Merge "Add shape check to CAST validation" into rvc-dev

3 files changed, 98 insertions, 2 deletions

diff --git a/nn/common/Utils.cpp b/nn/common/Utils.cpp
index fedc8cb30..4e4d0e06a 100644
--- a/nn/common/Utils.cpp
+++ b/nn/common/Utils.cpp
@@ -26,7 +26,10 @@
 #include <sys/system_properties.h>
 
 #include <algorithm>
+#include <functional>
+#include <iostream>
 #include <limits>
+#include <numeric>
 #include <set>
 #include <string>
 #include <tuple>
@@ -1509,8 +1512,10 @@ int validateOperation(ANeuralNetworksOperationType opType, uint32_t inputCount,
                 logInvalidInOutNumber(1, 1);
                 return ANEURALNETWORKS_BAD_DATA;
             }
-            auto inputType = operands[inputIndexes[0]].type;
-            auto outputType = operands[outputIndexes[0]].type;
+            auto inputOperand = operands[inputIndexes[0]];
+            auto outputOperand = operands[outputIndexes[0]];
+            auto inputType = inputOperand.type;
+            auto outputType = outputOperand.type;
             std::vector<OperandType> inExpectedTypes;
             std::vector<OperandType> outExpectedTypes;
             if ((inputType == OperandType::TENSOR_FLOAT16 ||
@@ -1536,6 +1541,19 @@ int validateOperation(ANeuralNetworksOperationType opType, uint32_t inputCount,
                 LOG(ERROR) << "Unsupported data type for operation " << getOperationName(opType);
                 return ANEURALNETWORKS_BAD_DATA;
             }
+            // Validate that output shape is equal to input shape if dimensions
+            // are already known.
+            auto getNumberOfElements = [](const hardware::hidl_vec<uint32_t>& dims) {
+                if (dims.size() == 0) {
+                    return 0;
+                }
+                return std::accumulate(dims.begin(), dims.end(), 1, std::multiplies<>());
+            };
+            if (inputOperand.dimensions.size() != 0 && outputOperand.dimensions.size() != 0 &&
+                getNumberOfElements(outputOperand.dimensions) != 0 &&
+                inputOperand.dimensions != outputOperand.dimensions) {
+                return ANEURALNETWORKS_BAD_DATA;
+            }
             return validateOperationOperandTypes(operands, inputCount, inputIndexes,
                                                  inExpectedTypes, outputCount, outputIndexes,
                                                  outExpectedTypes);
diff --git a/nn/runtime/test/generated/spec_V1_3_cts_only/cast_mismatching_shapes.example.cpp b/nn/runtime/test/generated/spec_V1_3_cts_only/cast_mismatching_shapes.example.cpp
new file mode 100644
index 000000000..24ba83438
--- /dev/null
+++ b/nn/runtime/test/generated/spec_V1_3_cts_only/cast_mismatching_shapes.example.cpp
@@ -0,0 +1,53 @@
+// Generated from cast_mismatching_shapes.mod.py
+// DO NOT EDIT
+// clang-format off
+#include "TestHarness.h"
+using namespace test_helper;
+
+namespace generated_tests::cast_mismatching_shapes {
+
+const TestModel& get_test_model() {
+    static TestModel model = {
+        .expectFailure = true,
+        .expectedMultinomialDistributionTolerance = 0,
+        .isRelaxed = false,
+        .main = {
+                .inputIndexes = {0},
+                .operands = {{ // input0
+                            .channelQuant = {},
+                            .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 4, 5, 6}),
+                            .dimensions = {2, 3},
+                            .isIgnored = false,
+                            .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+                            .numberOfConsumers = 1,
+                            .scale = 0.0f,
+                            .type = TestOperandType::TENSOR_INT32,
+                            .zeroPoint = 0
+                        }, { // output0
+                            .channelQuant = {},
+                            .data = TestBuffer::createFromVector<int32_t>({1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}),
+                            .dimensions = {100},
+                            .isIgnored = false,
+                            .lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT,
+                            .numberOfConsumers = 0,
+                            .scale = 0.0f,
+                            .type = TestOperandType::TENSOR_INT32,
+                            .zeroPoint = 0
+                        }},
+                .operations = {{
+                            .inputs = {0},
+                            .outputs = {1},
+                            .type = TestOperationType::CAST
+                        }},
+                .outputIndexes = {1}
+            },
+        .minSupportedVersion = TestHalVersion::UNKNOWN,
+        .referenced = {}
+    };
+    return model;
+}
+
+const auto dummy_test_model = TestModelManager::get().add("cast_mismatching_shapes", get_test_model());
+
+}  // namespace generated_tests::cast_mismatching_shapes
+
diff --git a/nn/runtime/test/specs/V1_3_cts_only/cast_mismatching_shapes.mod.py b/nn/runtime/test/specs/V1_3_cts_only/cast_mismatching_shapes.mod.py
new file mode 100644
index 000000000..c718e5cc2
--- /dev/null
+++ b/nn/runtime/test/specs/V1_3_cts_only/cast_mismatching_shapes.mod.py
@@ -0,0 +1,25 @@
+#
+# Copyright (C) 2020 The Android Open Source Project
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+input0 = Input("input0", "TENSOR_INT32", "{2, 3}")
+output0 = Output("output0", "TENSOR_INT32", "{100}")
+
+model = Model().Operation("CAST", input0).To(output0)
+
+example = Example({
+    input0: [1, 2, 3, 4, 5, 6],
+    output0: [1, 2, 3, 4, 5, 6] + [0] * 94,
+}, model=model).ExpectFailure()