COMPMID-2383: DepthwiseConv use output qinfo

There was a problem in depthwise_conv where when needing to run
permute it was calling auto_init to initialise the temporary tensor
with input's qinfo instead of output's qinfo. This patch fixes
this and adds some tests to exercise the cases where we have different
qinfos

Change-Id: I396fbb4d73f6aa5efe03dc2dd727b3e13154d6f5
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1270
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giuseppe Rossini <giuseppe.rossini@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

3 files changed, 7 insertions, 1 deletions

diff --git a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp
index e912740d69..16082775c3 100644
--- a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp
@@ -90,6 +90,7 @@ void CLDepthwiseConvolutionLayer3x3::configure(ICLTensor *input, const ICLTensor
         // Configure the function to transform the weights tensor from HWI -> IHW
         _permute_weights_to_nchw.configure(weights, &_permuted_weights, PermutationVector(1U, 2U, 0U));
         _permuted_weights.info()->set_data_layout(DataLayout::NCHW);
+        _permuted_output.info()->set_quantization_info(output->info()->quantization_info());
 
         input_to_use   = &_permuted_input;
         weights_to_use = &_permuted_weights;
diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
index 4bc8439d93..43288ec4c6 100644
--- a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp
@@ -87,6 +87,7 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor
         // Configure the function to transform the weights tensor from HWI -> IHW
         _permute_weights.configure(weights, &_permuted_weights, PermutationVector(1U, 2U, 0U));
         _permuted_weights.info()->set_data_layout(DataLayout::NCHW);
+        _permuted_output.info()->set_quantization_info(output->info()->quantization_info());
 
         // Configure depthwise
         _dwc_kernel.configure(&_permuted_input, &_permuted_weights, (_is_quantized) ? &_accumulator : &_permuted_output, conv_info, depth_multiplier, dilation);
@@ -164,6 +165,9 @@ void NEDepthwiseConvolutionLayer3x3::configure_optimized(const ITensor
         _permute_weights.configure(weights, &_permuted_weights, PermutationVector(2U, 0U, 1U));
         _permuted_weights.info()->set_data_layout(DataLayout::NHWC);
 
+        _permuted_output.info()->set_data_layout(DataLayout::NHWC);
+        _permuted_output.info()->set_quantization_info(output->info()->quantization_info());
+
         // Configure optimized depthwise
         _dwc_optimized_func.configure(&_permuted_input, &_permuted_weights, biases, &_permuted_output, conv_info, depth_multiplier, act_info_to_use);
 
@@ -423,6 +427,7 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh
         permute(output_shape, PermutationVector(1U, 2U, 0U));
         _permuted_output.allocator()->init(output->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(output_shape));
         _permuted_output.info()->set_data_layout(DataLayout::NCHW);
+        _permuted_output.info()->set_quantization_info(output->info()->quantization_info());
         output_to_use = &_permuted_output;
     }
 
diff --git a/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp b/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp
index 0499d9930f..5f57bbfe23 100644
--- a/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp
+++ b/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp
@@ -176,7 +176,7 @@ void NEDepthwiseConvolutionAssemblyDispatch::configure(const ITensor
 
     // Output auto inizialitation if not yet initialized
     const TensorShape output_shape = misc::shape_calculator::compute_depthwise_convolution_shape(*input->info(), *weights->info(), conv_info, depth_multiplier);
-    auto_init_if_empty(*output->info(), input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(output_shape));
+    auto_init_if_empty(*output->info(), input->info()->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(output_shape).set_quantization_info(output->info()->quantization_info()));
 
     _input       = input;
     _weights     = weights;