COMPMID-970 : Remove QS8 / QS16 support

Removed fixed point related code.

Change-Id: I487acf138dace3b0450e0d72ca7071eaec254566
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/137678
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

6 files changed, 15 insertions, 21 deletions

diff --git a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp
index 4c1ea5b9a2..9f3dc78022 100644
--- a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp
@@ -64,12 +64,10 @@ Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInf
     const TensorShape output_shape = deconvolution_output_shape(out_dims, input->tensor_shape(), weights->tensor_shape());
 
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights);
-    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output, weights);
 
     if(bias != nullptr)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias);
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, bias);
     }
 
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimX) != output_shape.x(), "Output's width is invalid.");
@@ -100,7 +98,7 @@ void CLDeconvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights,
     const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape());
 
     // Output auto initialization if not yet initialized
-    auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position());
+    auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type());
 
     // Perform validation step
     ARM_COMPUTE_ERROR_THROW_ON(CLDeconvolutionLayer::validate(input->info(), weights->info(), bias == nullptr ? nullptr : bias->info(), output->info(), info, inner_border_right, inner_border_top));
@@ -116,7 +114,7 @@ void CLDeconvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights,
     const unsigned int out_y = input->info()->dimension(1) + (input->info()->dimension(1) - 1) * (stride_y - 1) + inner_border_top + 2 * info.pad().second;
     scale_out_shape.set(0, out_x);
     scale_out_shape.set(1, out_y);
-    TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->fixed_point_position());
+    TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type());
     _scaled_output.allocator()->init(scale_out_info);
 
     _scale_f.configure(input, &_scaled_output, BorderSize(inner_border_top, inner_border_right), info);
diff --git a/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp b/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp
index 26d46a438c..0b26f55a29 100644
--- a/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp
+++ b/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp
@@ -55,7 +55,7 @@ void CLDepthConcatenateLayer::configure(std::vector<ICLTensor *> inputs_vector,
     TensorShape output_shape = calculate_depth_concatenate_shape(inputs_vector);
 
     // Output auto inizialitation if not yet initialized
-    auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type(), inputs_vector[0]->info()->fixed_point_position());
+    auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
 
     for(unsigned int i = 0; i < _num_inputs; i++)
     {
diff --git a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
index 9248bc559b..273ef96a03 100644
--- a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
+++ b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp
@@ -232,7 +232,7 @@ Status CLFullyConnectedLayer::validate(const ITensorInfo *input, const ITensorIn
 {
     ARM_COMPUTE_UNUSED(retain_internal_weights);
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::F16, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, output);
     ARM_COMPUTE_RETURN_ERROR_ON(weights->num_dimensions() > 2);
 
diff --git a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
index ace3379618..f1d2924c92 100644
--- a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
@@ -62,7 +62,7 @@ void CLConvolutionLayerReshapeWeights::configure(const ICLTensor *weights, const
 Status CLConvolutionLayerReshapeWeights::validate(const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(weights);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::F16, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON(weights->num_dimensions() > 4);
 
     if(biases != nullptr)
@@ -77,7 +77,6 @@ Status CLConvolutionLayerReshapeWeights::validate(const ITensorInfo *weights, co
     if((output != nullptr) && (output->total_size() != 0))
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, output);
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(weights, output);
 
         CLWeightsReshapeKernel::validate(weights, biases, output);
     }
@@ -233,7 +232,7 @@ void CLGEMMConvolutionLayer::configure(const ICLTensor *input, const ICLTensor *
         shape_im2col.set(1, conv_w * conv_h);
 
         // FIXME: input->clone() doesn't work with subtensors for grouped convolutions.
-        TensorInfo im2col_reshaped_info(shape_im2col, 1, data_type, input->info()->fixed_point_position());
+        TensorInfo im2col_reshaped_info(shape_im2col, 1, data_type);
         im2col_reshaped_info.set_quantization_info(input->info()->quantization_info());
         _im2col_output.allocator()->init(im2col_reshaped_info);
         _memory_group.manage(&_im2col_output);
@@ -257,7 +256,7 @@ void CLGEMMConvolutionLayer::configure(const ICLTensor *input, const ICLTensor *
         // GEMM output should be S32 for acquiring raw integer accumulator without quantized postprocessing for quantized asymmetric input.
         const DataType gemm_data_type = _is_quantized ? DataType::S32 : data_type;
         // FIXME: input->clone() doesn't work with subtensors for grouped convolutions.
-        TensorInfo info_gemm(shape_gemm, 1, gemm_data_type, input->info()->fixed_point_position());
+        TensorInfo info_gemm(shape_gemm, 1, gemm_data_type);
         info_gemm.set_quantization_info(output->info()->quantization_info());
         _gemm_output.allocator()->init(info_gemm);
         _memory_group.manage(&_gemm_output);
@@ -326,10 +325,9 @@ Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output);
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights_info.are_reshaped(), "Weights already reshaped are not supported!");
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::QS16, DataType::F16, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, weights);
-    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, weights);
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::QASYMM8 && input->data_layout() == DataLayout::NHWC,
                                     "NHWC is unsupported for QASYMM8!");
 
@@ -369,7 +367,6 @@ Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI
         {
             ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, biases);
         }
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, biases);
         ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(idx_kernels));
         ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1);
     }
@@ -395,7 +392,7 @@ Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI
 
     // Output tensor auto inizialitation if not yet initialized
     ARM_COMPUTE_RETURN_ON_ERROR(CLConvolutionLayerReshapeWeights::validate(weights, is_quantized ? nullptr : biases, nullptr));
-    weights_reshaped_info = TensorInfo(compute_weights_reshaped_shape(*weights, append_bias), 1, data_type, weights->fixed_point_position());
+    weights_reshaped_info = TensorInfo(compute_weights_reshaped_shape(*weights, append_bias), 1, data_type);
     weights_to_use        = &weights_reshaped_info;
 
     if(!skip_im2col)
@@ -408,7 +405,7 @@ Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI
         }
         shape_im2col.set(0, mat_weights_rows);
         shape_im2col.set(1, conv_w * conv_h);
-        im2col_reshaped_info = TensorInfo(shape_im2col, 1, data_type, input->fixed_point_position());
+        im2col_reshaped_info = TensorInfo(shape_im2col, 1, data_type);
         im2col_reshaped_info.set_quantization_info(input->quantization_info());
         ARM_COMPUTE_RETURN_ON_ERROR(CLIm2ColKernel::validate(input, &im2col_reshaped_info, Size2D(kernel_width, kernel_height), conv_info, append_bias, dilation));
         gemm_input_to_use = &im2col_reshaped_info;
@@ -422,7 +419,7 @@ Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI
         shape_gemm.set(1, conv_w * conv_h);
         const DataType gemm_data_type = is_quantized ? DataType::S32 : data_type;
         // GEMM output should be S32 for acquiring raw integer accumulator without quantized postprocessing for quantized asymmetric input.
-        info_gemm = TensorInfo(shape_gemm, 1, gemm_data_type, input->fixed_point_position());
+        info_gemm = TensorInfo(shape_gemm, 1, gemm_data_type);
         info_gemm.set_quantization_info(output->quantization_info());
         gemm_output_to_use = &info_gemm;
     }
@@ -436,7 +433,7 @@ Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI
         quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
         if(!is_nhwc)
         {
-            tmp_info = TensorInfo(gemm_output_to_use->tensor_shape(), 1, DataType::QASYMM8, input->fixed_point_position());
+            tmp_info = TensorInfo(gemm_output_to_use->tensor_shape(), 1, DataType::QASYMM8);
             tmp_info.set_quantization_info(output->quantization_info());
             gemm_output_staged_to_use = &tmp_info;
         }
diff --git a/src/runtime/CL/functions/CLReductionOperation.cpp b/src/runtime/CL/functions/CLReductionOperation.cpp
index 3a5133d91f..2a171c3969 100644
--- a/src/runtime/CL/functions/CLReductionOperation.cpp
+++ b/src/runtime/CL/functions/CLReductionOperation.cpp
@@ -71,7 +71,6 @@ Status CLReductionOperation::validate(const ITensorInfo *input, const ITensorInf
         sums_vector[i].set_data_type(input->data_type());
         sums_vector[i].set_tensor_shape(shape);
         sums_vector[i].set_num_channels(input->num_channels());
-        sums_vector[i].set_fixed_point_position(input->fixed_point_position());
     }
 
     // Validate ReductionOperation only on first kernel
@@ -105,7 +104,7 @@ void CLReductionOperation::configure(ICLTensor *input, ICLTensor *output, unsign
     for(unsigned int i = 0; i < _num_of_stages - 1; i++)
     {
         shape.set(0, ceil(shape.x() / 128.f));
-        _sums_vector[i].allocator()->init(TensorInfo(shape, input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position()));
+        _sums_vector[i].allocator()->init(TensorInfo(shape, input->info()->num_channels(), input->info()->data_type()));
     }
 
     // Apply ReductionOperation only on first kernel
diff --git a/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp b/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp
index d5427819c3..5233ff4f52 100644
--- a/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp
+++ b/src/runtime/CL/functions/CLWidthConcatenateLayer.cpp
@@ -48,7 +48,7 @@ Status CLWidthConcatenateLayer::validate(const std::vector<ITensorInfo *> &input
     // Output auto inizialitation if not yet initialized
     TensorInfo  tmp_output_info = *output->clone();
     TensorShape output_shape    = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(inputs_vector);
-    auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type(), inputs_vector[0]->fixed_point_position());
+    auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
 
     unsigned int width_offset = 0;
     for(const auto &input : inputs_vector)
@@ -73,7 +73,7 @@ void CLWidthConcatenateLayer::configure(std::vector<ICLTensor *> inputs_vector,
     TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(inputs_vector);
 
     // Output auto inizialitation if not yet initialized
-    auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type(), inputs_vector[0]->info()->fixed_point_position());
+    auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
     ARM_COMPUTE_ERROR_THROW_ON(CLWidthConcatenateLayer::validate(inputs_vector_info, output->info()));
 
     unsigned int width_offset = 0;