1 files changed, 9 insertions, 42 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 4e0efbbf3c..15ca36d906 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -2545,11 +2545,9 @@ void TfLiteParserImpl::ParseReshape(size_t subgraphIndex, size_t operatorIndex)
     // If there is no built-in option given or if the built-in new_shape parameter was empty
     if (!targetShapeFound)
     {
-        bool secondInputTensorExists = inputs.size() > 1 && inputs[1] != nullptr;
-        if (secondInputTensorExists)
+        // Check for a second input tensor
+        if (inputs.size() > 1 && inputs[1] != nullptr)
         {
-            armnn::TensorInfo shapeInfo  = ToTensorInfo(inputs[1]);
-
             if (inputs[1]->is_variable)
             {
                 ARMNN_THROW_PARSE_EXCEPTION( "Target shapes defined in non-const input tensors is not supported");
@@ -2565,47 +2563,16 @@ void TfLiteParserImpl::ParseReshape(size_t subgraphIndex, size_t operatorIndex)
                 ARMNN_THROW_PARSE_EXCEPTION("Target 'shape' input is not an int32 type");
             }
 
-            // If the provided shape is constant, we can load in from the buffer ...
-            if (shapeInfo.IsConstant())
+            // Extract target shape from input
+            auto bufferPtr = GetBuffer(m_Model, inputs[1]->buffer);
+            auto values = reinterpret_cast<const int32_t*>(bufferPtr->data.data());
+            if (!values)
             {
-                // Extract target shape from input
-                auto bufferPtr = GetBuffer(m_Model, inputs[1]->buffer);
-                auto values = reinterpret_cast<const int32_t*>(bufferPtr->data.data());
-                if (!values)
-                {
-                    ARMNN_THROW_PARSE_EXCEPTION("Reshape operator target shape input buffer data is null");
-                }
-                for (int i=0; i < inputs[1]->shape[0]; ++i)
-                {
-                    targetShape.push_back(values[i]);
-                }
+                ARMNN_THROW_PARSE_EXCEPTION("Reshape operator target shape input buffer data is null");
             }
-            // ... otherwise, we have to infer it during Runtime.
-            else
+            for (int i=0; i < inputs[1]->shape[0]; ++i)
             {
-                // The parser only supports shape (batch, -1) or (-1) for non-constant shape input.
-                unsigned int dims = shapeInfo.GetNumDimensions();
-                TensorShape shapes = shapeInfo.GetShape();
-                if (dims != 1 || shapes[0] > 2)
-                {
-                    throw ParseException(fmt::format("Invalid input shape '{}' in Reshape layer '{}' {}. "
-                                                    "The parser only supports shape (batch, -1) or (-1) for "
-                                                    "non-constant shape input.",
-                                                    shapes[0],
-                                                    layerName,
-                                                    CHECK_LOCATION().AsString()));
-                }
-
-                const int32_t numInputElements = inputTensorInfo.GetNumElements();
-                const int32_t inputTensorShape = inputTensorInfo.GetShape()[0];
-                if (shapes[0] == 1)
-                {
-                    targetShape = { numInputElements };
-                }
-                else if (shapes[0] == 2)
-                {
-                    targetShape = { inputTensorShape , numInputElements / inputTensorShape };
-                }
+                targetShape.push_back(values[i]);
             }
         }
         else