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authorMichalis Spyrou <michalis.spyrou@arm.com>2019-10-02 17:22:11 +0100
committerMichalis Spyrou <michalis.spyrou@arm.com>2019-10-08 09:08:50 +0000
commit6bff195a51915fd88c1aa1904cf269dbd1a04f50 (patch)
tree645fc3bb8f6bbe05aeb16385a52a696973da0b73
parent6665f82b38ce904aa588230546d66e65d38f20d6 (diff)
downloadComputeLibrary-6bff195a51915fd88c1aa1904cf269dbd1a04f50.tar.gz
COMPMID-2486: Remove disabled compiler warnings
Removed -Wno-unused-parameter and -Wno-deprecated-declarations compilation flags. Plus, 3RDPARTY_UPDATE. Change-Id: I43098c7af527d5651aad3c597b508a56f8813dda Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com> Reviewed-on: https://review.mlplatform.org/c/2041 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
m---------3rdparty0
-rw-r--r--SConstruct6
-rw-r--r--arm_compute/core/CL/OpenCL.h1
-rw-r--r--arm_compute/core/Helpers.inl1
-rw-r--r--arm_compute/core/NEON/NEColorConvertHelper.inl48
-rw-r--r--arm_compute/core/NEON/kernels/NEBoundingBoxTransformKernel.h2
-rw-r--r--arm_compute/core/NEON/kernels/NEGenerateProposalsLayerKernel.h2
-rw-r--r--arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedMatrixMultiplyWrapper.h2
-rw-r--r--arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h2
-rw-r--r--arm_compute/core/NEON/kernels/assembly/gemm_common.hpp4
-rw-r--r--arm_compute/core/NEON/wrapper/intrinsics/inv.h1
-rw-r--r--arm_compute/core/Validate.h1
-rw-r--r--arm_compute/core/utils/logging/LogMsgDecorators.h3
-rw-r--r--arm_compute/core/utils/misc/ShapeCalculator.h2
-rw-r--r--arm_compute/core/utils/misc/Utility.h3
-rw-r--r--arm_compute/graph/INodeVisitor.h50
-rw-r--r--arm_compute/graph/backends/FunctionHelpers.h3
-rw-r--r--arm_compute/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.h1
-rw-r--r--arm_compute/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.h1
-rw-r--r--examples/graph_deepspeech_v0_4_1.cpp35
-rw-r--r--src/core/CL/OpenCL.cpp3
-rw-r--r--src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp1
-rw-r--r--src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp5
-rw-r--r--src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp12
-rw-r--r--src/core/NEON/kernels/NEDepthConvertLayerKernel.cpp26
-rw-r--r--src/core/NEON/kernels/NEDequantizationLayerKernel.cpp2
-rw-r--r--src/core/NEON/kernels/NEGenerateProposalsLayerKernel.cpp10
-rw-r--r--src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp4
-rw-r--r--src/core/NEON/kernels/arm_gemm/buffer_manager.hpp16
-rw-r--r--src/core/NEON/kernels/arm_gemm/gemm_hybrid.hpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/gemv_batched.hpp2
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s16_12x8.hpp2
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s8_4x4.hpp2
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u16_12x8.hpp2
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u8_4x4.hpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_nativeA_pretransposeB_16x4.hpp2
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_native_16x4.hpp2
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_pretransposed.hpp2
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_trans.hpp2
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/a55.cpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/generic.cpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/a55.cpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/generic.cpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/a55.cpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/generic.cpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/a55.cpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/generic.cpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/merges/a64_merge_int32_12x8.hpp1
-rw-r--r--src/core/NEON/kernels/arm_gemm/utils.hpp2
-rw-r--r--src/runtime/CL/CLHelpers.cpp1
-rw-r--r--src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp1
-rw-r--r--src/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.cpp4
-rw-r--r--src/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.cpp7
-rw-r--r--support/ToolchainSupport.h22
-rw-r--r--tests/AssetsLibrary.h5
-rw-r--r--tests/SConscript8
-rw-r--r--tests/Utils.h2
-rw-r--r--tests/benchmark/fixtures/ConvolutionFixture.h12
-rw-r--r--tests/benchmark/fixtures/DepthwiseConvolutionLayerFixture.h2
-rw-r--r--tests/benchmark/fixtures/ElementWiseUnaryFixture.h14
-rw-r--r--tests/validate_examples/ValidateExample.h4
-rw-r--r--tests/validate_examples/graph_validate_utils.h1
-rw-r--r--tests/validation/CL/GlobalPoolingLayer.cpp6
-rw-r--r--tests/validation/CL/Permute.cpp5
-rw-r--r--tests/validation/CPP/Permute.cpp7
-rw-r--r--tests/validation/NEON/Permute.cpp7
-rw-r--r--tests/validation/UNIT/LifetimeManager.cpp1
-rw-r--r--tests/validation/fixtures/DropoutLayerFixture.h3
-rw-r--r--tests/validation/fixtures/FullyConnectedLayerFixture.h7
-rw-r--r--tests/validation/fixtures/FuseBatchNormalizationFixture.h4
-rw-r--r--tests/validation/fixtures/GEMMFixture.h53
-rw-r--r--tests/validation/fixtures/GEMMTranspose1xWFixture.h6
-rw-r--r--tests/validation/fixtures/InstanceNormalizationLayerFixture.h4
-rw-r--r--tests/validation/fixtures/PermuteFixture.h8
-rw-r--r--tests/validation/fixtures/PoolingLayerFixture.h2
-rw-r--r--tests/validation/fixtures/UNIT/DynamicTensorFixture.h1
-rw-r--r--tests/validation/fixtures/WarpPerspectiveFixture.h12
-rw-r--r--tests/validation/fixtures/WinogradConvolutionLayerFixture.h22
-rw-r--r--tests/validation/reference/ColorConvert.cpp6
-rw-r--r--tests/validation/reference/ColorConvertHelper.h4
-rw-r--r--tests/validation/reference/ROIAlignLayer.cpp2
-rw-r--r--utils/GraphUtils.cpp4
-rw-r--r--utils/GraphUtils.h2
-rw-r--r--utils/ImageLoader.h9
-rw-r--r--utils/Utils.cpp5
-rw-r--r--utils/Utils.h18
86 files changed, 326 insertions, 231 deletions
diff --git a/3rdparty b/3rdparty
-Subproject 82e582f5359ab572452c6df6b6be50c93963840
+Subproject fdefd7169e204b83bdc43b78c55add387f9cbbe
diff --git a/SConstruct b/SConstruct
index 33cc72cf0..5f966563f 100644
--- a/SConstruct
+++ b/SConstruct
@@ -129,11 +129,11 @@ if not env['exceptions']:
env.Append(CPPDEFINES = ['ARM_COMPUTE_EXCEPTIONS_DISABLED'])
env.Append(CXXFLAGS = ['-fno-exceptions'])
-env.Append(CXXFLAGS = ['-Wno-deprecated-declarations','-Wall','-DARCH_ARM',
- '-Wextra','-Wno-unused-parameter','-pedantic','-Wdisabled-optimization','-Wformat=2',
+env.Append(CXXFLAGS = ['-Wall','-DARCH_ARM',
+ '-Wextra','-pedantic','-Wdisabled-optimization','-Wformat=2', '-Wno-format-nonliteral',
'-Winit-self','-Wstrict-overflow=2','-Wswitch-default',
'-fpermissive','-std=gnu++11','-Wno-vla','-Woverloaded-virtual',
- '-Wctor-dtor-privacy','-Wsign-promo','-Weffc++','-Wno-format-nonliteral','-Wno-overlength-strings','-Wno-strict-overflow'])
+ '-Wctor-dtor-privacy','-Wsign-promo','-Weffc++','-Wno-overlength-strings','-Wno-strict-overflow'])
env.Append(CPPDEFINES = ['_GLIBCXX_USE_NANOSLEEP'])
diff --git a/arm_compute/core/CL/OpenCL.h b/arm_compute/core/CL/OpenCL.h
index fc7083d27..912a53103 100644
--- a/arm_compute/core/CL/OpenCL.h
+++ b/arm_compute/core/CL/OpenCL.h
@@ -37,6 +37,7 @@
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Weffc++"
#pragma GCC diagnostic ignored "-Wignored-qualifiers"
+#pragma GCC diagnostic ignored "-Wunused-parameter"
#if defined(__GNUG__) && __GNUG__ >= 8
#pragma GCC diagnostic ignored "-Wcatch-value"
#endif // defined(__GNUG__) && __GNUG__ >= 8
diff --git a/arm_compute/core/Helpers.inl b/arm_compute/core/Helpers.inl
index aeb290b23..29f31c12c 100644
--- a/arm_compute/core/Helpers.inl
+++ b/arm_compute/core/Helpers.inl
@@ -114,6 +114,7 @@ struct ForEachDimension<0>
template <typename L, typename... Ts>
static void unroll(const Window &w, Coordinates &id, L &&lambda_function, Ts &&... iterators)
{
+ ARM_COMPUTE_UNUSED(w, iterators...);
lambda_function(id);
}
};
diff --git a/arm_compute/core/NEON/NEColorConvertHelper.inl b/arm_compute/core/NEON/NEColorConvertHelper.inl
index 7540d3383..68f437116 100644
--- a/arm_compute/core/NEON/NEColorConvertHelper.inl
+++ b/arm_compute/core/NEON/NEColorConvertHelper.inl
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2016-2018 ARM Limited.
+ * Copyright (c) 2016-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -80,12 +80,12 @@ inline void convert_float32x4x4_to_unit8x16(const float32x4x4_t &in, uint8x16_t
out = vcombine_u8(vqmovn_u16(low), vqmovn_u16(high));
}
-inline float32x4_t rgb_to_greyscale_calculation(const float32x4_t &rcolor,const float32x4_t &gcolor, const float32x4_t &bcolor,
- const float rcoef, const float gcoef, const float bcoef)
+inline float32x4_t rgb_to_greyscale_calculation(const float32x4_t &rcolor, const float32x4_t &gcolor, const float32x4_t &bcolor,
+ const float rcoef, const float gcoef, const float bcoef)
{
float32x4_t greyscale = vmulq_n_f32(rcolor, rcoef);
- greyscale = vmlaq_n_f32(greyscale, gcolor, gcoef);
- greyscale = vmlaq_n_f32(greyscale, bcolor, bcoef);
+ greyscale = vmlaq_n_f32(greyscale, gcolor, gcoef);
+ greyscale = vmlaq_n_f32(greyscale, bcolor, bcoef);
return greyscale;
}
@@ -101,16 +101,16 @@ inline void rgb_to_u8_conversion(const uint8x16x3_t &in, uint8x16_t &out)
//New grayscale image = ( (RED_COEFF * R) + (GREEN_COEFF * G) + (BLUE_COEFF * B) )
//Computation of 1(Greyscale) 4 uint8 using 3(RGB) 4 uint8s float
out_float32.val[0] = rgb_to_greyscale_calculation(r_float32.val[0], g_float32.val[0], b_float32.val[0],
- rgb2u8_red_coef, rgb2u8_green_coef, rgb2u8_blue_coef);
+ rgb2u8_red_coef, rgb2u8_green_coef, rgb2u8_blue_coef);
out_float32.val[1] = rgb_to_greyscale_calculation(r_float32.val[1], g_float32.val[1], b_float32.val[1],
- rgb2u8_red_coef, rgb2u8_green_coef, rgb2u8_blue_coef);
+ rgb2u8_red_coef, rgb2u8_green_coef, rgb2u8_blue_coef);
out_float32.val[2] = rgb_to_greyscale_calculation(r_float32.val[2], g_float32.val[2], b_float32.val[2],
- rgb2u8_red_coef, rgb2u8_green_coef, rgb2u8_blue_coef);
+ rgb2u8_red_coef, rgb2u8_green_coef, rgb2u8_blue_coef);
out_float32.val[3] = rgb_to_greyscale_calculation(r_float32.val[3], g_float32.val[3], b_float32.val[3],
- rgb2u8_red_coef, rgb2u8_green_coef, rgb2u8_blue_coef);
+ rgb2u8_red_coef, rgb2u8_green_coef, rgb2u8_blue_coef);
//Conversion from 1(Greyscale) 4 floats to 1(Greyscale) 4 uint8s
convert_float32x4x4_to_unit8x16(out_float32, out);
@@ -359,7 +359,7 @@ void colorconvert_rgb_to_rgbx(const void *__restrict input, void *__restrict out
Iterator in(input_ptr, win);
Iterator out(output_ptr, win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta1 = vld3q_u8(in.ptr());
uint8x16x4_t ta2;
@@ -390,7 +390,7 @@ void colorconvert_rgb_to_u8(const void *__restrict input, void *__restrict outpu
Iterator in(input_ptr, win);
Iterator out(output_ptr, win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta1 = vld3q_u8(in.ptr());
uint8x16_t ta2;
@@ -418,7 +418,7 @@ void colorconvert_rgbx_to_rgb(const void *input, void *output, const Window &win
Iterator in(input_ptr, win);
Iterator out(output_ptr, win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta1 = vld4q_u8(in.ptr());
uint8x16x3_t ta2;
@@ -452,7 +452,7 @@ void colorconvert_yuyv_to_rgb(const void *__restrict input, void *__restrict out
Iterator in(input_ptr, win);
Iterator out(output_ptr, win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta = vld4q_u8(in.ptr());
//ta.val[0] = Y0 Y2 Y4 Y6 ...
@@ -505,7 +505,7 @@ void colorconvert_nv12_to_rgb(const void *__restrict input, void *__restrict out
Iterator in_uv(input_ptr->plane(1), win_uv);
Iterator out(output_ptr, win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_y_top = vld2q_u8(in_y.ptr());
const auto ta_y_bottom = vld2q_u8(in_y.ptr() + input_ptr->plane(0)->info()->strides_in_bytes().y());
@@ -567,7 +567,7 @@ void colorconvert_iyuv_to_rgb(const void *__restrict input, void *__restrict out
Iterator in_v(input_ptr->plane(2), win_uv);
Iterator out(output_ptr, win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_y_top = vld2q_u8(in_y.ptr());
const auto ta_y_bottom = vld2q_u8(in_y.ptr() + input_ptr->plane(0)->info()->strides_in_bytes().y());
@@ -628,7 +628,7 @@ void colorconvert_yuyv_to_nv12(const void *__restrict input, void *__restrict ou
Iterator out_y(output_ptr->plane(0), win);
Iterator out_uv(output_ptr->plane(1), win_uv);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_top = vld4q_u8(in.ptr());
const auto ta_bottom = vld4q_u8(in.ptr() + input_ptr->info()->strides_in_bytes().y());
@@ -683,7 +683,7 @@ void colorconvert_iyuv_to_nv12(const void *__restrict input, void *__restrict ou
Iterator out_y(output_ptr->plane(0), win);
Iterator out_uv(output_ptr->plane(1), win_uv);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_y_top = vld2q_u8(in_y.ptr());
const auto ta_y_bottom = vld2q_u8(in_y.ptr() + input_ptr->plane(0)->info()->strides_in_bytes().y());
@@ -733,7 +733,7 @@ void colorconvert_nv12_to_iyuv(const void *__restrict input, void *__restrict ou
Iterator out_u(output_ptr->plane(1), win_uv);
Iterator out_v(output_ptr->plane(2), win_uv);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_y_top = vld2q_u8(in_y.ptr());
const auto ta_y_bottom = vld2q_u8(in_y.ptr() + input_ptr->plane(0)->info()->strides_in_bytes().y());
@@ -781,7 +781,7 @@ void colorconvert_yuyv_to_iyuv(const void *__restrict input, void *__restrict ou
Iterator out_u(output_ptr->plane(1), win_uv);
Iterator out_v(output_ptr->plane(2), win_uv);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_top = vld4q_u8(in.ptr());
const auto ta_bottom = vld4q_u8(in.ptr() + input_ptr->info()->strides_in_bytes().y());
@@ -842,7 +842,7 @@ void colorconvert_nv12_to_yuv4(const void *__restrict input, void *__restrict ou
Iterator out_u(output_ptr->plane(1), win);
Iterator out_v(output_ptr->plane(2), win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_y_top = vld2q_u8(in_y.ptr());
const auto ta_y_bottom = vld2q_u8(in_y.ptr() + input_ptr->plane(0)->info()->strides_in_bytes().y());
@@ -899,7 +899,7 @@ void colorconvert_iyuv_to_yuv4(const void *__restrict input, void *__restrict ou
Iterator out_u(output_ptr->plane(1), win);
Iterator out_v(output_ptr->plane(2), win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_y_top = vld2q_u8(in_y.ptr());
const auto ta_y_bottom = vld2q_u8(in_y.ptr() + input_ptr->plane(0)->info()->strides_in_bytes().y());
@@ -955,7 +955,7 @@ void colorconvert_rgb_to_nv12(const void *__restrict input, void *__restrict out
Iterator out_y(output_ptr->plane(0), win);
Iterator out_uv(output_ptr->plane(1), win_uv);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_rgb_top = load_rgb(in.ptr(), alpha);
const auto ta_rgb_bottom = load_rgb(in.ptr() + input_ptr->info()->strides_in_bytes().y(), alpha);
@@ -999,7 +999,7 @@ void colorconvert_rgb_to_iyuv(const void *__restrict input, void *__restrict out
Iterator out_u(output_ptr->plane(1), win_uv);
Iterator out_v(output_ptr->plane(2), win_uv);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_rgb_top = load_rgb(in.ptr(), alpha);
const auto ta_rgb_bottom = load_rgb(in.ptr() + input_ptr->info()->strides_in_bytes().y(), alpha);
@@ -1037,7 +1037,7 @@ void colorconvert_rgb_to_yuv4(const void *__restrict input, void *__restrict out
Iterator out_u(output_ptr->plane(1), win);
Iterator out_v(output_ptr->plane(2), win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto ta_rgb = load_rgb(in.ptr(), alpha);
//ta_rgb.val[0] = R0 R1 R2 R3 ...
diff --git a/arm_compute/core/NEON/kernels/NEBoundingBoxTransformKernel.h b/arm_compute/core/NEON/kernels/NEBoundingBoxTransformKernel.h
index c2b3862b1..70dd0f6a5 100644
--- a/arm_compute/core/NEON/kernels/NEBoundingBoxTransformKernel.h
+++ b/arm_compute/core/NEON/kernels/NEBoundingBoxTransformKernel.h
@@ -84,7 +84,7 @@ public:
private:
template <typename T>
- void internal_run(const Window &window, const ThreadInfo &info);
+ void internal_run(const Window &window);
const ITensor *_boxes;
ITensor *_pred_boxes;
diff --git a/arm_compute/core/NEON/kernels/NEGenerateProposalsLayerKernel.h b/arm_compute/core/NEON/kernels/NEGenerateProposalsLayerKernel.h
index 9ee9d5dd0..9b129c206 100644
--- a/arm_compute/core/NEON/kernels/NEGenerateProposalsLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEGenerateProposalsLayerKernel.h
@@ -75,7 +75,7 @@ public:
private:
template <typename T>
- void internal_run(const Window &window, const ThreadInfo &info);
+ void internal_run(const Window &window);
const ITensor *_anchors;
ITensor *_all_anchors;
diff --git a/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedMatrixMultiplyWrapper.h b/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedMatrixMultiplyWrapper.h
index 40b6f5da3..641f88ee5 100644
--- a/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedMatrixMultiplyWrapper.h
+++ b/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedMatrixMultiplyWrapper.h
@@ -165,7 +165,7 @@ public:
// Merge the result with the other blocks' results:
strat.transforms.Merge(c(0, 0, batch, wl._multi), tmp_c(0, info.thread_id), c.stride(1), y, ymax, wl._x0, wl._xmax, _alpha, (wl._k0 == 0 ? _beta : static_cast<typename strategy::result_type>(1)));
});
- auto on_new_row_size = [&](unsigned int start, unsigned int end)
+ auto on_new_row_size = [&](unsigned int, unsigned int)
{
//Nothing to do
};
diff --git a/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h b/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h
index b18d32733..c1fd86e45 100644
--- a/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h
+++ b/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h
@@ -139,7 +139,7 @@ public:
a.stride(1), first_m, last_m, wl._k0, wl._kmax, _transpose_a);
}
});
- auto on_new_row_size = [&](unsigned int start, unsigned int end)
+ auto on_new_row_size = [&](unsigned int, unsigned int end)
{
last_m = std::min(end, _Msize);
};
diff --git a/arm_compute/core/NEON/kernels/assembly/gemm_common.hpp b/arm_compute/core/NEON/kernels/assembly/gemm_common.hpp
index f59a61703..1ae503cdd 100644
--- a/arm_compute/core/NEON/kernels/assembly/gemm_common.hpp
+++ b/arm_compute/core/NEON/kernels/assembly/gemm_common.hpp
@@ -25,6 +25,8 @@
#include <cstddef>
+#define UNUSED(x) (void)(x)
+
namespace arm_gemm {
// Abstract class for the GEMM/GEMV functions.
@@ -95,7 +97,7 @@ public:
/*** "Quantized bias" interface (optional) ***/
/* Set the bias vector for quantized GEMMs */
- virtual void set_quantized_bias(const int32_t *bias) { }
+ virtual void set_quantized_bias(const int32_t *bias) { UNUSED(bias); }
// Destructor
virtual ~IGemmCommon() { }
diff --git a/arm_compute/core/NEON/wrapper/intrinsics/inv.h b/arm_compute/core/NEON/wrapper/intrinsics/inv.h
index acb2c91fe..9e2db5839 100644
--- a/arm_compute/core/NEON/wrapper/intrinsics/inv.h
+++ b/arm_compute/core/NEON/wrapper/intrinsics/inv.h
@@ -40,6 +40,7 @@ namespace wrapper
#define VINV_IMPL_INT(vtype, prefix, postfix) \
inline vtype vinv(const vtype &a) \
{ \
+ ARM_COMPUTE_UNUSED(a); \
ARM_COMPUTE_ERROR("Not supported"); \
}
diff --git a/arm_compute/core/Validate.h b/arm_compute/core/Validate.h
index 37c7b50ec..ab518ef68 100644
--- a/arm_compute/core/Validate.h
+++ b/arm_compute/core/Validate.h
@@ -638,6 +638,7 @@ void error_on_format_not_in(const char *function, const char *file, const int li
return f == object_format;
}),
function, file, line, "Format %s not supported by this kernel", string_from_format(object_format).c_str());
+ ARM_COMPUTE_UNUSED(function, format, file, line);
}
#define ARM_COMPUTE_ERROR_ON_FORMAT_NOT_IN(t, ...) ::arm_compute::error_on_format_not_in(__func__, __FILE__, __LINE__, t, __VA_ARGS__)
diff --git a/arm_compute/core/utils/logging/LogMsgDecorators.h b/arm_compute/core/utils/logging/LogMsgDecorators.h
index 03a2d41f1..7c5b58b63 100644
--- a/arm_compute/core/utils/logging/LogMsgDecorators.h
+++ b/arm_compute/core/utils/logging/LogMsgDecorators.h
@@ -24,6 +24,7 @@
#ifndef __ARM_COMPUTE_LOGGING_LOG_MSG_DECORATORS_H__
#define __ARM_COMPUTE_LOGGING_LOG_MSG_DECORATORS_H__
+#include "arm_compute/core/Error.h"
#include "arm_compute/core/utils/logging/Helpers.h"
#include "arm_compute/core/utils/logging/Types.h"
@@ -120,6 +121,8 @@ public:
{
#ifndef NO_MULTI_THREADING
log_msg.raw_ += angle_wrap_value(std::this_thread::get_id());
+#else /* NO_MULTI_THREADING */
+ ARM_COMPUTE_UNUSED(log_msg);
#endif /* NO_MULTI_THREADING */
}
};
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 65a2a1edf..c4c360842 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -859,6 +859,7 @@ inline TensorShape compute_mm_shape(const ITensorInfo &input0, const ITensorInfo
*/
inline TensorShape compute_mm_shape(const ITensorInfo &input0, const ITensorInfo &input1, const GEMMReshapeInfo &gemm_info)
{
+ ARM_COMPUTE_UNUSED(input1);
ARM_COMPUTE_ERROR_ON_MSG(input0.num_dimensions() > 4, "The number of dimensions for the matrix A must be <= 4");
const bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d();
@@ -896,6 +897,7 @@ inline TensorShape compute_mm_shape(const ITensorInfo &input0, const ITensorInfo
*/
inline TensorShape compute_mm_shape(const ITensorInfo &input0, const ITensorInfo &input1, const GEMMKernelInfo &gemm_info)
{
+ ARM_COMPUTE_UNUSED(input1);
ARM_COMPUTE_ERROR_ON_MSG(input0.num_dimensions() > 4, "The number of dimensions for the matrix A must be <= 4");
const bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d;
diff --git a/arm_compute/core/utils/misc/Utility.h b/arm_compute/core/utils/misc/Utility.h
index 2325644e7..d27a3cf75 100644
--- a/arm_compute/core/utils/misc/Utility.h
+++ b/arm_compute/core/utils/misc/Utility.h
@@ -65,7 +65,7 @@ struct generate_array<T, 0, val, vals...>
static constexpr std::array<T, sizeof...(vals)> value{ vals... };
};
-template <typename T, T val, T... vals>
+template <typename T, T val, T... vals>
constexpr std::array<T, sizeof...(vals)> generate_array<T, 0, val, vals...>::value;
/** @endcond */
@@ -83,6 +83,7 @@ T make_array(Iterator first, index_sequence<S...>)
template <std::size_t N, typename Iterator>
std::array<typename std::iterator_traits<Iterator>::value_type, N> make_array(Iterator first, Iterator last)
{
+ ARM_COMPUTE_UNUSED(last);
return detail::make_array(first, index_sequence_t<N> {});
}
diff --git a/arm_compute/graph/INodeVisitor.h b/arm_compute/graph/INodeVisitor.h
index f97906d02..c9f9d2172 100644
--- a/arm_compute/graph/INodeVisitor.h
+++ b/arm_compute/graph/INodeVisitor.h
@@ -176,103 +176,103 @@ public:
#ifndef DOXYGEN_SKIP_THIS
// Inherited methods overridden
- virtual void visit(INode &n) override
+ virtual void visit(INode &) override
{
default_visit();
}
- virtual void visit(ActivationLayerNode &n) override
+ virtual void visit(ActivationLayerNode &) override
{
default_visit();
}
- virtual void visit(BatchNormalizationLayerNode &n) override
+ virtual void visit(BatchNormalizationLayerNode &) override
{
default_visit();
}
- virtual void visit(ConcatenateLayerNode &n) override
+ virtual void visit(ConcatenateLayerNode &) override
{
default_visit();
}
- virtual void visit(ConstNode &n) override
+ virtual void visit(ConstNode &) override
{
default_visit();
}
- virtual void visit(ConvolutionLayerNode &n) override
+ virtual void visit(ConvolutionLayerNode &) override
{
default_visit();
}
- virtual void visit(DetectionOutputLayerNode &n) override
+ virtual void visit(DetectionOutputLayerNode &) override
{
default_visit();
}
- virtual void visit(DetectionPostProcessLayerNode &n) override
+ virtual void visit(DetectionPostProcessLayerNode &) override
{
default_visit();
}
- virtual void visit(DepthwiseConvolutionLayerNode &n) override
+ virtual void visit(DepthwiseConvolutionLayerNode &) override
{
default_visit();
}
- virtual void visit(EltwiseLayerNode &n) override
+ virtual void visit(EltwiseLayerNode &) override
{
default_visit();
}
- virtual void visit(FlattenLayerNode &n) override
+ virtual void visit(FlattenLayerNode &) override
{
default_visit();
}
- virtual void visit(FullyConnectedLayerNode &n) override
+ virtual void visit(FullyConnectedLayerNode &) override
{
default_visit();
}
- virtual void visit(FusedConvolutionBatchNormalizationNode &n) override
+ virtual void visit(FusedConvolutionBatchNormalizationNode &) override
{
default_visit();
}
- virtual void visit(FusedDepthwiseConvolutionBatchNormalizationNode &n) override
+ virtual void visit(FusedDepthwiseConvolutionBatchNormalizationNode &) override
{
default_visit();
}
- virtual void visit(InputNode &n) override
+ virtual void visit(InputNode &) override
{
default_visit();
}
- virtual void visit(NormalizationLayerNode &n) override
+ virtual void visit(NormalizationLayerNode &) override
{
default_visit();
}
- virtual void visit(OutputNode &n) override
+ virtual void visit(OutputNode &) override
{
default_visit();
}
- virtual void visit(PermuteLayerNode &n) override
+ virtual void visit(PermuteLayerNode &) override
{
default_visit();
}
- virtual void visit(PoolingLayerNode &n) override
+ virtual void visit(PoolingLayerNode &) override
{
default_visit();
}
- virtual void visit(PriorBoxLayerNode &n) override
+ virtual void visit(PriorBoxLayerNode &) override
{
default_visit();
}
- virtual void visit(QuantizationLayerNode &n) override
+ virtual void visit(QuantizationLayerNode &) override
{
default_visit();
}
- virtual void visit(ReshapeLayerNode &n) override
+ virtual void visit(ReshapeLayerNode &) override
{
default_visit();
}
- virtual void visit(SoftmaxLayerNode &n) override
+ virtual void visit(SoftmaxLayerNode &) override
{
default_visit();
}
- virtual void visit(SplitLayerNode &n) override
+ virtual void visit(SplitLayerNode &) override
{
default_visit();
}
- virtual void visit(StackLayerNode &n) override
+ virtual void visit(StackLayerNode &) override
{
default_visit();
}
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 10f8c0c5c..94b385e81 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -83,6 +83,7 @@ void validate_node(const INode &node, size_t num_expected_inputs, size_t num_exp
ARM_COMPUTE_ERROR_ON(TargetInfo::TargetType != node.assigned_target());
ARM_COMPUTE_ERROR_ON(node.num_inputs() != num_expected_inputs);
ARM_COMPUTE_ERROR_ON(node.num_outputs() != num_expected_outputs);
+ ARM_COMPUTE_UNUSED(node, num_expected_inputs, num_expected_outputs);
}
/** Creates a backend activation layer function
@@ -1471,6 +1472,7 @@ std::unique_ptr<arm_compute::IFunction> create_stack_layer(StackLayerNode &node)
template <typename UpsampleLayerFunction, typename TargetInfo>
std::unique_ptr<IFunction> create_upsample_layer(UpsampleLayerNode &node, GraphContext &ctx)
{
+ ARM_COMPUTE_UNUSED(ctx);
validate_node<TargetInfo>(node, 1 /* expected inputs */, 1 /* expected outputs */);
// Extract IO and info
@@ -1514,6 +1516,7 @@ std::unique_ptr<IFunction> create_upsample_layer(UpsampleLayerNode &node, GraphC
template <typename YOLOlayerFunction, typename TargetInfo>
std::unique_ptr<IFunction> create_yolo_layer(YOLOLayerNode &node, GraphContext &ctx)
{
+ ARM_COMPUTE_UNUSED(ctx);
validate_node<TargetInfo>(node, 1 /* expected inputs */, 1 /* expected outputs */);
// Extract IO and info
diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.h
index 3a13e659f..64e98e2f4 100644
--- a/arm_compute/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.h
+++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.h
@@ -94,6 +94,7 @@ private:
void configure_conv_fc(const IGCTensor *input, const IGCTensor *weights, IGCTensor *output);
MemoryGroup _memory_group;
+ IWeightsManager *_weights_manager;
GCIm2ColKernel _im2col_kernel;
GCFullyConnectedLayerReshapeWeights _reshape_weights_kernel;
GCGEMMMatrixMultiplyKernel _mm_kernel;
diff --git a/arm_compute/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.h b/arm_compute/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.h
index eeea0babf..695dcd5b6 100644
--- a/arm_compute/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.h
+++ b/arm_compute/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.h
@@ -120,6 +120,7 @@ public:
private:
MemoryGroup _memory_group;
+ IWeightsManager *_weights_manager;
bool _is_prepared{ false };
bool _pretranspose_b{ false };
Window _block_walker{};
diff --git a/examples/graph_deepspeech_v0_4_1.cpp b/examples/graph_deepspeech_v0_4_1.cpp
index 84650a662..d2a4832bd 100644
--- a/examples/graph_deepspeech_v0_4_1.cpp
+++ b/examples/graph_deepspeech_v0_4_1.cpp
@@ -155,22 +155,22 @@ public:
.set_name("MatMul_3_bias");
// LSTM Block
- std::pair<SubStream, SubStream> new_state_1 = add_lstm_cell(data_path, unstack_nid, 0, previous_state, previous_state, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_2 = add_lstm_cell(data_path, unstack_nid, 1, new_state_1.first, new_state_1.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_3 = add_lstm_cell(data_path, unstack_nid, 2, new_state_2.first, new_state_2.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_4 = add_lstm_cell(data_path, unstack_nid, 3, new_state_3.first, new_state_3.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_5 = add_lstm_cell(data_path, unstack_nid, 4, new_state_4.first, new_state_4.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_6 = add_lstm_cell(data_path, unstack_nid, 5, new_state_5.first, new_state_5.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_7 = add_lstm_cell(data_path, unstack_nid, 6, new_state_6.first, new_state_6.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_8 = add_lstm_cell(data_path, unstack_nid, 7, new_state_7.first, new_state_7.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_9 = add_lstm_cell(data_path, unstack_nid, 8, new_state_8.first, new_state_8.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_10 = add_lstm_cell(data_path, unstack_nid, 9, new_state_9.first, new_state_9.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_11 = add_lstm_cell(data_path, unstack_nid, 10, new_state_10.first, new_state_10.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_12 = add_lstm_cell(data_path, unstack_nid, 11, new_state_11.first, new_state_11.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_13 = add_lstm_cell(data_path, unstack_nid, 12, new_state_12.first, new_state_12.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_14 = add_lstm_cell(data_path, unstack_nid, 13, new_state_13.first, new_state_13.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_15 = add_lstm_cell(data_path, unstack_nid, 14, new_state_14.first, new_state_14.second, add_y, lstm_fc_weights, lstm_fc_bias);
- std::pair<SubStream, SubStream> new_state_16 = add_lstm_cell(data_path, unstack_nid, 15, new_state_15.first, new_state_15.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_1 = add_lstm_cell(unstack_nid, 0, previous_state, previous_state, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_2 = add_lstm_cell(unstack_nid, 1, new_state_1.first, new_state_1.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_3 = add_lstm_cell(unstack_nid, 2, new_state_2.first, new_state_2.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_4 = add_lstm_cell(unstack_nid, 3, new_state_3.first, new_state_3.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_5 = add_lstm_cell(unstack_nid, 4, new_state_4.first, new_state_4.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_6 = add_lstm_cell(unstack_nid, 5, new_state_5.first, new_state_5.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_7 = add_lstm_cell(unstack_nid, 6, new_state_6.first, new_state_6.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_8 = add_lstm_cell(unstack_nid, 7, new_state_7.first, new_state_7.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_9 = add_lstm_cell(unstack_nid, 8, new_state_8.first, new_state_8.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_10 = add_lstm_cell(unstack_nid, 9, new_state_9.first, new_state_9.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_11 = add_lstm_cell(unstack_nid, 10, new_state_10.first, new_state_10.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_12 = add_lstm_cell(unstack_nid, 11, new_state_11.first, new_state_11.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_13 = add_lstm_cell(unstack_nid, 12, new_state_12.first, new_state_12.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_14 = add_lstm_cell(unstack_nid, 13, new_state_13.first, new_state_13.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_15 = add_lstm_cell(unstack_nid, 14, new_state_14.first, new_state_14.second, add_y, lstm_fc_weights, lstm_fc_bias);
+ std::pair<SubStream, SubStream> new_state_16 = add_lstm_cell(unstack_nid, 15, new_state_15.first, new_state_15.second, add_y, lstm_fc_weights, lstm_fc_bias);
// Concatenate new states on height
const int axis = 1;
@@ -241,8 +241,7 @@ private:
return Status{};
}
- std::pair<SubStream, SubStream> add_lstm_cell(const std::string &data_path,
- NodeID unstack_nid,
+ std::pair<SubStream, SubStream> add_lstm_cell(NodeID unstack_nid,
unsigned int unstack_idx,
SubStream previous_state_c,
SubStream previous_state_h,
diff --git a/src/core/CL/OpenCL.cpp b/src/core/CL/OpenCL.cpp
index ef03a5a30..1ce1b526d 100644
--- a/src/core/CL/OpenCL.cpp
+++ b/src/core/CL/OpenCL.cpp
@@ -22,7 +22,10 @@
* SOFTWARE.
*/
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wunused-parameter"
#include "arm_compute/core/CL/OpenCL.h"
+#pragma GCC diagnostic pop
#include <dlfcn.h>
#include <iostream>
diff --git a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp
index 4ae9cabd1..819e3c910 100644
--- a/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp
+++ b/src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.cpp
@@ -42,6 +42,7 @@ CLDeconvolutionLayerUpsampleKernel::CLDeconvolutionLayerUpsampleKernel()
Status CLDeconvolutionLayerUpsampleKernel::validate(const ITensorInfo *input, const ITensorInfo *output,
const PadStrideInfo &info)
{
+ ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
index b34c261a4..8b624bb2c 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
@@ -23,7 +23,6 @@
*/
#include "arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.h"
-#include "arm_compute/core/IAccessWindow.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/CLValidate.h"
@@ -31,6 +30,7 @@
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/IAccessWindow.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Utils.h"
@@ -43,6 +43,7 @@ namespace
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info,
const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
{
+ ARM_COMPUTE_UNUSED(dwc_info);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
@@ -74,6 +75,8 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights,
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info,
const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
{
+ ARM_COMPUTE_UNUSED(dwc_info);
+
// Get convolved dimensions
const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation);
diff --git a/src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp b/src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp
index 5a40b9960..e195c9672 100644
--- a/src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp
+++ b/src/core/NEON/kernels/NEBoundingBoxTransformKernel.cpp
@@ -79,6 +79,7 @@ Status validate_arguments(const ITensorInfo *boxes, const ITensorInfo *pred_boxe
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *boxes, ITensorInfo *pred_boxes, ITensorInfo *deltas, const BoundingBoxTransformInfo &bb_info)
{
+ ARM_COMPUTE_UNUSED(bb_info);
ARM_COMPUTE_ERROR_ON_NULLPTR(boxes, pred_boxes);
auto_init_if_empty(*pred_boxes, deltas->clone()->set_data_type(boxes->data_type()).set_quantization_info(boxes->quantization_info()));
@@ -130,7 +131,7 @@ Status NEBoundingBoxTransformKernel::validate(const ITensorInfo *boxes, const IT
}
template <>
-void NEBoundingBoxTransformKernel::internal_run<uint16_t>(const Window &window, const ThreadInfo &info)
+void NEBoundingBoxTransformKernel::internal_run<uint16_t>(const Window &window)
{
const size_t num_classes = _deltas->info()->tensor_shape()[0] >> 2;
const size_t deltas_width = _deltas->info()->tensor_shape()[0];
@@ -187,7 +188,7 @@ void NEBoundingBoxTransformKernel::internal_run<uint16_t>(const Window &window,
}
template <typename T>
-void NEBoundingBoxTransformKernel::internal_run(const Window &window, const ThreadInfo &info)
+void NEBoundingBoxTransformKernel::internal_run(const Window &window)
{
const size_t num_classes = _deltas->info()->tensor_shape()[0] >> 2;
const size_t deltas_width = _deltas->info()->tensor_shape()[0];
@@ -242,24 +243,25 @@ void NEBoundingBoxTransformKernel::internal_run(const Window &window, const Thre
void NEBoundingBoxTransformKernel::run(const Window &window, const ThreadInfo &info)
{
+ ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
switch(_boxes->info()->data_type())
{
case DataType::F32:
{
- internal_run<float>(window, info);
+ internal_run<float>(window);
break;
}
case DataType::QASYMM16:
{
- internal_run<uint16_t>(window, info);
+ internal_run<uint16_t>(window);
break;
}
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
{
- internal_run<float16_t>(window, info);
+ internal_run<float16_t>(window);
break;
}
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
diff --git a/src/core/NEON/kernels/NEDepthConvertLayerKernel.cpp b/src/core/NEON/kernels/NEDepthConvertLayerKernel.cpp
index 10bbe8324..d00c5009d 100644
--- a/src/core/NEON/kernels/NEDepthConvertLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEDepthConvertLayerKernel.cpp
@@ -49,7 +49,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, C
ARM_COMPUTE_RETURN_ERROR_ON(shift >= 8);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::QASYMM8 && (output->data_type() != DataType::S16 && output->data_type() != DataType::U16
- && output->data_type() != DataType::S32 && output->data_type() != DataType::F16 && output->data_type() != DataType::F32),
+ && output->data_type() != DataType::S32 && output->data_type() != DataType::F16 && output->data_type() != DataType::F32),
"Only data_types supported [in] QASYMM8 -> [out] U16, S16, S32, F16, F32");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::U8 && (output->data_type() != DataType::S16 && output->data_type() != DataType::U16
@@ -62,13 +62,16 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, C
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::S16 && (output->data_type() != DataType::U8 && output->data_type() != DataType::S32),
"Only data_types supported [in] S16 -> [out] U8, S32");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::F16 && (output->data_type() != DataType::QASYMM8 && output->data_type() != DataType::U8 && output->data_type() != DataType::F32 && output->data_type() != DataType::S32),
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::F16 && (output->data_type() != DataType::QASYMM8 && output->data_type() != DataType::U8 && output->data_type() != DataType::F32
+ && output->data_type() != DataType::S32),
"Only data_types supported [in] F16 -> [out] QASYMM8, F32, S32, U8");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::F32 && (output->data_type() != DataType::QASYMM8 && output->data_type() != DataType::F16 && output->data_type() != DataType::S32 && output->data_type() != DataType::U8),
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::F32 && (output->data_type() != DataType::QASYMM8 && output->data_type() != DataType::F16 && output->data_type() != DataType::S32
+ && output->data_type() != DataType::U8),
"Only data_types supported [in] F32 -> [out] QASYMM8, F16, S32, U8");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::S32 && (output->data_type() != DataType::QASYMM8 && output->data_type() != DataType::F16 && output->data_type() != DataType::F32 && output->data_type() != DataType::U8),
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() == DataType::S32 && (output->data_type() != DataType::QASYMM8 && output->data_type() != DataType::F16 && output->data_type() != DataType::F32
+ && output->data_type() != DataType::U8),
"Only data_types supported [in] S32 -> [out] QASYMM8, F16, F32, U8");
// Validate in case of configured output
@@ -427,7 +430,7 @@ void NEDepthConvertLayerKernel::run(const Window &window, const ThreadInfo &info
const float16x8_t scale = vdupq_n_f16(1 << _shift);
/* Up-conversion F16 -> U8 */
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
const float16x8x2_t texels =
{
@@ -447,7 +450,7 @@ void NEDepthConvertLayerKernel::run(const Window &window, const ThreadInfo &info
const float32x4_t scale = vdupq_n_f32(1 << _shift);
/* Up-conversion F16 -> F32 */
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
const float16x8x2_t texels =
{
@@ -470,7 +473,7 @@ void NEDepthConvertLayerKernel::run(const Window &window, const ThreadInfo &info
const float32x4_t scale = vdupq_n_f32(1 << _shift);
/* Up-conversion F16 -> S32 */
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
const float16x8x2_t texels =
{
@@ -565,13 +568,12 @@ void NEDepthConvertLayerKernel::run(const Window &window, const ThreadInfo &info
};
vst1_u8(reinterpret_cast<uint8_t *>(output.ptr()), vqmovn_u16(vcombine_u16(vqmovun_s32(vcvtq_s32_f32(texels.val[0])), vqmovun_s32(vcvtq_s32_f32(texels.val[1])))));
- vst1_u8(reinterpret_cast<uint8_t *>(output.ptr())+8, vqmovn_u16(vcombine_u16(vqmovun_s32(vcvtq_s32_f32(texels.val[2])), vqmovun_s32(vcvtq_s32_f32(texels.val[3])))));
+ vst1_u8(reinterpret_cast<uint8_t *>(output.ptr()) + 8, vqmovn_u16(vcombine_u16(vqmovun_s32(vcvtq_s32_f32(texels.val[2])), vqmovun_s32(vcvtq_s32_f32(texels.val[3])))));
},
input, output);
break;
}
-
default:
ARM_COMPUTE_ERROR("Output data type not supported");
}
@@ -650,7 +652,7 @@ void NEDepthConvertLayerKernel::run(const Window &window, const ThreadInfo &info
}
};
vst1_u8(reinterpret_cast<uint8_t *>(output.ptr()), vqmovn_u16(vcombine_u16(vqmovun_s32(texels.val[0]), vqmovun_s32(texels.val[1]))));
- vst1_u8(reinterpret_cast<uint8_t *>(output.ptr())+8, vqmovn_u16(vcombine_u16(vqmovun_s32(texels.val[2]), vqmovun_s32(texels.val[3]))));
+ vst1_u8(reinterpret_cast<uint8_t *>(output.ptr()) + 8, vqmovn_u16(vcombine_u16(vqmovun_s32(texels.val[2]), vqmovun_s32(texels.val[3]))));
},
input, output);
}
@@ -668,8 +670,8 @@ void NEDepthConvertLayerKernel::run(const Window &window, const ThreadInfo &info
}
};
- vst1_u8(reinterpret_cast<uint8_t *>(output.ptr()), vmovn_u16(vcombine_u16(vmovn_u32(vreinterpretq_u32_s32(texels.val[0])),vmovn_u32(vreinterpretq_u32_s32(texels.val[1])))));
- vst1_u8(reinterpret_cast<uint8_t *>(output.ptr())+8, vmovn_u16(vcombine_u16(vmovn_u32(vreinterpretq_u32_s32(texels.val[2])),vmovn_u32(vreinterpretq_u32_s32(texels.val[3])))));
+ vst1_u8(reinterpret_cast<uint8_t *>(output.ptr()), vmovn_u16(vcombine_u16(vmovn_u32(vreinterpretq_u32_s32(texels.val[0])), vmovn_u32(vreinterpretq_u32_s32(texels.val[1])))));
+ vst1_u8(reinterpret_cast<uint8_t *>(output.ptr()) + 8, vmovn_u16(vcombine_u16(vmovn_u32(vreinterpretq_u32_s32(texels.val[2])), vmovn_u32(vreinterpretq_u32_s32(texels.val[3])))));
},
input, output);
}
diff --git a/src/core/NEON/kernels/NEDequantizationLayerKernel.cpp b/src/core/NEON/kernels/NEDequantizationLayerKernel.cpp
index 49de3ec8b..5abd6a122 100644
--- a/src/core/NEON/kernels/NEDequantizationLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEDequantizationLayerKernel.cpp
@@ -219,7 +219,7 @@ void run_dequantization_qasymm8_per_channel_nhwc(const ITensor *input, ITensor *
Iterator in(input, win);
Iterator out(output, win);
- execute_window_loop(win, [&](const Coordinates & id)
+ execute_window_loop(win, [&](const Coordinates &)
{
const auto in_ptr = reinterpret_cast<const uint8_t *>(in.ptr());
const auto out_ptr = reinterpret_cast<T *>(out.ptr());
diff --git a/src/core/NEON/kernels/NEGenerateProposalsLayerKernel.cpp b/src/core/NEON/kernels/NEGenerateProposalsLayerKernel.cpp
index ba5ca7895..940ccabe6 100644
--- a/src/core/NEON/kernels/NEGenerateProposalsLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEGenerateProposalsLayerKernel.cpp
@@ -100,7 +100,7 @@ Status NEComputeAllAnchorsKernel::validate(const ITensorInfo *anchors, const ITe
}
template <>
-void NEComputeAllAnchorsKernel::internal_run<int16_t>(const Window &window, const ThreadInfo &info)
+void NEComputeAllAnchorsKernel::internal_run<int16_t>(const Window &window)
{
Iterator all_anchors_it(_all_anchors, window);
Iterator anchors_it(_all_anchors, window);
@@ -136,7 +136,7 @@ void NEComputeAllAnchorsKernel::internal_run<int16_t>(const Window &window, cons
}
template <typename T>
-void NEComputeAllAnchorsKernel::internal_run(const Window &window, const ThreadInfo &info)
+void NEComputeAllAnchorsKernel::internal_run(const Window &window)
{
Iterator all_anchors_it(_all_anchors, window);
Iterator anchors_it(_all_anchors, window);
@@ -174,19 +174,19 @@ void NEComputeAllAnchorsKernel::run(const Window &window, const ThreadInfo &info
{
case DataType::QSYMM16:
{
- internal_run<int16_t>(window, info);
+ internal_run<int16_t>(window);
break;
}
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F16:
{
- internal_run<float16_t>(window, info);
+ internal_run<float16_t>(window);
break;
}
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
case DataType::F32:
{
- internal_run<float>(window, info);
+ internal_run<float>(window);
break;
}
default:
diff --git a/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp b/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp
index 1dab5d955..4bd03e959 100644
--- a/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp
+++ b/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp
@@ -191,7 +191,7 @@ inline uint16x8_t scale255_U16_U16(uint16x8_t in)
return vreinterpretq_u16_s16(vcombine_s16(vmovn_s32(tmp_s2), vmovn_s32(tmp_s1)));
}
-inline void mul_saturate_QASYMM8_QASYMM8_QASYMM8_n_opt(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, float scale,
+inline void mul_saturate_QASYMM8_QASYMM8_QASYMM8_n_opt(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr,
float32x4_t input1_vscale, int32x4_t input1_voffset, float32x4_t input2_vscale, int32x4_t input2_voffset, float32x4_t output_voffset, float32x4_t vinvscale)
{
const auto input1 = static_cast<const qasymm8_t *__restrict>(input1_ptr);
@@ -739,7 +739,7 @@ void NEPixelWiseMultiplicationKernel::run(const Window &window, const ThreadInfo
execute_window_loop(collapsed, [&](const Coordinates &)
{
- mul_saturate_QASYMM8_QASYMM8_QASYMM8_n_opt(input1.ptr(), input2.ptr(), output.ptr(), _scale,
+ mul_saturate_QASYMM8_QASYMM8_QASYMM8_n_opt(input1.ptr(), input2.ptr(), output.ptr(),
input1_vscale, input1_voffset, input2_vscale, input2_voffset, output_voffset, vinvscale);
ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1));
ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2));
diff --git a/src/core/NEON/kernels/arm_gemm/buffer_manager.hpp b/src/core/NEON/kernels/arm_gemm/buffer_manager.hpp
index 03f099d57..001cab7f0 100644
--- a/src/core/NEON/kernels/arm_gemm/buffer_manager.hpp
+++ b/src/core/NEON/kernels/arm_gemm/buffer_manager.hpp
@@ -303,22 +303,32 @@ public:
BufferManager(BufferManager &) = delete;
BufferManager & operator=(BufferManager &) = delete;
- BufferManager(const int maxthreads, const size_t buffersize, void *storage) : _storage(storage) { }
+ BufferManager(const int maxthreads, const size_t buffersize, void *storage) : _storage(storage) {
+ UNUSED(maxthreads);
+ UNUSED(buffersize);
+ }
~BufferManager() { }
// Say how much storage is needed.
static inline size_t get_storage_requirement(const int maxthreads, const size_t buffersize) {
+ UNUSED(maxthreads);
return buffersize;
}
template <typename T>
- void try_populate(const int index, T func) { }
+ void try_populate(const int index, T func) {
+ UNUSED(index);
+ UNUSED(func);
+ }
- void release(const int index) { }
+ void release(const int index) {
+ UNUSED(index);
+ }
template <typename T>
void *get(const int index, T func) {
+ UNUSED(index);
func(_storage);
return _storage;
}
diff --git a/src/core/NEON/kernels/arm_gemm/gemm_hybrid.hpp b/src/core/NEON/kernels/arm_gemm/gemm_hybrid.hpp
index a74437639..436f55dee 100644
--- a/src/core/NEON/kernels/arm_gemm/gemm_hybrid.hpp
+++ b/src/core/NEON/kernels/arm_gemm/gemm_hybrid.hpp
@@ -146,6 +146,7 @@ public:
// Execute
void execute(unsigned int start, unsigned int end, int threadid) override {
+ UNUSED(threadid);
#ifdef CYCLE_PROFILING
profiler prof;
#endif
diff --git a/src/core/NEON/kernels/arm_gemm/gemv_batched.hpp b/src/core/NEON/kernels/arm_gemm/gemv_batched.hpp
index 8dae7c309..4453ee824 100644
--- a/src/core/NEON/kernels/arm_gemm/gemv_batched.hpp
+++ b/src/core/NEON/kernels/arm_gemm/gemv_batched.hpp
@@ -48,6 +48,8 @@ public:
void set_arrays(const To *A, const int lda, const int A_batch_stride, const int A_multi_stride,
const To *B, const int ldb, const int B_multi_stride,
Tr *C, const int ldc, const int C_batch_stride, const int C_multi_stride) override {
+ UNUSED(lda);
+ UNUSED(ldc);
/* A and C's batch stride becomes their new row stride. New batch stride is 0 as nbatches for subgemm is always 1. */
_subgemm->set_arrays(A, A_batch_stride, 0, A_multi_stride,
B, ldb, B_multi_stride,
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s16_12x8.hpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s16_12x8.hpp
index 2fcb587df..a19e07d30 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s16_12x8.hpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s16_12x8.hpp
@@ -65,7 +65,7 @@ public:
kern_type kernel = a64_gemm_s16_asimd_12x8;
- gemm_s16_12x8(const CPUInfo *ci) { }
+ gemm_s16_12x8(const CPUInfo *ci) { UNUSED(ci); }
};
} // namespace arm_gemm
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s8_4x4.hpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s8_4x4.hpp
index 71c666ad0..7856eb55e 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s8_4x4.hpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_s8_4x4.hpp
@@ -59,7 +59,7 @@ public:
kern_type kernel=a64_gemm_s8_4x4;
- gemm_s8_4x4(const CPUInfo *ci) { }
+ gemm_s8_4x4(const CPUInfo *ci) { UNUSED(ci); }
};
} // namespace arm_gemm
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u16_12x8.hpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u16_12x8.hpp
index 3d5c92c62..a8255629f 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u16_12x8.hpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u16_12x8.hpp
@@ -65,7 +65,7 @@ public:
kern_type kernel = a64_gemm_u16_asimd_12x8;
- gemm_u16_12x8(const CPUInfo *ci) { }
+ gemm_u16_12x8(const CPUInfo *ci) { UNUSED(ci); }
};
} // namespace arm_gemm
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u8_4x4.hpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u8_4x4.hpp
index fda7657b2..56044e928 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u8_4x4.hpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_gemm_u8_4x4.hpp
@@ -68,6 +68,7 @@ public:
kern_type kernel = a64_gemm_u8_4x4;
gemm_u8_4x4(const CPUInfo *ci) {
+ UNUSED(ci);
}
};
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_nativeA_pretransposeB_16x4.hpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_nativeA_pretransposeB_16x4.hpp
index 95e3712e8..9b7082712 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_nativeA_pretransposeB_16x4.hpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_nativeA_pretransposeB_16x4.hpp
@@ -69,7 +69,7 @@ public:
kern_type kernel=a64_sgemm_nativeA_pretransposeB_16x4;
sgemm_nativeA_pretransposeB_16x4(const CPUInfo *ci) {
-
+ UNUSED(ci);
}
};
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_native_16x4.hpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_native_16x4.hpp
index 3d2b32431..a5511931d 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_native_16x4.hpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemm_native_16x4.hpp
@@ -62,7 +62,7 @@ public:
kern_type kernel=a64_sgemm_native_16x4;
sgemm_native_16x4(const CPUInfo *ci) {
-
+ UNUSED(ci);
}
};
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_pretransposed.hpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_pretransposed.hpp
index f5b4f4aa1..c5b410f0b 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_pretransposed.hpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_pretransposed.hpp
@@ -69,7 +69,7 @@ public:
kern_type kernel = a64_sgemv_pretransposed;
- sgemv_pretransposed(const CPUInfo *ci) { }
+ sgemv_pretransposed(const CPUInfo *ci) { UNUSED(ci); }
};
} // namespace arm_gemm
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_trans.hpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_trans.hpp
index cbaa0cfb1..c904dc8e7 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_trans.hpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_sgemv_trans.hpp
@@ -49,7 +49,7 @@ public:
kern_type kernel=a64_sgemv_trans;
- sgemv_trans(const CPUInfo *ci) { }
+ sgemv_trans(const CPUInfo *ci) { UNUSED(ci); }
};
} // namespace arm_gemm
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/a55.cpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/a55.cpp
index c957d1160..e8ac2d748 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/a55.cpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/a55.cpp
@@ -32,6 +32,7 @@
namespace arm_gemm {
void a64_smallK_hybrid_s8s32_dot_4x6_a55(const int8_t *A, int lda, const int8_t *B, int32_t *C, int ldc, int32_t beta, int M, int N, int K) {
+ UNUSED(beta);
const long loops_count = (N / 4) - 1;
const long ldab = lda * sizeof(int8_t);
const long ldcb = ldc * sizeof(int32_t);
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/generic.cpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/generic.cpp
index 05d8bd5ad..64ab6f0fd 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/generic.cpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x6/generic.cpp
@@ -32,6 +32,7 @@
namespace arm_gemm {
void a64_smallK_hybrid_s8s32_dot_4x6(const int8_t *A, int lda, const int8_t *B, int32_t *C, int ldc, int32_t beta, int M, int N, int K) {
+ UNUSED(beta);
const long loops_count = (N / 4) - 1;
const long ldab = lda * sizeof(int8_t);
const long ldcb = ldc * sizeof(int32_t);
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/a55.cpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/a55.cpp
index f050fff84..4ed2bc823 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/a55.cpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/a55.cpp
@@ -32,6 +32,7 @@
namespace arm_gemm {
void a64_smallK_hybrid_s8s32_dot_4x8_a55(const int8_t *A, int lda, const int8_t *B, int32_t *C, int ldc, int32_t beta, int M, int N, int K) {
+ UNUSED(beta);
const long loops_count = (N / 4) - 1;
const long ldab = lda * sizeof(int8_t);
const long ldcb = ldc * sizeof(int32_t);
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/generic.cpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/generic.cpp
index 1881cf57a..1eb58e1cd 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/generic.cpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_s8s32_dot_4x8/generic.cpp
@@ -32,6 +32,7 @@
namespace arm_gemm {
void a64_smallK_hybrid_s8s32_dot_4x8(const int8_t *A, int lda, const int8_t *B, int32_t *C, int ldc, int32_t beta, int M, int N, int K) {
+ UNUSED(beta);
const long loops_count = (N / 4) - 1;
const long ldab = lda * sizeof(int8_t);
const long ldcb = ldc * sizeof(int32_t);
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/a55.cpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/a55.cpp
index 88ea940fb..8bf5debc3 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/a55.cpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/a55.cpp
@@ -32,6 +32,7 @@
namespace arm_gemm {
void a64_smallK_hybrid_u8u32_dot_4x6_a55(const uint8_t *A, int lda, const uint8_t *B, uint32_t *C, int ldc, uint32_t beta, int M, int N, int K) {
+ UNUSED(beta);
const long loops_count = iceildiv(N, (int)4) - 1;
const long ldab = lda * sizeof(uint8_t);
const long ldcb = ldc * sizeof(uint32_t);
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/generic.cpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/generic.cpp
index ec3ba4ad2..1f279afd4 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/generic.cpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x6/generic.cpp
@@ -32,6 +32,7 @@
namespace arm_gemm {
void a64_smallK_hybrid_u8u32_dot_4x6(const uint8_t *A, int lda, const uint8_t *B, uint32_t *C, int ldc, uint32_t beta, int M, int N, int K) {
+ UNUSED(beta);
const long loops_count = iceildiv(N, (int)4) - 1;
const long ldab = lda * sizeof(uint8_t);
const long ldcb = ldc * sizeof(uint32_t);
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/a55.cpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/a55.cpp
index fdd928d56..ec29698f4 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/a55.cpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/a55.cpp
@@ -32,6 +32,7 @@
namespace arm_gemm {
void a64_smallK_hybrid_u8u32_dot_4x8_a55(const uint8_t *A, int lda, const uint8_t *B, uint32_t *C, int ldc, uint32_t beta, int M, int N, int K) {
+ UNUSED(beta);
const long loops_count = iceildiv(N, (int)4) - 1;
const long ldab = lda * sizeof(uint8_t);
const long ldcb = ldc * sizeof(uint32_t);
diff --git a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/generic.cpp b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/generic.cpp
index 7cc8c285c..46ca01327 100644
--- a/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/generic.cpp
+++ b/src/core/NEON/kernels/arm_gemm/kernels/a64_smallK_hybrid_u8u32_dot_4x8/generic.cpp
@@ -32,6 +32,7 @@
namespace arm_gemm {
void a64_smallK_hybrid_u8u32_dot_4x8(const uint8_t *A, int lda, const uint8_t *B, uint32_t *C, int ldc, uint32_t beta, int M, int N, int K) {
+ UNUSED(beta);
const long loops_count = iceildiv(N, (int)4) - 1;
const long ldab = lda * sizeof(uint8_t);
const long ldcb = ldc * sizeof(uint32_t);
diff --git a/src/core/NEON/kernels/arm_gemm/merges/a64_merge_int32_12x8.hpp b/src/core/NEON/kernels/arm_gemm/merges/a64_merge_int32_12x8.hpp
index ce7310d13..410a0a1dc 100644
--- a/src/core/NEON/kernels/arm_gemm/merges/a64_merge_int32_12x8.hpp
+++ b/src/core/NEON/kernels/arm_gemm/merges/a64_merge_int32_12x8.hpp
@@ -27,6 +27,7 @@
template<>
inline void MergeResults<12, 8, false>(int32_t *out, const int32_t *in, const int ldout, const int y0, const int ymax, const int x0, const int xmax, const int32_t alpha, const int32_t beta) {
+ UNUSED(alpha);
const int32_t *inptr = in;
prefetch_6x(inptr);
prefetch_6x(inptr + 96);
diff --git a/src/core/NEON/kernels/arm_gemm/utils.hpp b/src/core/NEON/kernels/arm_gemm/utils.hpp
index 4271997cd..7dbbe91ba 100644
--- a/src/core/NEON/kernels/arm_gemm/utils.hpp
+++ b/src/core/NEON/kernels/arm_gemm/utils.hpp
@@ -32,6 +32,8 @@
// Paranoid option for the above with assert
// #define UNREACHABLE(why) assert(0 && why)
+#define UNUSED(x) (void)(x)
+
template<typename T>
inline T iceildiv(const T a, const T b) {
return (a + b - 1) / b;
diff --git a/src/runtime/CL/CLHelpers.cpp b/src/runtime/CL/CLHelpers.cpp
index 8bc7b8eb7..edfc8ed2a 100644
--- a/src/runtime/CL/CLHelpers.cpp
+++ b/src/runtime/CL/CLHelpers.cpp
@@ -32,6 +32,7 @@ namespace
#if defined(ARM_COMPUTE_ASSERTS_ENABLED)
void printf_callback(const char *buffer, unsigned int len, size_t complete, void *user_data)
{
+ ARM_COMPUTE_UNUSED(complete, user_data);
printf("%.*s", len, buffer);
}
#endif /* defined(ARM_COMPUTE_ASSERTS_ENABLED) */
diff --git a/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp b/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp
index 782771bc5..d4be939c5 100644
--- a/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp
+++ b/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp
@@ -196,6 +196,7 @@ void CPPBoxWithNonMaximaSuppressionLimit::configure(const ITensor *scores_in, co
Status validate(const ITensorInfo *scores_in, const ITensorInfo *boxes_in, const ITensorInfo *batch_splits_in, const ITensorInfo *scores_out, const ITensorInfo *boxes_out, const ITensorInfo *classes,
const ITensorInfo *batch_splits_out, const ITensorInfo *keeps, const ITensorInfo *keeps_size, const BoxNMSLimitInfo info)
{
+ ARM_COMPUTE_UNUSED(batch_splits_in, batch_splits_out, keeps, keeps_size, info);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(scores_in, boxes_in, scores_out, boxes_out, classes);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(scores_in, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
diff --git a/src/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.cpp
index 4ccda8827..8f26c620b 100644
--- a/src/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.cpp
+++ b/src/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.cpp
@@ -39,8 +39,8 @@ void GCFullyConnectedLayerReshapeWeights::configure(const IGCTensor *input, IGCT
}
GCFullyConnectedLayer::GCFullyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager)
- : _memory_group(std::move(memory_manager)), _im2col_kernel(), _reshape_weights_kernel(), _mm_kernel(), _accumulate_biases_kernel(), _im2col_output(), _reshape_weights_output(),
- _original_weights(nullptr), _are_weights_reshaped(true), _is_fc_after_conv(true), _accumulate_biases(false)
+ : _memory_group(std::move(memory_manager)), _weights_manager(std::move(weights_manager)), _im2col_kernel(), _reshape_weights_kernel(), _mm_kernel(), _accumulate_biases_kernel(), _im2col_output(),
+ _reshape_weights_output(), _original_weights(nullptr), _are_weights_reshaped(true), _is_fc_after_conv(true), _accumulate_biases(false)
{
}
diff --git a/src/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.cpp b/src/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.cpp
index 79e40a718..1aeab5b9c 100644
--- a/src/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.cpp
+++ b/src/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.cpp
@@ -171,17 +171,21 @@ public:
}
void mark_as_reshaped(unsigned int index) override
{
+ ARM_COMPUTE_UNUSED(index);
}
void wait_for_reshaping(unsigned int index) override
{
+ ARM_COMPUTE_UNUSED(index);
}
void mark_as_unused(unsigned int index) override
{
+ ARM_COMPUTE_UNUSED(index);
}
};
NEGEMMInterleavedWrapper::NEGEMMInterleavedWrapper(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager)
- : _memory_group(std::move(memory_manager))
+ : _memory_group(std::move(memory_manager)),
+ _weights_manager(weights_manager)
{
}
@@ -195,6 +199,7 @@ void NEGEMMInterleavedWrapper::run()
void NEGEMMInterleavedWrapper::prepare()
{
+ ARM_COMPUTE_UNUSED(_weights_manager);
if(!_is_prepared)
{
if(_pretranspose_b)
diff --git a/support/ToolchainSupport.h b/support/ToolchainSupport.h
index 03bbff9ab..b4ed2fa9a 100644
--- a/support/ToolchainSupport.h
+++ b/support/ToolchainSupport.h
@@ -71,6 +71,17 @@ inline int stoi(const std::string &str, std::size_t *pos = 0, NumericBase base =
}
ss << str;
ss >> x;
+
+ if(pos)
+ {
+ std::string s;
+ std::stringstream ss_p;
+
+ ss_p << x;
+ ss_p >> s;
+ *pos = s.length();
+ }
+
return x;
}
@@ -96,6 +107,17 @@ inline unsigned long stoul(const std::string &str, std::size_t *pos = 0, Numeric
}
stream << str;
stream >> value;
+
+ if(pos)
+ {
+ std::string s;
+ std::stringstream ss_p;
+
+ ss_p << value;
+ ss_p >> s;
+ *pos = s.length();
+ }
+
return value;
}
diff --git a/tests/AssetsLibrary.h b/tests/AssetsLibrary.h
index 2ac13468d..a512dab36 100644
--- a/tests/AssetsLibrary.h
+++ b/tests/AssetsLibrary.h
@@ -32,7 +32,10 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Window.h"
#include "arm_compute/core/utils/misc/Random.h"
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wunused-parameter"
#include "libnpy/npy.hpp"
+#pragma GCC diagnostic pop
#include "tests/RawTensor.h"
#include "tests/TensorCache.h"
#include "tests/Utils.h"
@@ -467,7 +470,7 @@ void AssetsLibrary::fill_borders_with_garbage(T &&tensor, D &&distribution, std:
window.set(1, Window::Dimension(-padding_size.top, tensor.shape()[1] + padding_size.bottom, 1));
}
- std::mt19937 gen(_seed);
+ std::mt19937 gen(_seed + seed_offset);
execute_window_loop(window, [&](const Coordinates & id)
{
diff --git a/tests/SConscript b/tests/SConscript
index 3e462910a..a062cacaa 100644
--- a/tests/SConscript
+++ b/tests/SConscript
@@ -1,4 +1,4 @@
-# Copyright (c) 2017, 2018 ARM Limited.
+# Copyright (c) 2017-2019 ARM Limited.
#
# SPDX-License-Identifier: MIT
#
@@ -58,12 +58,6 @@ Help(new_options.GenerateHelpText(test_env))
Import("arm_compute_test_framework")
test_env.Append(LIBS = arm_compute_test_framework)
-# Remove warnings from tests
-warnings_to_remove = ['-Wno-deprecated-declarations']
-for warning in warnings_to_remove:
- if warning in test_env['CXXFLAGS']:
- test_env['CXXFLAGS'].remove(warning)
-
# Remove -Wnoexcept from tests
if 'g++' in test_env['CXX'] and '-Wnoexcept' in test_env['CXXFLAGS']:
test_env['CXXFLAGS'].remove("-Wnoexcept")
diff --git a/tests/Utils.h b/tests/Utils.h
index f26507d1a..ea70fffe3 100644
--- a/tests/Utils.h
+++ b/tests/Utils.h
@@ -805,6 +805,8 @@ inline void sync_tensor_if_necessary(TensorType &tensor)
t.map();
t.unmap();
}
+#else /* ARM_COMPUTE_GC */
+ ARM_COMPUTE_UNUSED(tensor);
#endif /* ARM_COMPUTE_GC */
}
} // namespace test
diff --git a/tests/benchmark/fixtures/ConvolutionFixture.h b/tests/benchmark/fixtures/ConvolutionFixture.h
index 3f9c2a4f2..f355168ec 100644
--- a/tests/benchmark/fixtures/ConvolutionFixture.h
+++ b/tests/benchmark/fixtures/ConvolutionFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -73,7 +73,7 @@ public:
dst = create_tensor<TensorType>(src_shape, output_data_type);
// Configure function
- configure_target(convolution_func, src, dst, conv.data(), scale, border_mode, constant_border_value);
+ configure_target(src, dst, conv.data(), scale, border_mode, constant_border_value);
// Allocate tensors
src.allocator()->allocate();
@@ -96,7 +96,7 @@ public:
}
protected:
- virtual void configure_target(Function &func, TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale,
+ virtual void configure_target(TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale,
BorderMode border_mode, uint8_t border_value) = 0;
protected:
@@ -122,7 +122,7 @@ public:
}
protected:
- void configure_target(Function &func, TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale,
+ void configure_target(TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale,
BorderMode border_mode, uint8_t constant_border_value)
{
this->convolution_func.configure(&src, &dst, conv, scale, border_mode, constant_border_value);
@@ -141,7 +141,7 @@ public:
}
protected:
- void configure_target(Function &func, TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale,
+ void configure_target(TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale,
BorderMode border_mode, uint8_t constant_border_value)
{
this->convolution_func.configure(&src, &dst, conv, this->_width, this->_height, scale, border_mode, constant_border_value);
@@ -160,7 +160,7 @@ public:
}
protected:
- void configure_target(Function &func, TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale,
+ void configure_target(TensorType &src, TensorType &dst, const int16_t *conv, uint32_t scale,
BorderMode border_mode, uint8_t constant_border_value)
{
this->convolution_func.configure(&src, &dst, conv, scale, border_mode, constant_border_value);
diff --git a/tests/benchmark/fixtures/DepthwiseConvolutionLayerFixture.h b/tests/benchmark/fixtures/DepthwiseConvolutionLayerFixture.h
index 33753bcd0..09da816fd 100644
--- a/tests/benchmark/fixtures/DepthwiseConvolutionLayerFixture.h
+++ b/tests/benchmark/fixtures/DepthwiseConvolutionLayerFixture.h
@@ -47,6 +47,8 @@ public:
template <typename...>
void setup(TensorShape src_shape, Size2D kernel_size, PadStrideInfo info, Size2D Dilation, DataType data_type, int batches)
{
+ ARM_COMPUTE_UNUSED(Dilation);
+
// Get shapes
TensorShape weights_shape(kernel_size.width, kernel_size.height);
diff --git a/tests/benchmark/fixtures/ElementWiseUnaryFixture.h b/tests/benchmark/fixtures/ElementWiseUnaryFixture.h
index e4f76a441..a26f7c84c 100644
--- a/tests/benchmark/fixtures/ElementWiseUnaryFixture.h
+++ b/tests/benchmark/fixtures/ElementWiseUnaryFixture.h
@@ -44,7 +44,7 @@ class ElementWiseUnaryBenchmarkFixture : public framework::Fixture
{
public:
template <typename...>
- void setup(TensorShape input_shape, DataType input_data_type, ElementWiseUnary op)
+ void setup(TensorShape input_shape, DataType input_data_type)
{
src = create_tensor<TensorType>(input_shape, input_data_type);
dst = create_tensor<TensorType>(input_shape, input_data_type);
@@ -80,7 +80,7 @@ public:
template <typename...>
void setup(const TensorShape &shape, DataType data_type)
{
- ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, ElementWiseUnary::RSQRT);
+ ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type);
}
};
@@ -91,7 +91,7 @@ public:
template <typename...>
void setup(const TensorShape &shape, DataType data_type)
{
- ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, ElementWiseUnary::EXP);
+ ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type);
}
};
@@ -102,7 +102,7 @@ public:
template <typename...>
void setup(const TensorShape &shape, DataType data_type)
{
- ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, ElementWiseUnary::NEG);
+ ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type);
}
};
@@ -113,7 +113,7 @@ public:
template <typename...>
void setup(const TensorShape &shape, DataType data_type)
{
- ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, ElementWiseUnary::LOG);
+ ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type);
}
};
@@ -124,7 +124,7 @@ public:
template <typename...>
void setup(const TensorShape &shape, DataType data_type)
{
- ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, ElementWiseUnary::ABS);
+ ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type);
}
};
@@ -135,7 +135,7 @@ public:
template <typename...>
void setup(const TensorShape &shape, DataType data_type)
{
- ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, ElementWiseUnary::SIN);
+ ElementWiseUnaryBenchmarkFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type);
}
};
} // namespace validation
diff --git a/tests/validate_examples/ValidateExample.h b/tests/validate_examples/ValidateExample.h
index 272150833..8076006af 100644
--- a/tests/validate_examples/ValidateExample.h
+++ b/tests/validate_examples/ValidateExample.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2016-2018 ARM Limited.
+ * Copyright (c) 2016-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -50,6 +50,7 @@ public:
*/
virtual bool do_setup(int argc, char **argv)
{
+ ARM_COMPUTE_UNUSED(argc, argv);
return true;
};
/** Run the example. */
@@ -67,6 +68,7 @@ public:
*/
virtual void print_parameters(test::framework::Printer &printer)
{
+ ARM_COMPUTE_UNUSED(printer);
}
/** Default destructor */
diff --git a/tests/validate_examples/graph_validate_utils.h b/tests/validate_examples/graph_validate_utils.h
index 13cc4fa68..7342ccce3 100644
--- a/tests/validate_examples/graph_validate_utils.h
+++ b/tests/validate_examples/graph_validate_utils.h
@@ -405,6 +405,7 @@ public:
arm_compute::test::SimpleTensor<TBias> &bias,
ITensor &tensor)
{
+ ARM_COMPUTE_UNUSED(tensor);
//Create Input tensors
src = arm_compute::test::SimpleTensor<D> { TensorShape(_params.input.width, _params.input.height, _params.input.fm, _params.input.batch), _params.data_type, 1, _params.input.quant_info };
weights = arm_compute::test::SimpleTensor<D> { TensorShape(_params.weights.width, _params.weights.height, _params.weights.fm), _params.data_type, 1, _params.weights.quant_info };
diff --git a/tests/validation/CL/GlobalPoolingLayer.cpp b/tests/validation/CL/GlobalPoolingLayer.cpp
index 586be5e04..bd4fb68c7 100644
--- a/tests/validation/CL/GlobalPoolingLayer.cpp
+++ b/tests/validation/CL/GlobalPoolingLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -61,7 +61,7 @@ TEST_SUITE(Float)
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunGlobalPooling, CLGlobalPoolingLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(GlobalPoolingLayerDataset, framework::dataset::make("DataType",
DataType::F32)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f32);
@@ -71,7 +71,7 @@ TEST_SUITE_END()
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunGlobalPooling, CLGlobalPoolingLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(GlobalPoolingLayerDataset, framework::dataset::make("DataType",
DataType::F16)),
- framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })))
+ framework::dataset::make("DataLayout", { DataLayout::NCHW })))
{
// Validate output
validate(CLAccessor(_target), _reference, tolerance_f16);
diff --git a/tests/validation/CL/Permute.cpp b/tests/validation/CL/Permute.cpp
index e1908abe2..8eb302adc 100644
--- a/tests/validation/CL/Permute.cpp
+++ b/tests/validation/CL/Permute.cpp
@@ -62,9 +62,8 @@ const auto PermuteVectors4 = framework::dataset::make("PermutationVector",
PermutationVector(0U, 3U, 2U, 1U)
});
const auto PermuteVectors = concat(PermuteVectors3, PermuteVectors4);
-const auto PermuteInputLayout = framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC });
-const auto PermuteParametersSmall = concat(concat(datasets::Small2DShapes(), datasets::Small3DShapes()), datasets::Small4DShapes()) * PermuteInputLayout * PermuteVectors;
-const auto PermuteParametersLarge = datasets::Large4DShapes() * PermuteInputLayout * PermuteVectors;
+const auto PermuteParametersSmall = concat(concat(datasets::Small2DShapes(), datasets::Small3DShapes()), datasets::Small4DShapes()) * PermuteVectors;
+const auto PermuteParametersLarge = datasets::Large4DShapes() * PermuteVectors;
} // namespace
TEST_SUITE(CL)
TEST_SUITE(Permute)
diff --git a/tests/validation/CPP/Permute.cpp b/tests/validation/CPP/Permute.cpp
index 2ba10ec65..3d28df17b 100644
--- a/tests/validation/CPP/Permute.cpp
+++ b/tests/validation/CPP/Permute.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -51,9 +51,8 @@ const auto PermuteVectors = framework::dataset::make("PermutationVector",
PermutationVector(1U, 0U, 2U),
PermutationVector(2U, 1U, 0U),
});
-const auto PermuteInputLayout = framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC });
-const auto PermuteParametersSmall = concat(concat(datasets::Small2DShapes(), datasets::Small3DShapes()), datasets::Small4DShapes()) * PermuteInputLayout * PermuteVectors;
-const auto PermuteParametersLarge = datasets::Large4DShapes() * PermuteInputLayout * PermuteVectors;
+const auto PermuteParametersSmall = concat(concat(datasets::Small2DShapes(), datasets::Small3DShapes()), datasets::Small4DShapes()) * PermuteVectors;
+const auto PermuteParametersLarge = datasets::Large4DShapes() * PermuteVectors;
} // namespace
TEST_SUITE(CPP)
diff --git a/tests/validation/NEON/Permute.cpp b/tests/validation/NEON/Permute.cpp
index a5a81b7ac..07578d389 100644
--- a/tests/validation/NEON/Permute.cpp
+++ b/tests/validation/NEON/Permute.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -62,9 +62,8 @@ const auto PermuteVectors4 = framework::dataset::make("PermutationVector",
PermutationVector(0U, 3U, 2U, 1U)
});
const auto PermuteVectors = concat(PermuteVectors3, PermuteVectors4);
-const auto PermuteInputLayout = framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC });
-const auto PermuteParametersSmall = concat(concat(datasets::Small2DShapes(), datasets::Small3DShapes()), datasets::Small4DShapes()) * PermuteInputLayout * PermuteVectors;
-const auto PermuteParametersLarge = datasets::Large4DShapes() * PermuteInputLayout * PermuteVectors;
+const auto PermuteParametersSmall = concat(concat(datasets::Small2DShapes(), datasets::Small3DShapes()), datasets::Small4DShapes()) * PermuteVectors;
+const auto PermuteParametersLarge = datasets::Large4DShapes() * PermuteVectors;
} // namespace
TEST_SUITE(NEON)
TEST_SUITE(Permute)
diff --git a/tests/validation/UNIT/LifetimeManager.cpp b/tests/validation/UNIT/LifetimeManager.cpp
index d4c0a5134..44a52aa5e 100644
--- a/tests/validation/UNIT/LifetimeManager.cpp
+++ b/tests/validation/UNIT/LifetimeManager.cpp
@@ -46,6 +46,7 @@ class MockMemoryManageable : public IMemoryManageable
public:
void associate_memory_group(IMemoryGroup *memory_group) override
{
+ ARM_COMPUTE_UNUSED(memory_group);
}
};
/** Creates a lifetime of three objects where the two of them can share the same underlying within the given scope
diff --git a/tests/validation/fixtures/DropoutLayerFixture.h b/tests/validation/fixtures/DropoutLayerFixture.h
index 771de3091..be2580265 100644
--- a/tests/validation/fixtures/DropoutLayerFixture.h
+++ b/tests/validation/fixtures/DropoutLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -93,6 +93,7 @@ protected:
SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type)
{
+ ARM_COMPUTE_UNUSED(shape, data_type);
}
TensorType _target{};
diff --git a/tests/validation/fixtures/FullyConnectedLayerFixture.h b/tests/validation/fixtures/FullyConnectedLayerFixture.h
index 1e4a74445..0449d80de 100644
--- a/tests/validation/fixtures/FullyConnectedLayerFixture.h
+++ b/tests/validation/fixtures/FullyConnectedLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -64,7 +64,7 @@ public:
_quantization_info = quantization_info;
_target = compute_target(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, reshape_weights);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, reshape_weights);
+ _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape);
}
protected:
@@ -181,8 +181,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, bool transpose_weights,
- bool reshape_weights)
+ SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape)
{
// Create reference
SimpleTensor<T> src{ input_shape, _data_type, 1, _quantization_info };
diff --git a/tests/validation/fixtures/FuseBatchNormalizationFixture.h b/tests/validation/fixtures/FuseBatchNormalizationFixture.h
index 4a81fb082..780b4a0fb 100644
--- a/tests/validation/fixtures/FuseBatchNormalizationFixture.h
+++ b/tests/validation/fixtures/FuseBatchNormalizationFixture.h
@@ -51,7 +51,7 @@ public:
void setup(TensorShape shape_w, DataType data_type, DataLayout data_layout, bool in_place, bool with_bias, bool with_gamma, bool with_beta)
{
std::tie(_target_w, _target_b) = compute_target(shape_w, data_type, data_layout, in_place, with_bias, with_gamma, with_beta);
- std::tie(_reference_w, _reference_b) = compute_reference(shape_w, data_type, data_layout, with_bias, with_gamma, with_beta);
+ std::tie(_reference_w, _reference_b) = compute_reference(shape_w, data_type, with_bias, with_gamma, with_beta);
}
protected:
@@ -138,7 +138,7 @@ protected:
return std::make_pair(std::move(in_place_w ? w : w_fused), std::move(in_place_b ? b : b_fused));
}
- std::pair<SimpleTensor<T>, SimpleTensor<T>> compute_reference(TensorShape shape_w, DataType data_type, DataLayout data_layout, bool with_bias, bool with_gamma, bool with_beta)
+ std::pair<SimpleTensor<T>, SimpleTensor<T>> compute_reference(TensorShape shape_w, DataType data_type, bool with_bias, bool with_gamma, bool with_beta)
{
const TensorShape shape_v(shape_w[dims_weights - 1]);
diff --git a/tests/validation/fixtures/GEMMFixture.h b/tests/validation/fixtures/GEMMFixture.h
index bf919c9b0..efe756707 100644
--- a/tests/validation/fixtures/GEMMFixture.h
+++ b/tests/validation/fixtures/GEMMFixture.h
@@ -51,8 +51,9 @@ public:
template <typename...>
void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, TensorShape output_shape, float alpha, float beta, bool pretranspose, DataType data_type)
{
- _target = compute_target(shape_a, shape_b, shape_c, output_shape, alpha, beta, pretranspose, data_type);
- _reference = compute_reference(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type);
+ ARM_COMPUTE_UNUSED(pretranspose);
+ _target = compute_target(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type);
+ _reference = compute_reference(shape_a, shape_b, output_shape, alpha, beta, data_type);
}
protected:
@@ -74,7 +75,7 @@ protected:
}
TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, const TensorShape &output_shape, float alpha, float beta,
- bool pretranspose, DataType data_type)
+ DataType data_type)
{
// Create tensors
TensorType a = create_tensor<TensorType>(shape_a, data_type, 1);
@@ -124,7 +125,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, const TensorShape &output_shape, float alpha, float beta,
+ SimpleTensor<T> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &output_shape, float alpha, float beta,
DataType data_type)
{
TensorShape shape_a_to_use = shape_a;
@@ -183,7 +184,7 @@ public:
broadcast_bias ? 1 : batch_size);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, broadcast_bias, fp16_mixed_precision, act_info, gpu_arch);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, broadcast_bias, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, broadcast_bias, act_info);
}
protected:
@@ -244,7 +245,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
@@ -289,6 +290,8 @@ public:
void setup(unsigned int m_w, unsigned int m_h, unsigned int n, unsigned int k, unsigned int batch_size, float alpha, float beta, bool broadcast_bias, bool fp16_mixed_precision,
const ActivationLayerInfo &act_info, DataType data_type, GPUTarget gpu_arch)
{
+ ARM_COMPUTE_UNUSED(broadcast_bias);
+
// In case of GEMM3D, m is the product between m_w and m_h
const unsigned int m = m_w * m_h;
@@ -298,7 +301,7 @@ public:
const TensorShape bias_shape(n, 1, 1);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, m_h, fp16_mixed_precision, act_info, gpu_arch);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, m_h, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, m_h, act_info);
}
protected:
@@ -355,7 +358,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
@@ -421,7 +424,7 @@ public:
broadcast_bias ? 1 : batch_size);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, broadcast_bias, fp16_mixed_precision, act_info, gpu_arch);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, broadcast_bias, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, broadcast_bias, act_info);
}
protected:
@@ -494,7 +497,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
@@ -539,6 +542,8 @@ public:
void setup(unsigned int m_w, unsigned int m_h, unsigned int n, unsigned int k, unsigned int batch_size, float alpha, float beta, unsigned int v0, unsigned int h0, bool broadcast_bias,
bool fp16_mixed_precision, const ActivationLayerInfo &act_info, DataType data_type, GPUTarget gpu_arch)
{
+ ARM_COMPUTE_UNUSED(broadcast_bias);
+
GEMMLHSMatrixInfo lhs_info;
lhs_info.m0 = 4;
lhs_info.k0 = 4;
@@ -562,7 +567,7 @@ public:
const TensorShape bias_shape(n, 1, 1);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, m_h, fp16_mixed_precision, act_info, gpu_arch);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, m_h, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, m_h, act_info);
}
protected:
@@ -631,7 +636,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
@@ -697,7 +702,7 @@ public:
broadcast_bias ? 1 : batch_size);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, broadcast_bias, act_info);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, broadcast_bias, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, broadcast_bias, act_info);
}
protected:
@@ -778,7 +783,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
@@ -854,7 +859,7 @@ public:
const TensorShape bias_shape(n, 1, 1);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, m_h, act_info);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, m_h, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, m_h, act_info);
}
protected:
@@ -931,7 +936,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
@@ -1001,7 +1006,7 @@ public:
broadcast_bias ? 1 : batch_size);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, broadcast_bias, act_info);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, broadcast_bias, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, broadcast_bias, act_info);
}
protected:
@@ -1075,7 +1080,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
@@ -1140,7 +1145,7 @@ public:
const TensorShape bias_shape(n, 1, 1);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, m_h, act_info);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, m_h, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, m_h, act_info);
}
protected:
@@ -1211,7 +1216,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
@@ -1271,7 +1276,7 @@ public:
broadcast_bias ? 1 : batch_size);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, broadcast_bias, act_info);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, broadcast_bias, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, broadcast_bias, act_info);
}
protected:
@@ -1337,7 +1342,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, bool broadcast_bias,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
@@ -1399,7 +1404,7 @@ public:
const TensorShape bias_shape(n, 1, 1);
_target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, m_h, act_info);
- _reference = compute_reference(lhs_shape, rhs_shape, bias_shape, data_type, alpha, beta, m_h, act_info);
+ _reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, m_h, act_info);
}
protected:
@@ -1463,7 +1468,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
+ SimpleTensor<T> compute_reference(const TensorShape &lhs_shape, const TensorShape &rhs_shape, DataType data_type, float alpha, float beta, unsigned int m_h,
const ActivationLayerInfo &act_info)
{
TensorShape dst_shape = lhs_shape;
diff --git a/tests/validation/fixtures/GEMMTranspose1xWFixture.h b/tests/validation/fixtures/GEMMTranspose1xWFixture.h
index af2a3b278..89d223834 100644
--- a/tests/validation/fixtures/GEMMTranspose1xWFixture.h
+++ b/tests/validation/fixtures/GEMMTranspose1xWFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -54,7 +54,7 @@ public:
const unsigned int transpose_w = 16 / data_size_from_type(data_type);
const TensorShape shape_b(static_cast<size_t>(y * transpose_w), static_cast<size_t>(std::ceil(x / static_cast<float>(transpose_w))));
_target = compute_target(shape_a, shape_b, data_type);
- _reference = compute_reference(shape_a, shape_b, data_type);
+ _reference = compute_reference(shape_a, data_type);
}
protected:
@@ -106,7 +106,7 @@ protected:
return b;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, DataType data_type)
+ SimpleTensor<T> compute_reference(const TensorShape &shape_a, DataType data_type)
{
// Create reference
SimpleTensor<T> a{ shape_a, data_type, 1 };
diff --git a/tests/validation/fixtures/InstanceNormalizationLayerFixture.h b/tests/validation/fixtures/InstanceNormalizationLayerFixture.h
index 175ef2fb9..5e230d443 100644
--- a/tests/validation/fixtures/InstanceNormalizationLayerFixture.h
+++ b/tests/validation/fixtures/InstanceNormalizationLayerFixture.h
@@ -48,7 +48,7 @@ public:
void setup(TensorShape shape, DataType data_type, DataLayout data_layout, bool in_place)
{
_target = compute_target(shape, data_type, data_layout, in_place);
- _reference = compute_reference(shape, data_type, data_layout);
+ _reference = compute_reference(shape, data_type);
}
protected:
@@ -118,7 +118,7 @@ protected:
}
}
- SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, DataLayout data_layout)
+ SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type)
{
std::mt19937 gen(library->seed());
std::uniform_real_distribution<float> dist_gamma(1.f, 2.f);
diff --git a/tests/validation/fixtures/PermuteFixture.h b/tests/validation/fixtures/PermuteFixture.h
index 92d01a565..76351734d 100644
--- a/tests/validation/fixtures/PermuteFixture.h
+++ b/tests/validation/fixtures/PermuteFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -46,9 +46,9 @@ class PermuteValidationFixture : public framework::Fixture
{
public:
template <typename...>
- void setup(TensorShape input_shape, DataLayout input_layout, PermutationVector perm, DataType data_type)
+ void setup(TensorShape input_shape, PermutationVector perm, DataType data_type)
{
- _target = compute_target(input_shape, input_layout, data_type, perm);
+ _target = compute_target(input_shape, data_type, perm);
_reference = compute_reference(input_shape, data_type, perm);
}
@@ -59,7 +59,7 @@ protected:
library->fill_tensor_uniform(tensor, 0);
}
- TensorType compute_target(const TensorShape &input_shape, DataLayout input_layout, DataType data_type, PermutationVector perm)
+ TensorType compute_target(const TensorShape &input_shape, DataType data_type, PermutationVector perm)
{
// Permute shapes
TensorShape output_shape = input_shape;
diff --git a/tests/validation/fixtures/PoolingLayerFixture.h b/tests/validation/fixtures/PoolingLayerFixture.h
index cdc2cae58..18577edc6 100644
--- a/tests/validation/fixtures/PoolingLayerFixture.h
+++ b/tests/validation/fixtures/PoolingLayerFixture.h
@@ -182,7 +182,7 @@ public:
template <typename...>
void setup(TensorShape shape, PoolingType pool_type, DataType data_type, DataLayout data_layout = DataLayout::NCHW)
{
- PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type), data_type, DataLayout::NCHW);
+ PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type), data_type, data_layout);
}
};
diff --git a/tests/validation/fixtures/UNIT/DynamicTensorFixture.h b/tests/validation/fixtures/UNIT/DynamicTensorFixture.h
index b2600f13f..08b90c5b5 100644
--- a/tests/validation/fixtures/UNIT/DynamicTensorFixture.h
+++ b/tests/validation/fixtures/UNIT/DynamicTensorFixture.h
@@ -104,6 +104,7 @@ public:
}
void configure(ITensorType *src, ITensorType *dst)
{
+ ARM_COMPUTE_UNUSED(src, dst);
}
void run()
{
diff --git a/tests/validation/fixtures/WarpPerspectiveFixture.h b/tests/validation/fixtures/WarpPerspectiveFixture.h
index 0eba97c47..aa84946e9 100644
--- a/tests/validation/fixtures/WarpPerspectiveFixture.h
+++ b/tests/validation/fixtures/WarpPerspectiveFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -58,14 +58,12 @@ public:
constant_border_value = distribution_u8(gen);
}
- const TensorShape vmask_shape(input_shape);
-
// Create the matrix
std::array<float, 9> matrix = { { 0 } };
fill_warp_matrix<9>(matrix);
- _target = compute_target(input_shape, vmask_shape, matrix, policy, border_mode, constant_border_value, data_type);
- _reference = compute_reference(input_shape, vmask_shape, matrix, policy, border_mode, constant_border_value, data_type);
+ _target = compute_target(input_shape, matrix, policy, border_mode, constant_border_value, data_type);
+ _reference = compute_reference(input_shape, matrix, policy, border_mode, constant_border_value, data_type);
}
protected:
@@ -75,7 +73,7 @@ protected:
library->fill_tensor_uniform(tensor, 0);
}
- TensorType compute_target(const TensorShape &shape, const TensorShape &vmask_shape, const std::array<float, 9> &matrix, InterpolationPolicy policy, BorderMode border_mode,
+ TensorType compute_target(const TensorShape &shape, const std::array<float, 9> &matrix, InterpolationPolicy policy, BorderMode border_mode,
uint8_t constant_border_value,
DataType data_type)
{
@@ -106,7 +104,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape, const TensorShape &vmask_shape, const std::array<float, 9> &matrix, InterpolationPolicy policy, BorderMode border_mode,
+ SimpleTensor<T> compute_reference(const TensorShape &shape, const std::array<float, 9> &matrix, InterpolationPolicy policy, BorderMode border_mode,
uint8_t constant_border_value,
DataType data_type)
{
diff --git a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
index c0ba57a82..9c2df9ef4 100644
--- a/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/WinogradConvolutionLayerFixture.h
@@ -81,8 +81,6 @@ protected:
default:
{
ARM_COMPUTE_ERROR("Not supported");
- library->fill_tensor_uniform(tensor, i);
- break;
}
}
}
@@ -168,7 +166,7 @@ public:
{
ARM_COMPUTE_UNUSED(dilation);
_target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info, data_layout);
- _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info);
+ _reference = compute_reference(input_shape, weights_shape, bias_shape, info, data_type, act_info);
}
protected:
@@ -192,8 +190,6 @@ protected:
default:
{
ARM_COMPUTE_ERROR("Not supported");
- library->fill_tensor_uniform(tensor, i);
- break;
}
}
}
@@ -247,7 +243,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
+ SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const PadStrideInfo &info,
DataType data_type, ActivationLayerInfo act_info)
{
// Create reference
@@ -332,7 +328,7 @@ public:
TensorShape output_shape = compute_winograd_input_transform_shape(TensorInfo(input_shape, 1, data_type), winograd_info);
_target = compute_target(input_shape, output_shape, winograd_info, data_layout, data_type);
- _reference = compute_reference(input_shape, output_shape, winograd_info, data_layout, data_type);
+ _reference = compute_reference(input_shape, output_shape, winograd_info, data_type);
}
protected:
@@ -351,8 +347,6 @@ protected:
default:
{
ARM_COMPUTE_ERROR("Not supported");
- library->fill_tensor_uniform(tensor, i);
- break;
}
}
}
@@ -390,7 +384,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &output_shape, const WinogradInfo &winograd_info, DataLayout data_layout, DataType data_type)
+ SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &output_shape, const WinogradInfo &winograd_info, DataType data_type)
{
// Create reference
SimpleTensor<T> src{ input_shape, data_type, 1, QuantizationInfo() };
@@ -416,7 +410,7 @@ public:
TensorShape output_shape = compute_winograd_filter_transform_shape(TensorInfo(input_shape, 1, data_type), winograd_info);
_target = compute_target(input_shape, output_shape, winograd_info, data_layout, data_type);
- _reference = compute_reference(input_shape, output_shape, winograd_info, data_layout, data_type);
+ _reference = compute_reference(input_shape, output_shape, winograd_info, data_type);
}
protected:
@@ -435,8 +429,6 @@ protected:
default:
{
ARM_COMPUTE_ERROR("Not supported");
- library->fill_tensor_uniform(tensor, i);
- break;
}
}
}
@@ -474,7 +466,7 @@ protected:
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &output_shape, const WinogradInfo &winograd_info, DataLayout data_layout, DataType data_type)
+ SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &output_shape, const WinogradInfo &winograd_info, DataType data_type)
{
// Create reference
SimpleTensor<T> src{ input_shape, data_type, 1, QuantizationInfo() };
@@ -516,8 +508,6 @@ protected:
default:
{
ARM_COMPUTE_ERROR("Not supported");
- library->fill_tensor_uniform(tensor, i);
- break;
}
}
}
diff --git a/tests/validation/reference/ColorConvert.cpp b/tests/validation/reference/ColorConvert.cpp
index 9090319a8..a759594cf 100644
--- a/tests/validation/reference/ColorConvert.cpp
+++ b/tests/validation/reference/ColorConvert.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -170,7 +170,7 @@ std::vector<SimpleTensor<T>> color_convert(const TensorShape &shape, const std::
{
case Format::RGB888:
case Format::RGBA8888:
- colorconvert_helper::detail::colorconvert_iyuv_to_rgb(shape, tensor_planes, dst[0]);
+ colorconvert_helper::detail::colorconvert_iyuv_to_rgb(tensor_planes, dst[0]);
break;
default:
ARM_COMPUTE_ERROR("Not Supported");
@@ -185,7 +185,7 @@ std::vector<SimpleTensor<T>> color_convert(const TensorShape &shape, const std::
{
case Format::RGB888:
case Format::RGBA8888:
- colorconvert_helper::detail::colorconvert_nv12_to_rgb(shape, src_format, tensor_planes, dst[0]);
+ colorconvert_helper::detail::colorconvert_nv12_to_rgb(src_format, tensor_planes, dst[0]);
break;
case Format::IYUV:
colorconvert_helper::detail::colorconvert_nv_to_iyuv(tensor_planes, src_format, dst);
diff --git a/tests/validation/reference/ColorConvertHelper.h b/tests/validation/reference/ColorConvertHelper.h
index abd1f5d1f..8dd961c0f 100644
--- a/tests/validation/reference/ColorConvertHelper.h
+++ b/tests/validation/reference/ColorConvertHelper.h
@@ -306,7 +306,7 @@ inline void colorconvert_yuyv_to_rgb(const SimpleTensor<T> src, const Format for
}
template <typename T>
-inline void colorconvert_iyuv_to_rgb(const TensorShape &shape, const std::vector<SimpleTensor<T>> &tensor_planes, SimpleTensor<T> &dst)
+inline void colorconvert_iyuv_to_rgb(const std::vector<SimpleTensor<T>> &tensor_planes, SimpleTensor<T> &dst)
{
SimpleTensor<T> yvec(TensorShape{ tensor_planes[0].shape().x() / 2, tensor_planes[0].shape().y() }, Format::U8);
SimpleTensor<T> uvec(TensorShape{ tensor_planes[0].shape().x() / 2, tensor_planes[0].shape().y() }, Format::U8);
@@ -361,7 +361,7 @@ inline void colorconvert_iyuv_to_rgb(const TensorShape &shape, const std::vector
}
template <typename T>
-inline void colorconvert_nv12_to_rgb(const TensorShape &shape, const Format format, const std::vector<SimpleTensor<T>> &tensor_planes, SimpleTensor<T> &dst)
+inline void colorconvert_nv12_to_rgb(const Format format, const std::vector<SimpleTensor<T>> &tensor_planes, SimpleTensor<T> &dst)
{
SimpleTensor<T> yvec(TensorShape{ tensor_planes[0].shape().x() / 2, tensor_planes[0].shape().y() }, Format::U8);
SimpleTensor<T> uvec(TensorShape{ tensor_planes[0].shape().x() / 2, tensor_planes[0].shape().y() }, Format::U8);
diff --git a/tests/validation/reference/ROIAlignLayer.cpp b/tests/validation/reference/ROIAlignLayer.cpp
index 415b483bc..c32dce72e 100644
--- a/tests/validation/reference/ROIAlignLayer.cpp
+++ b/tests/validation/reference/ROIAlignLayer.cpp
@@ -132,6 +132,8 @@ SimpleTensor<float> convert_rois_from_asymmetric(SimpleTensor<uint16_t> rois)
template <typename T, typename TRois>
SimpleTensor<T> roi_align_layer(const SimpleTensor<T> &src, const SimpleTensor<TRois> &rois, const ROIPoolingLayerInfo &pool_info, const QuantizationInfo &output_qinfo)
{
+ ARM_COMPUTE_UNUSED(output_qinfo);
+
const size_t values_per_roi = rois.shape()[0];
const size_t num_rois = rois.shape()[1];
DataType dst_data_type = src.data_type();
diff --git a/utils/GraphUtils.cpp b/utils/GraphUtils.cpp
index 3646facab..eaa7d7977 100644
--- a/utils/GraphUtils.cpp
+++ b/utils/GraphUtils.cpp
@@ -28,7 +28,11 @@
#include "arm_compute/core/Types.h"
#include "arm_compute/graph/Logger.h"
#include "arm_compute/runtime/SubTensor.h"
+
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wunused-parameter"
#include "utils/ImageLoader.h"
+#pragma GCC diagnostic pop
#include "utils/Utils.h"
#include <iomanip>
diff --git a/utils/GraphUtils.h b/utils/GraphUtils.h
index 4c25dd246..826ffff8c 100644
--- a/utils/GraphUtils.h
+++ b/utils/GraphUtils.h
@@ -518,6 +518,7 @@ inline std::unique_ptr<graph::ITensorAccessor> get_output_accessor(const arm_com
bool is_validation = false,
std::ostream &output_stream = std::cout)
{
+ ARM_COMPUTE_UNUSED(is_validation);
if(!graph_parameters.validation_file.empty())
{
return arm_compute::support::cpp14::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file,
@@ -551,6 +552,7 @@ inline std::unique_ptr<graph::ITensorAccessor> get_detection_output_accessor(con
bool is_validation = false,
std::ostream &output_stream = std::cout)
{
+ ARM_COMPUTE_UNUSED(is_validation);
if(!graph_parameters.validation_file.empty())
{
return arm_compute::support::cpp14::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file,
diff --git a/utils/ImageLoader.h b/utils/ImageLoader.h
index 5d3a84c59..5a2825ebc 100644
--- a/utils/ImageLoader.h
+++ b/utils/ImageLoader.h
@@ -203,7 +203,7 @@ public:
unsigned char green = 0;
unsigned char blue = 0;
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
red = _feeder->get();
green = _feeder->get();
@@ -225,7 +225,7 @@ public:
Iterator out(&image, window);
size_t row_size = _width * image.info()->element_size();
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
_feeder->get_row(out.ptr(), row_size);
},
@@ -302,7 +302,7 @@ public:
unsigned char green = 0;
unsigned char blue = 0;
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
red = _feeder->get();
green = _feeder->get();
@@ -352,6 +352,7 @@ protected:
/** Validate metadata */
virtual void validate_info(const ITensorInfo *tensor_info)
{
+ ARM_COMPUTE_UNUSED(tensor_info);
}
protected:
@@ -418,7 +419,7 @@ protected:
ARM_COMPUTE_ERROR_ON_MSG((end_position - current_position) < tensor_info->tensor_shape().total_size(),
"Not enough data in file");
- ARM_COMPUTE_UNUSED(end_position);
+ ARM_COMPUTE_UNUSED(end_position, tensor_info);
}
private:
diff --git a/utils/Utils.cpp b/utils/Utils.cpp
index baf829b47..b0e162acc 100644
--- a/utils/Utils.cpp
+++ b/utils/Utils.cpp
@@ -34,6 +34,7 @@
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wswitch-default"
+#pragma GCC diagnostic ignored "-Wunused-parameter"
#define STB_IMAGE_IMPLEMENTATION
#include "stb/stb_image.h"
#pragma GCC diagnostic pop
@@ -313,6 +314,8 @@ void restore_program_cache_from_file(const std::string &filename)
}
cache_file.close();
}
+#else /* ARM_COMPUTE_CL */
+ ARM_COMPUTE_UNUSED(filename);
#endif /* ARM_COMPUTE_CL */
}
@@ -347,6 +350,8 @@ void save_program_cache_to_file(const std::string &filename)
ARM_COMPUTE_ERROR("Cannot open cache file");
}
}
+#else /* ARM_COMPUTE_CL */
+ ARM_COMPUTE_UNUSED(filename);
#endif /* ARM_COMPUTE_CL */
}
} // namespace utils
diff --git a/utils/Utils.h b/utils/Utils.h
index 7fa74ab08..d669730a3 100644
--- a/utils/Utils.h
+++ b/utils/Utils.h
@@ -30,7 +30,10 @@
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include "arm_compute/runtime/Tensor.h"
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wunused-parameter"
#include "libnpy/npy.hpp"
+#pragma GCC diagnostic pop
#include "support/ToolchainSupport.h"
#ifdef ARM_COMPUTE_CL
@@ -79,6 +82,7 @@ public:
*/
virtual bool do_setup(int argc, char **argv)
{
+ ARM_COMPUTE_UNUSED(argc, argv);
return true;
};
/** Run the example. */
@@ -570,7 +574,7 @@ void save_to_ppm(T &tensor, const std::string &ppm_filename)
arm_compute::Iterator in(&tensor, window);
- arm_compute::execute_window_loop(window, [&](const arm_compute::Coordinates & id)
+ arm_compute::execute_window_loop(window, [&](const arm_compute::Coordinates &)
{
const unsigned char value = *in.ptr();
@@ -588,7 +592,7 @@ void save_to_ppm(T &tensor, const std::string &ppm_filename)
arm_compute::Iterator in(&tensor, window);
- arm_compute::execute_window_loop(window, [&](const arm_compute::Coordinates & id)
+ arm_compute::execute_window_loop(window, [&](const arm_compute::Coordinates &)
{
fs.write(reinterpret_cast<std::fstream::char_type *>(in.ptr()), width * tensor.info()->element_size());
},
@@ -653,7 +657,7 @@ void save_to_npy(T &tensor, const std::string &npy_filename, bool fortran_order)
arm_compute::Iterator in(&tensor, window);
- arm_compute::execute_window_loop(window, [&](const arm_compute::Coordinates & id)
+ arm_compute::execute_window_loop(window, [&](const arm_compute::Coordinates &)
{
stream.write(reinterpret_cast<const char *>(in.ptr()), sizeof(typestring_type));
},
@@ -705,7 +709,7 @@ void load_trained_data(T &tensor, const std::string &filename)
arm_compute::Iterator in(&tensor, window);
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
fs.read(reinterpret_cast<std::fstream::char_type *>(in.ptr()), tensor.info()->tensor_shape()[0] * tensor.info()->element_size());
},
@@ -739,7 +743,7 @@ void fill_random_tensor(T &tensor, float lower_bound, float upper_bound)
{
std::uniform_real_distribution<float> dist(lower_bound, upper_bound);
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
*reinterpret_cast<half *>(it.ptr()) = (half)dist(gen);
},
@@ -751,7 +755,7 @@ void fill_random_tensor(T &tensor, float lower_bound, float upper_bound)
{
std::uniform_real_distribution<float> dist(lower_bound, upper_bound);
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
*reinterpret_cast<float *>(it.ptr()) = dist(gen);
},
@@ -803,7 +807,7 @@ int compare_tensor(ITensor &tensor1, ITensor &tensor2, T tolerance)
Iterator itensor1(&tensor1, window);
Iterator itensor2(&tensor2, window);
- execute_window_loop(window, [&](const Coordinates & id)
+ execute_window_loop(window, [&](const Coordinates &)
{
if(std::abs(*reinterpret_cast<T *>(itensor1.ptr()) - *reinterpret_cast<T *>(itensor2.ptr())) > tolerance)
{