Perform weights datatype check for slice (#632)

Signed-off-by: Kevin Chen <kevinch@nvidia.com>

Author: kevinch-nv

builtin_op_importers.cpp

@@ -3073,6 +3073,7 @@ ShapeTensor computeSizes(IImporterContext* ctx, const ShapeTensor& starts, const
 
 DEFINE_BUILTIN_OP_IMPORTER(Slice)
 {
+    ASSERT(validateInputs(inputs), ErrorCode::kUNSUPPORTED_NODE);
     const int nbInputs = node.input().size();
     // "...it uses this information to slice the input data tensor."
     nvinfer1::ITensor& data = convertToTensor(inputs.at(0), ctx);

onnx2trt_utils.cpp

@@ -1806,6 +1806,20 @@ int64_t volume(const nvinfer1::Dims& dims)
     return std::accumulate(dims.d, dims.d + dims.nbDims, 1, std::multiplies<int64_t>{});
 }
 
+bool validateInputs(std::vector<TensorOrWeights>& inputs)
+{
+    nvinfer1::DataType type = nvinfer1::DataType::kFLOAT;
+    bool valid = true;
+    for (auto& input : inputs)
+    {
+        if (input.is_weights())
+        {
+            valid = valid && convertDtype(input.weights().type, &type);
+        }
+    }
+    return valid;
+}
+
 Status weightsToVector(TensorOrWeights weights, std::vector<int64_t>* weightVector)
 {
     ASSERT(weights.is_weights(), ErrorCode::kUNSUPPORTED_NODE);

onnx2trt_utils.hpp

@@ -304,6 +304,9 @@ NodeImportResult unaryHelper(IImporterContext* ctx, const ::ONNX_NAMESPACE::Node
 // Helper function to unsqueeze tensors on a given set of axes
 nvinfer1::ITensor* unsqueezeTensor(IImporterContext* ctx, const ::ONNX_NAMESPACE::NodeProto& node, nvinfer1::ITensor& tensor, const std::vector<int>& axes, bool regLayer = false);
 
+// Helper function to validate inputs and receive type information
+bool validateInputs(std::vector<TensorOrWeights>& inputs);
+
 // Helper function to convert a ShapedWeights object into a vector
 Status weightsToVector(TensorOrWeights weights, std::vector<int64_t>* weightVector);