Revert "IVGCVSW-6252 Armnn Error: Failed to parse operator #1 within subgraph #0 error: Operator not supported"

This reverts commit 9fc259682c8b85af58bda42e87703bbec5ae57ce.

Fixes: IVGCVSW-6644 ExecuteNetwork tests failing with invalid input shape in Reshape layer

Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I561e0bd9ed1b92491cb8a08635042e199dd661d8

3 files changed, 9 insertions, 215 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
index d08641431d..fde058216b 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -718,7 +718,6 @@ if(BUILD_UNIT_TESTS)
              src/armnnTfLiteParser/test/Prelu.cpp
              src/armnnTfLiteParser/test/Reduce.cpp
              src/armnnTfLiteParser/test/Reshape.cpp
-             src/armnnTfLiteParser/test/ReshapeDynamic.cpp
              src/armnnTfLiteParser/test/ResizeBilinear.cpp
              src/armnnTfLiteParser/test/ResizeNearestNeighbor.cpp
              src/armnnTfLiteParser/test/Quantize.cpp
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
diff --git a/src/armnnTfLiteParser/test/ReshapeDynamic.cpp b/src/armnnTfLiteParser/test/ReshapeDynamic.cpp
deleted file mode 100644
index ca993fb90c..0000000000
--- a/src/armnnTfLiteParser/test/ReshapeDynamic.cpp
+++ /dev/null
@@ -1,172 +0,0 @@
-//
-// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include "ParserFlatbuffersFixture.hpp"
-
-
-TEST_SUITE("TensorflowLiteParser_Reshape_Dynamic")
-{
-struct ReshapeDynamicFixture : public ParserFlatbuffersFixture
-{
-    explicit ReshapeDynamicFixture()
-    {
-        m_JsonString = R"(
-{
-  "version": 3,
-  "operator_codes": [
-    {
-      "deprecated_builtin_code": 77,
-      "version": 1,
-      "builtin_code": "ADD"
-    },
-    {
-      "deprecated_builtin_code": 22,
-      "version": 1,
-      "builtin_code": "ADD"
-    }
-  ],
-  "subgraphs": [
-    {
-      "tensors": [
-        {
-          "shape": [
-            1,
-            9
-          ],
-          "type": "FLOAT32",
-          "buffer": 1,
-          "name": "input_33",
-          "quantization": {
-            "details_type": "NONE",
-            "quantized_dimension": 0
-          },
-          "is_variable": false,
-          "shape_signature": [
-            -1,
-            9
-          ]
-        },
-        {
-          "shape": [
-            2
-          ],
-          "type": "INT32",
-          "buffer": 2,
-          "name": "functional_15/tf_op_layer_Shape_9/Shape_9",
-          "quantization": {
-            "details_type": "NONE",
-            "quantized_dimension": 0
-          },
-          "is_variable": false
-        },
-        {
-          "shape": [
-            1,
-            9
-          ],
-          "type": "FLOAT32",
-          "buffer": 3,
-          "name": "Identity",
-          "quantization": {
-            "details_type": "NONE",
-            "quantized_dimension": 0
-          },
-          "is_variable": false,
-          "shape_signature": [
-            -1,
-            9
-          ]
-        }
-      ],
-      "inputs": [
-        0
-      ],
-      "outputs": [
-        2
-      ],
-      "operators": [
-        {
-          "opcode_index": 0,
-          "inputs": [
-            0
-          ],
-          "outputs": [
-            1
-          ],
-          "builtin_options_type": "ShapeOptions",
-          "builtin_options": {
-            "out_type": "INT32"
-          },
-          "custom_options_format": "FLEXBUFFERS"
-        },
-        {
-          "opcode_index": 1,
-          "inputs": [
-            0,
-            1
-          ],
-          "outputs": [
-            2
-          ],
-          "builtin_options_type": "NONE",
-          "custom_options_format": "FLEXBUFFERS"
-        }
-      ],
-      "name": "main"
-    }
-  ],
-  "description": "MLIR Converted.",
-  "buffers": [
-    {
-    },
-    {
-    },
-    {
-    },
-    {
-    },
-    {
-      "data": [
-        49,
-        46,
-        49,
-        48,
-        46,
-        48,
-        0,
-        0,
-        0,
-        0,
-        0,
-        0,
-        0,
-        0,
-        0,
-        0
-      ]
-    }
-  ],
-  "metadata": [
-    {
-      "name": "min_runtime_version",
-      "buffer": 4
-    }
-  ]
-}
-)";
-
-    }
-};
-
-TEST_CASE_FIXTURE(ReshapeDynamicFixture, "ParseReshapeDynamic")
-{
-    SetupSingleInputSingleOutput("input_33", "Identity");
-    RunTest<2, armnn::DataType::Float32>(0,
-                                                 { 1, 2, 3, 4, 5, 6, 7, 8, 9 },
-                                                 { 1, 2, 3, 4, 5, 6, 7, 8, 9 });
-    CHECK((m_Parser->GetNetworkOutputBindingInfo(0, "Identity").second.GetShape()
-                == armnn::TensorShape({1,9})));
-}
-}
\ No newline at end of file