COMPMID-1995: Prepare Graph to support different input/output quantization info

- Added support for different input/output qinfo in ActivationLayer and DepthwiseConv
- Added support for different input/output qinfo in ConcatenateLayer introducing ConcatDescriptor
- Added reshape validate
- Allow OutputLayer to return a specific connection index from the input
- Not run Inplace and Depth mutator when input/output quantization info are different

Change-Id: I03f5e416fc43ddd284e1501887202a3145f76d8a
Signed-off-by: Isabella Gottardi <isabella.gottardi@arm.com>
Reviewed-on: https://review.mlplatform.org/c/852
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 9 insertions, 4 deletions

diff --git a/utils/GraphUtils.cpp b/utils/GraphUtils.cpp
index b714c55136..26ea02a9ff 100644
--- a/utils/GraphUtils.cpp
+++ b/utils/GraphUtils.cpp
@@ -153,24 +153,29 @@ NumPyAccessor::NumPyAccessor(std::string npy_path, TensorShape shape, DataType d
 }
 
 template <typename T>
-void NumPyAccessor::access_numpy_tensor(ITensor &tensor)
+void NumPyAccessor::access_numpy_tensor(ITensor &tensor, T tolerance)
 {
     const int num_elements          = tensor.info()->tensor_shape().total_size();
-    int       num_mismatches        = utils::compare_tensor<T>(tensor, _npy_tensor);
+    int       num_mismatches        = utils::compare_tensor<T>(tensor, _npy_tensor, tolerance);
     float     percentage_mismatches = static_cast<float>(num_mismatches) / num_elements;
 
     _output_stream << "Results: " << 100.f - (percentage_mismatches * 100) << " % matches with the provided output[" << _filename << "]." << std::endl;
+    _output_stream << "         " << num_elements - num_mismatches << " out of " << num_elements << " matches with the provided output[" << _filename << "]." << std::endl
+                   << std::endl;
 }
 
 bool NumPyAccessor::access_tensor(ITensor &tensor)
 {
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&tensor, 1, DataType::F32);
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&tensor, 1, DataType::F32, DataType::QASYMM8);
     ARM_COMPUTE_ERROR_ON(_npy_tensor.info()->dimension(0) != tensor.info()->dimension(0));
 
     switch(tensor.info()->data_type())
     {
+        case DataType::QASYMM8:
+            access_numpy_tensor<qasymm8_t>(tensor, 0);
+            break;
         case DataType::F32:
-            access_numpy_tensor<float>(tensor);
+            access_numpy_tensor<float>(tensor, 0.0001f);
             break;
         default:
             ARM_COMPUTE_ERROR("NOT SUPPORTED!");