COMPMID-1935 Add support for QASYMM8 in NEQuantizeLayer
Change-Id: I2b63a644d8e34f91c830d9ac398debcbdca3e497
Signed-off-by: John Kesapides <john.kesapides@arm.com>
Reviewed-on: https://review.mlplatform.org/c/829
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/runtime/NEON/functions/NEQuantizationLayer.cpp b/src/runtime/NEON/functions/NEQuantizationLayer.cpp
index 8f7db96..65873b1 100644
--- a/src/runtime/NEON/functions/NEQuantizationLayer.cpp
+++ b/src/runtime/NEON/functions/NEQuantizationLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -26,22 +26,13 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
-#include "arm_compute/runtime/NEON/NEScheduler.h"
using namespace arm_compute;
-NEQuantizationLayer::NEQuantizationLayer()
- : _quantize_kernel(), _min_max_kernel(), _min_max()
-{
-}
-
Status NEQuantizationLayer::validate(const ITensorInfo *input, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
-
- TensorInfo min_max{ input->num_channels(), input->data_type() };
- ARM_COMPUTE_RETURN_ON_ERROR(NEMinMaxLayerKernel::validate(input, &min_max));
- ARM_COMPUTE_RETURN_ON_ERROR(NEQuantizationLayerKernel::validate(input, output, &min_max));
+ ARM_COMPUTE_RETURN_ON_ERROR(NEQuantizationLayerKernel::validate(input, output));
return Status{};
}
@@ -50,24 +41,8 @@
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- // Configure min-max kernel. _min_max tensor will be auto-configured within the kernel
- _min_max_kernel.configure(input, &_min_max);
-
// Configure quantize kernel
- _quantize_kernel.configure(input, output, &_min_max);
-
- // Allocate min_max tensor
- _min_max.allocator()->allocate();
-}
-
-void NEQuantizationLayer::run()
-{
- // Reset min and max
- _min_max_kernel.reset();
-
- // Run min and max kernel
- NEScheduler::get().schedule(&_min_max_kernel, Window::DimY);
-
- // Run quantize kernel
- NEScheduler::get().schedule(&_quantize_kernel, Window::DimY);
+ auto k = arm_compute::support::cpp14::make_unique<NEQuantizationLayerKernel>();
+ k->configure(input, output);
+ _kernel = std::move(k);
}