Testing support for MUL with shift as input

Always create the shift as a tensor for all types in testing.
In the reference model, set the shift operand to be available for
all types, but only read in the shift tensor for i32.

Signed-off-by: Jeremy Johnson <jeremy.johnson@arm.com>
Signed-off-by: TatWai Chong <tatwai.chong@arm.com>
Change-Id: Ia267cbf8b63ca0a9c97b38e8fb4db83eeb8c0538

3 files changed, 49 insertions, 31 deletions

diff --git a/reference_model/src/generate/generate_fixed_data.cc b/reference_model/src/generate/generate_fixed_data.cc
index 3d4ee3e..b0b6c81 100644
--- a/reference_model/src/generate/generate_fixed_data.cc
+++ b/reference_model/src/generate/generate_fixed_data.cc
@@ -20,8 +20,22 @@
 #include <type_traits>
 #include <vector>
 
+namespace
+{
+template <typename OutType>
+bool copyFixedData(const int64_t elements, const std::vector<int32_t> inData, OutType* outData)
+{
+    for (auto t = 0; t < elements; t++)
+    {
+        outData[t] = inData[t];
+    }
+    return true;
+}
+}    // namespace
+
 namespace TosaReference
 {
+
 bool generateFixedData(const GenerateConfig& cfg, void* data, size_t size)
 {
     // Check we support the operator
@@ -31,22 +45,23 @@ bool generateFixedData(const GenerateConfig& cfg, void* data, size_t size)
         return false;
     }
 
+    std::vector<int32_t> inData = cfg.fixedDataInfo.data;
+    const auto T                = TosaReference::numElementsFromShape(cfg.shape);
+    if (T != static_cast<int64_t>(inData.size()))
+    {
+        WARNING("[Generator][FD] Given data size %d does not match output size %d.", inData.size(), T);
+        return false;
+    }
+
     switch (cfg.dataType)
     {
         case DType::DType_SHAPE: {
-            int32_t* outData            = reinterpret_cast<int32_t*>(data);
-            std::vector<int32_t> inData = cfg.fixedDataInfo.data;
-            const auto T                = TosaReference::numElementsFromShape(cfg.shape);
-            if (T != static_cast<int64_t>(inData.size()))
-            {
-                WARNING("[Generator][FD] Size does not match.");
-                return false;
-            }
-            for (auto t = 0; t < T; t++)
-            {
-                outData[t] = inData[t];
-            }
-            return true;
+            int32_t* outData = reinterpret_cast<int32_t*>(data);
+            return copyFixedData(T, inData, outData);
+        }
+        case DType::DType_INT8: {
+            int8_t* outData = reinterpret_cast<int8_t*>(data);
+            return copyFixedData(T, inData, outData);
         }
         default:
             WARNING("[Generator][FD] Unsupported type.");
diff --git a/reference_model/src/ops/ewise_binary.cc b/reference_model/src/ops/ewise_binary.cc
index ed176f3..8cc1319 100644
--- a/reference_model/src/ops/ewise_binary.cc
+++ b/reference_model/src/ops/ewise_binary.cc
@@ -463,11 +463,18 @@ int OpMul<Rank, InDtype, OutDtype>::eval()
         using TInt64      = Eigen::Tensor<int64_t, Rank>;
         TInt64 tmp_result = ia.binaryExpr(ib, this->mul_fcn);
 
-        // Retrieve `shift` value and construct a Eigen tensor instance for it.
-        s = dynamic_cast<TosaReference::TensorTemplate<TShift>*>(this->inputs[2]);
-        ASSERT_MEM(s);
+        // Retrieve `shift` value and construct a Eigen tensor instance for it. Shift is stored
+        // as rank-0 tensor in Flatbuffer.
+        auto s0 = dynamic_cast<TosaReference::TensorTemplate<TShiftRank0>*>(this->inputs[2]);
 
-        int shift = s->getTensor()(0);
+        // Get zero element from rank-0 tensor (i.e. shape = (0,)) in Numpy since `class Tensor`
+        // currenly has no knowledge of the size of rank-0 tensor. Store rank-1 tensor instead
+        // for testing.
+        auto s1 = dynamic_cast<TosaReference::TensorTemplate<TShiftRank1>*>(this->inputs[2]);
+
+        ASSERT_MEM(s0 || s1);
+
+        int shift = s0 ? s0->getTensor()(0) : s1->getTensor()(0);
         TIn is(ia);
         is.setConstant(shift);
 
@@ -486,11 +493,12 @@ int OpMul<0, TOSA_REF_TYPE_INT32, TOSA_REF_TYPE_INT32>::eval()
     Eigen::Tensor<int64_t, 0> tmp_result = this->a->getTensor().binaryExpr(this->b->getTensor(), this->mul_fcn);
 
     // Retrieve `shift` value.
-    s = dynamic_cast<TosaReference::TensorTemplate<TShift>*>(this->inputs[2]);
-    ASSERT_MEM(s);
+    auto s0 = dynamic_cast<TosaReference::TensorTemplate<TShiftRank0>*>(this->inputs[2]);
+    auto s1 = dynamic_cast<TosaReference::TensorTemplate<TShiftRank1>*>(this->inputs[2]);
+    ASSERT_MEM(s0 || s1);
 
     Eigen::Tensor<int64_t, 0> shift;
-    shift.setConstant(s->getTensor()(0));
+    shift.setConstant(s0 ? s0->getTensor()(0) : s1->getTensor()(0));
 
     this->result->getTensor() = tmp_result.binaryExpr(shift, this->shr_fcn);
 
diff --git a/reference_model/src/ops/ewise_binary.h b/reference_model/src/ops/ewise_binary.h
index 8d2e486..7ebd852 100644
--- a/reference_model/src/ops/ewise_binary.h
+++ b/reference_model/src/ops/ewise_binary.h
@@ -159,11 +159,8 @@ public:
     OpMul(SubgraphTraverser* sgt_, TosaAttributeBase* attribute_, uint64_t id_)
         : BinaryNode<Rank, InDtype, OutDtype>(sgt_, Op_MUL, id_)
     {
-        if constexpr (InDtype == TOSA_REF_TYPE_INT32)
-        {
-            // Require `shift` operand.
-            this->setRequiredOperands(3, 1);
-        }
+        // Require `shift` operand.
+        this->setRequiredOperands(3, 1);
         register_fcn();
     }
     static constexpr int64_t QMin = GetQMin<OutDtype>::value;
@@ -173,9 +170,10 @@ public:
     using OutEigenType   = typename GetEigenType<OutDtype>::type;
     using ShiftEigenType = typename GetEigenType<TOSA_REF_TYPE_INT8>::type;
 
-    using TIn    = Eigen::Tensor<InEigenType, Rank>;
-    using TOut   = Eigen::Tensor<OutEigenType, Rank>;
-    using TShift = Eigen::Tensor<ShiftEigenType, 0>;
+    using TIn         = Eigen::Tensor<InEigenType, Rank>;
+    using TOut        = Eigen::Tensor<OutEigenType, Rank>;
+    using TShiftRank0 = Eigen::Tensor<ShiftEigenType, 0>;
+    using TShiftRank1 = Eigen::Tensor<ShiftEigenType, 1>;
 
     int register_fcn();
     int eval();
@@ -183,9 +181,6 @@ public:
     // Note that INT64 is not natively supported in Dtype system.
     std::function<int64_t(InEigenType, InEigenType)> mul_fcn;
     std::function<OutEigenType(int64_t, InEigenType)> shr_fcn;
-
-protected:
-    TosaReference::TensorTemplate<TShift>* s;
 };
 
 template <int Rank, TOSA_REF_TYPE InDtype>