perm = {1, 0};
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std::vector<int64_t> expected_shape({3, 2});
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std::initializer_list<MLFloat16> expected_vals =
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std::vector<MLFloat16> expected_vals =
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{MLFloat16::FromBits(static_cast<uint16_t>(1)), MLFloat16::FromBits(static_cast<uint16_t>(4)),
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MLFloat16::FromBits(static_cast<uint16_t>(2)), MLFloat16::FromBits(static_cast<uint16_t>(5)),
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MLFloat16::FromBits(static_cast<uint16_t>(3)), MLFloat16::FromBits(static_cast<uint16_t>(6))};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false);
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, {kTensorrtExecutionProvider});
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}
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#if defined(USE_DNNL)
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@ -234,7 +225,7 @@ TEST(TransposeOpTest, Transpose021_bfloat16) {
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std::vector<int64_t> perm = {0, 2, 1};
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std::vector<int64_t> expected_shape({4, 3, 2});
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auto expected_vals = {
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std::vector<float> expected_vals = {
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1.0f, 4.0f,
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2.0f, 5.0f,
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3.0f, 6.0f,
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@ -269,11 +260,11 @@ TEST(TransposeOpTest, TwoDim_int8) {
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std::vector<int64_t> perm = {1, 0};
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std::vector<int64_t> expected_shape({3, 2});
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std::initializer_list<int8_t> expected_vals = {1, 4,
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2, 5,
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3, 6};
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std::vector<int8_t> expected_vals = {1, 4,
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2, 5,
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3, 6};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false);
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, {kTensorrtExecutionProvider});
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}
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TEST(TransposeOpTest, TwoDimStr) {
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@ -284,7 +275,7 @@ TEST(TransposeOpTest, TwoDimStr) {
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std::vector<int64_t> perm = {1, 0};
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std::vector<int64_t> expected_shape({3, 2});
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std::initializer_list<std::string> expected_vals = {
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std::vector<std::string> expected_vals = {
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"1", "4",
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"2", "5",
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"3", "6"};
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@ -310,7 +301,7 @@ TEST(TransposeOpTest, Transpose021) {
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std::vector<int64_t> perm = {0, 2, 1};
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std::vector<int64_t> expected_shape({4, 3, 2});
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auto expected_vals = {
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std::vector<float> expected_vals = {
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1.0f, 4.0f,
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2.0f, 5.0f,
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3.0f, 6.0f,
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@ -327,7 +318,8 @@ TEST(TransposeOpTest, Transpose021) {
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2.3f, 5.3f,
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3.3f, 6.3f};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false); // TensorRT: illegal error
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals,
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{kTensorrtExecutionProvider}); // TensorRT: illegal error
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}
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TEST(TransposeOpTest, Transpose120) {
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@ -347,7 +339,7 @@ TEST(TransposeOpTest, Transpose120) {
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std::vector<int64_t> perm = {1, 2, 0};
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std::vector<int64_t> expected_shape({2, 3, 4});
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auto expected_vals = {
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std::vector<float> expected_vals = {
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1.0f, 1.1f, 1.2f, 1.3f,
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2.0f, 2.1f, 2.2f, 2.3f,
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3.0f, 3.1f, 3.2f, 3.3f,
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@ -356,7 +348,8 @@ TEST(TransposeOpTest, Transpose120) {
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5.0f, 5.1f, 5.2f, 5.3f,
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6.0f, 6.1f, 6.2f, 6.3f};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false); // TensorRT: illegal error
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals,
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{kTensorrtExecutionProvider}); // TensorRT: illegal error
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}
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// test when the suffix size is > 1 (last dimension is not moved)
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@ -377,7 +370,7 @@ TEST(TransposeOpTest, Transpose102) {
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std::vector<int64_t> perm = {1, 0, 2};
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std::vector<int64_t> expected_shape({2, 4, 3});
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auto expected_vals = {
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std::vector<float> expected_vals = {
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1.0f, 2.0f, 3.0f,
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1.1f, 2.1f, 3.1f,
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1.2f, 2.2f, 3.2f,
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@ -388,7 +381,8 @@ TEST(TransposeOpTest, Transpose102) {
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4.2f, 5.2f, 6.2f,
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4.3f, 5.3f, 6.3f};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false); // TensorRT: illegal error
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals,
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{kTensorrtExecutionProvider}); // TensorRT: illegal error
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}
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TEST(TransposeOpTest, TransposeReshape) {
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@ -408,7 +402,7 @@ TEST(TransposeOpTest, TransposeReshape) {
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std::vector<int64_t> perm = {1, 3, 2, 4, 0};
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std::vector<int64_t> expected_shape({4, 1, 2, 3, 1});
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auto expected_vals = {
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std::vector<float> expected_vals = {
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1.0f, 2.0f, 3.0f,
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4.0f, 5.0f, 6.0f,
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@ -421,7 +415,8 @@ TEST(TransposeOpTest, TransposeReshape) {
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1.3f, 2.3f, 3.3f,
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4.3f, 5.3f, 6.3f};
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false); // TensorRT: illegal error
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals,
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{kTensorrtExecutionProvider}); // TensorRT: illegal error
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}
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TEST(TransposeOpTest, ThreeDimStr) {
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@ -441,7 +436,7 @@ TEST(TransposeOpTest, ThreeDimStr) {
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std::vector<int64_t> perm = {0, 2, 1};
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std::vector<int64_t> expected_shape({4, 3, 2});
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std::initializer_list<std::string> expected_vals = {
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std::vector<std::string> expected_vals = {
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"1", "4",
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"2", "5",
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"3", "6",
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@ -461,6 +456,31 @@ TEST(TransposeOpTest, ThreeDimStr) {
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TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals);
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}
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TEST(TransposeOpTest, SixDim) {
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// CoreML has a 5D limit. With the CoreML EP enabled, this should fall back to the CPU EP.
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const auto input_shape = std::vector<int64_t>{2, 2, 2, 2, 2, 2};
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const auto input_vals = []() {
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std::vector<float> v(64);
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std::iota(v.begin(), v.end(), 0.0f);
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return v;
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}();
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const auto perm = std::vector<int64_t>{1, 0, 2, 3, 4, 5};
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||||
const auto expected_shape = input_shape; // all dimension values are the same
|
||||
const auto expected_vals = []() {
|
||||
std::vector<float> v(64);
|
||||
std::iota(v.begin() + 0, v.begin() + 16, 0.f);
|
||||
std::iota(v.begin() + 16, v.begin() + 32, 32.0f);
|
||||
std::iota(v.begin() + 32, v.begin() + 48, 16.0f);
|
||||
std::iota(v.begin() + 48, v.begin() + 64, 48.0f);
|
||||
return v;
|
||||
}();
|
||||
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals,
|
||||
{kQnnExecutionProvider}); // Error: Failed to finalize QNN graph.
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
static void NumericNCHW2NHWC() {
|
||||
std::vector<int64_t> input_shape({1, 3, 2, 2});
|
||||
|
|
@ -471,13 +491,14 @@ static void NumericNCHW2NHWC() {
|
|||
|
||||
std::vector<int64_t> perm = {0, 2, 3, 1};
|
||||
std::vector<int64_t> expected_shape({1, 2, 2, 3});
|
||||
std::initializer_list<T> expected_vals = {
|
||||
std::vector<T> expected_vals = {
|
||||
1, 5, 9,
|
||||
2, 6, 10,
|
||||
3, 7, 11,
|
||||
4, 8, 12};
|
||||
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false, false);
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals,
|
||||
{kTensorrtExecutionProvider, kOpenVINOExecutionProvider});
|
||||
}
|
||||
TEST(TransposeOpTest, NCHW2NHWC) {
|
||||
NumericNCHW2NHWC<int8_t>();
|
||||
|
|
@ -495,13 +516,13 @@ TEST(TransposeOpTest, NCHW2NHWCStr) {
|
|||
|
||||
std::vector<int64_t> perm = {0, 2, 3, 1};
|
||||
std::vector<int64_t> expected_shape({1, 2, 2, 3});
|
||||
std::initializer_list<std::string> expected_vals = {
|
||||
std::vector<std::string> expected_vals = {
|
||||
"1", "5", "9",
|
||||
"2", "6", "10",
|
||||
"3", "7", "11",
|
||||
"4", "8", "12"};
|
||||
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false);
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, {kTensorrtExecutionProvider});
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
|
|
@ -522,7 +543,7 @@ static void NumericNHWC2NCHW() {
|
|||
|
||||
std::vector<int64_t> perm = {0, 3, 1, 2};
|
||||
std::vector<int64_t> expected_shape({2, 2, 2, 2});
|
||||
std::initializer_list<T> expected_vals = {
|
||||
std::vector<T> expected_vals = {
|
||||
1, 3,
|
||||
5, 7,
|
||||
|
||||
|
|
@ -535,7 +556,8 @@ static void NumericNHWC2NCHW() {
|
|||
10, 12,
|
||||
14, 16};
|
||||
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false, false);
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals,
|
||||
{kTensorrtExecutionProvider, kOpenVINOExecutionProvider});
|
||||
}
|
||||
|
||||
TEST(TransposeOpTest, NHWC2NCHW) {
|
||||
|
|
@ -555,12 +577,12 @@ TEST(TransposeOpTest, NHWC2NCHW_String) {
|
|||
|
||||
std::vector<int64_t> perm = {0, 3, 1, 2};
|
||||
std::vector<int64_t> expected_shape({1, 3, 2, 2});
|
||||
std::initializer_list<std::string> expected_vals = {
|
||||
std::vector<std::string> expected_vals = {
|
||||
"1", "4", "7", "10",
|
||||
"2", "5", "8", "11",
|
||||
"3", "6", "9", "12"};
|
||||
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false);
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, {kTensorrtExecutionProvider});
|
||||
}
|
||||
|
||||
// test to cover memcpy from single axis moving inwards path
|
||||
|
|
@ -581,7 +603,7 @@ TEST(TransposeOpTest, SingleAxisMovingInwardsBlockCopy) {
|
|||
|
||||
std::vector<int64_t> perm = {1, 2, 0, 3};
|
||||
std::vector<int64_t> expected_shape({2, 2, 2, 2});
|
||||
std::initializer_list<uint64_t> expected_vals = {
|
||||
std::vector<uint64_t> expected_vals = {
|
||||
1, 2,
|
||||
9, 10,
|
||||
|
||||
|
|
@ -594,7 +616,7 @@ TEST(TransposeOpTest, SingleAxisMovingInwardsBlockCopy) {
|
|||
7, 8,
|
||||
15, 16};
|
||||
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, false);
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals, {kTensorrtExecutionProvider});
|
||||
}
|
||||
|
||||
TEST(TransposeOpTest, NDim) {
|
||||
|
|
@ -605,17 +627,17 @@ TEST(TransposeOpTest, NDim) {
|
|||
13.0f, 14.0f, 15.0f, 16.0f};
|
||||
|
||||
std::vector<int64_t> perm = {1, 0, 2, 3};
|
||||
auto expected_vals = {1.0f, 2.0f, 3.0f, 4.0f,
|
||||
9.0f, 10.0f, 11.0f, 12.0f,
|
||||
5.0f, 6.0f, 7.0f, 8.0f,
|
||||
13.0f, 14.0f, 15.0f, 16.0f};
|
||||
std::vector<float> expected_vals = {1.0f, 2.0f, 3.0f, 4.0f,
|
||||
9.0f, 10.0f, 11.0f, 12.0f,
|
||||
5.0f, 6.0f, 7.0f, 8.0f,
|
||||
13.0f, 14.0f, 15.0f, 16.0f};
|
||||
TransposeTest(input_shape, input_vals, &perm, input_shape, expected_vals);
|
||||
|
||||
perm = {1, 0, 3, 2};
|
||||
auto expected_vals2 = {1.0f, 3.0f, 2.0f, 4.0f,
|
||||
9.0f, 11.0f, 10.0f, 12.0f,
|
||||
5.0f, 7.0f, 6.0f, 8.0f,
|
||||
13.0f, 15.0f, 14.0f, 16.0f};
|
||||
std::vector<float> expected_vals2 = {1.0f, 3.0f, 2.0f, 4.0f,
|
||||
9.0f, 11.0f, 10.0f, 12.0f,
|
||||
5.0f, 7.0f, 6.0f, 8.0f,
|
||||
13.0f, 15.0f, 14.0f, 16.0f};
|
||||
TransposeTest(input_shape, input_vals, &perm, input_shape, expected_vals2);
|
||||
}
|
||||
|
||||
|
|
@ -627,11 +649,11 @@ TEST(TransposeOpTest, DoTransposeImpl) {
|
|||
}
|
||||
std::vector<int64_t> perm = {2, 1, 0, 3};
|
||||
std::vector<int64_t> expected_shape({1, 2, 5, 3});
|
||||
auto expected_vals = {0.0f, 1.0f, 2.0f, 6.0f, 7.0f, 8.0f,
|
||||
12.0f, 13.0f, 14.0f, 18.0f, 19.0f, 20.0f,
|
||||
24.0f, 25.0f, 26.0f, 3.0f, 4.0f, 5.0f,
|
||||
9.0f, 10.0f, 11.0f, 15.0f, 16.0f, 17.0f,
|
||||
21.0f, 22.0f, 23.0f, 27.0f, 28.0f, 29.0f};
|
||||
std::vector<float> expected_vals = {0.0f, 1.0f, 2.0f, 6.0f, 7.0f, 8.0f,
|
||||
12.0f, 13.0f, 14.0f, 18.0f, 19.0f, 20.0f,
|
||||
24.0f, 25.0f, 26.0f, 3.0f, 4.0f, 5.0f,
|
||||
9.0f, 10.0f, 11.0f, 15.0f, 16.0f, 17.0f,
|
||||
21.0f, 22.0f, 23.0f, 27.0f, 28.0f, 29.0f};
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals);
|
||||
}
|
||||
|
||||
|
|
@ -643,11 +665,11 @@ TEST(TransposeOpTest, DoTransposeImplString) {
|
|||
}
|
||||
std::vector<int64_t> perm = {2, 1, 0, 3};
|
||||
std::vector<int64_t> expected_shape({1, 2, 5, 3});
|
||||
std::initializer_list<std::string> expected_vals = {"n0", "n1", "n2", "n6", "n7", "n8",
|
||||
"n12", "n13", "n14", "n18", "n19", "n20",
|
||||
"n24", "n25", "n26", "n3", "n4", "n5",
|
||||
"n9", "n10", "n11", "n15", "n16", "n17",
|
||||
"n21", "n22", "n23", "n27", "n28", "n29"};
|
||||
std::vector<std::string> expected_vals = {"n0", "n1", "n2", "n6", "n7", "n8",
|
||||
"n12", "n13", "n14", "n18", "n19", "n20",
|
||||
"n24", "n25", "n26", "n3", "n4", "n5",
|
||||
"n9", "n10", "n11", "n15", "n16", "n17",
|
||||
"n21", "n22", "n23", "n27", "n28", "n29"};
|
||||
TransposeTest(input_shape, input_vals, &perm, expected_shape, expected_vals);
|
||||
}
|
||||
|
||||
|
|
@ -660,10 +682,10 @@ TEST(TransposeOpTest, DoTransposeEltWise) {
|
|||
13.0f, 14.0f, 15.0f, 16.0f};
|
||||
|
||||
std::vector<int64_t> perm = {1, 0, 3, 2};
|
||||
auto expected_vals2 = {1.0f, 3.0f, 2.0f, 4.0f,
|
||||
9.0f, 11.0f, 10.0f, 12.0f,
|
||||
5.0f, 7.0f, 6.0f, 8.0f,
|
||||
13.0f, 15.0f, 14.0f, 16.0f};
|
||||
std::vector<float> expected_vals2 = {1.0f, 3.0f, 2.0f, 4.0f,
|
||||
9.0f, 11.0f, 10.0f, 12.0f,
|
||||
5.0f, 7.0f, 6.0f, 8.0f,
|
||||
13.0f, 15.0f, 14.0f, 16.0f};
|
||||
TransposeTest(input_shape, input_vals, &perm, input_shape, expected_vals2);
|
||||
|
||||
// Specific test which tests that function DoTransposeEltWise does not
|
||||
|
|
@ -797,7 +819,7 @@ TEST(TransposeOpTest, TransposeBigMLFloat16) { // Exercises CanUse_cublasTransp
|
|||
const std::vector<int64_t> Y_dims{1, 1449, 1449, 3};
|
||||
TestTransposeMLFloat16(perm, X_dims, Y_dims);
|
||||
}
|
||||
#endif
|
||||
#endif // defined(USE_CUDA) || defined(USE_ROCM)
|
||||
|
||||
} // namespace test
|
||||
} // namespace onnxruntime
|
||||
|
|
|
|||
Loading…
Reference in a new issue