COMPMID-3163: Remove padding from NEDepthwiseConvolutionLayerNativeKernel

Change-Id: Ibbd6bee5c6a4ce4f212b207d17a65b9c33bcfa78
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4106
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

3 files changed, 12 insertions, 12 deletions

diff --git a/arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.h b/arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.h
index 2e29234b6f..335a70fc2b 100644
--- a/arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.h
+++ b/arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.h
@@ -25,7 +25,7 @@
 #define ARM_COMPUTE_NEDEPTHWISECONVOLUTIONLAYERNATIVEKERNEL_H
 
 #include "arm_compute/core/NEON/INEKernel.h"
-#include "arm_compute/core/utils/misc/Requires.h"
+#include "arm_compute/core/utils/misc/Traits.h"
 
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 #include <arm_neon.h>
@@ -92,18 +92,18 @@ public:
 
     // Inherited methods overridden:
     void run(const Window &window, const ThreadInfo &info) override;
-    BorderSize border_size() const override;
 
 private:
-    template < typename T, typename TW, int S, typename std::enable_if < std::is_same<T, float>::value
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-                                                                         || std::is_same<T, float16_t>::value
-#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-                                                                         ,
-                                                                         int >::type = 0 >
+    template <typename T>
+    using FloatEnalber = typename std::enable_if<arm_compute::utils::traits::is_floating_point<T>::value, int>::type;
+
+    template <typename T, typename TW, FloatEnalber<T> = 0>
     void run_depthwise(const Window &window, bool has_biases);
 
-    template < typename T, typename TW, int S, REQUIRES_TA(std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value) >
+    template <typename T>
+    using Quantized8bitEnalber = typename std::enable_if < std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int >::type;
+
+    template <typename T, typename TW, Quantized8bitEnalber<T> = 0>
     void run_depthwise(const Window &window, bool has_biases);
 
     /** Common signature for all the specialised depthwise convolution native functions
@@ -113,7 +113,6 @@ private:
     using DepthwiseFunctionPtr = void (NEDepthwiseConvolutionLayerNativeKernel::*)(const Window &window, bool has_biases);
 
     DepthwiseFunctionPtr _func;
-    BorderSize           _border_size;
     const ITensor       *_input;
     const ITensor       *_weights;
     const ITensor       *_biases;
diff --git a/arm_compute/core/Window.h b/arm_compute/core/Window.h
index 2ba5440c68..150320a90e 100644
--- a/arm_compute/core/Window.h
+++ b/arm_compute/core/Window.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2016-2019 Arm Limited.
+ * Copyright (c) 2016-2020 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -45,6 +45,8 @@ public:
     static constexpr size_t DimY = 1;
     /** Alias for dimension 2 also known as Z dimension */
     static constexpr size_t DimZ = 2;
+    /** Alias for dimension 3 also known as W dimension */
+    static constexpr size_t DimW = 3;
 
     /** Default constructor: create a window containing a single element. */
     constexpr Window()
diff --git a/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h
index 3b75bb11a7..c6b98ed435 100644
--- a/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h
@@ -249,7 +249,6 @@ private:
 
     private:
         NEDepthwiseConvolutionLayerNativeKernel _depthwise_conv_kernel;
-        NEFillBorderKernel                      _fill_border;
         NEPermute                               _permute_input;
         NEPermute                               _permute_weights;
         NEPermute                               _permute_output;