COMPMID-2248
L2NormalizeLayer: negative axis
Change-Id: Ic164d7a9ddf1615a2e3b0e10430c34194a70f221
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1127
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h b/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h
index 8dd4609..ec192be 100644
--- a/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -55,10 +55,10 @@
* Sum will have the same number of dimensions as input.
* @param[out] output Destination tensor. Data types and data layouts supported: Same as @p input.
* Output will have the same number of dimensions as input.
- * @param[in] axis Axis along which to reduce. Supported reduction axis : 0, 1, 2
+ * @param[in] axis Axis along which to reduce. Negative values wrap around. Maximum supported actual reduction axis : 2
* @param[in] epsilon Lower bound value for the normalization.
*/
- void configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, unsigned int axis, float epsilon);
+ void configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon);
/** Static function to check if given info will lead to a valid configuration of @ref CLL2NormalizeLayerKernel.
*
@@ -67,12 +67,12 @@
* Sum will have the same number of dimensions as input.
* @param[in] output Destination tensor info. Data types and data layouts supported: Same as @p input.
* Output will have the same number of dimensions as input.
- * @param[in] axis Axis along which to reduce. Supported reduction axis : 0, 1, 2
+ * @param[in] axis Axis along which to reduce. Negative values wrap around. Maximum supported actual reduction axis : 2
* @param[in] epsilon Lower bound value for the normalization.
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, unsigned int axis, float epsilon);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon);
// Inherited methods overridden:
void run(const Window &window, cl::CommandQueue &queue) override;
@@ -81,7 +81,7 @@
const ICLTensor *_input;
const ICLTensor *_sum;
ICLTensor *_output;
- unsigned int _axis;
+ unsigned int _actual_axis;
float _epsilon;
};
} // namespace arm_compute
diff --git a/arm_compute/core/NEON/kernels/NEL2NormalizeLayerKernel.h b/arm_compute/core/NEON/kernels/NEL2NormalizeLayerKernel.h
index f893c4a..ab5e040 100644
--- a/arm_compute/core/NEON/kernels/NEL2NormalizeLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEL2NormalizeLayerKernel.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -57,10 +57,10 @@
* Sum will have the same number of dimensions as input.
* @param[out] output Destination tensor. Data types and data layouts supported: same as @p input.
* Output will have the same number of dimensions as input.
- * @param[in] axis Dimension along which to reduce. Supported reduction axis : 0, 1, 2
+ * @param[in] axis Axis along which to reduce. Negative values wrap around. Maximum supported actual reduction axis : 2
* @param[in] epsilon Lower bound value for the normalization.
*/
- void configure(const ITensor *input, const ITensor *sum, ITensor *output, unsigned int axis, float epsilon);
+ void configure(const ITensor *input, const ITensor *sum, ITensor *output, int axis, float epsilon);
/** Static function to check if given info will lead to a valid configuration of @ref NEL2NormalizeLayerKernel.
*
@@ -69,12 +69,12 @@
* Sum will have the same number of dimensions as input.
* @param[in] output Destination tensor info. Data types and data layouts supported: same as @p input.
* Output will have the same number of dimensions as input.
- * @param[in] axis Dimension along which to reduce. Supported reduction axis : 0, 1, 2
+ * @param[in] axis Axis along which to reduce. Negative values wrap around. Maximum supported actual reduction axis : 2
* @param[in] epsilon Lower bound value for the normalization.
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, unsigned int axis, float epsilon);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon);
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;
@@ -83,7 +83,7 @@
const ITensor *_input;
const ITensor *_sum;
ITensor *_output;
- unsigned int _axis;
+ unsigned int _actual_axis;
float _epsilon;
};
} // namespace arm_compute
diff --git a/arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h b/arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h
index 2cabaee..15dcc58 100644
--- a/arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h
+++ b/arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -55,21 +55,21 @@
*
* @param[in] input Source tensor. Data types supported: F16/F32. Data layouts supported: NCHW/NHWC.
* @param[out] output Destination tensor. Data types and data layouts supported: Same as @p input.
- * @param[in] axis Axis along which to reduce. Supported reduction axis : 0, 1, 2
+ * @param[in] axis Axis along which to reduce. Negative values wrap around. Maximum supported actual reduction axis : 2
* @param[in] epsilon (Optional) Lower bound value for the normalization.
*/
- void configure(ICLTensor *input, ICLTensor *output, unsigned int axis, float epsilon = 1e-12f);
+ void configure(ICLTensor *input, ICLTensor *output, int axis, float epsilon = 1e-12f);
/** Static function to check if given info will lead to a valid configuration of @ref CLL2NormalizeLayer.
*
* @param[in] input Source tensor info. Data types supported: F16/F32. Data layouts supported: NCHW/NHWC.
* @param[in] output Destination tensor info. Data types and data layouts supported: Same as @p input.
- * @param[in] axis Axis along which to reduce. Supported reduction axis : 0, 1, 2
+ * @param[in] axis Axis along which to reduce. Negative values wrap around. Maximum supported actual reduction axis : 2
* @param[in] epsilon (Optional) Lower bound value for the normalization.
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, float epsilon = 1e-12f);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, int axis, float epsilon = 1e-12f);
// Inherited methods overridden:
void run() override;
diff --git a/arm_compute/runtime/NEON/functions/NEL2NormalizeLayer.h b/arm_compute/runtime/NEON/functions/NEL2NormalizeLayer.h
index ba506fa..e778f96 100644
--- a/arm_compute/runtime/NEON/functions/NEL2NormalizeLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEL2NormalizeLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -52,21 +52,21 @@
*
* @param[in, out] input Source tensor. Data types supported: F16/F32. (Written to only for border_size != 0)
* @param[out] output Destination tensor. Data types and data layouts supported: same as @p input.
- * @param[in] axis Dimension along which to reduce. Supported reduction axis : 0, 1, 2
+ * @param[in] axis Axis along which to reduce. Negative values wrap around. Maximum supported actual reduction axis : 2
* @param[in] epsilon (Optional) Lower bound value for the normalization.
*/
- void configure(ITensor *input, ITensor *output, unsigned int axis, float epsilon = 1e-12f);
+ void configure(ITensor *input, ITensor *output, int axis, float epsilon = 1e-12f);
/** Static function to check if given info will lead to a valid configuration of @ref NEL2NormalizeLayer.
*
* @param[in] input Source tensor info. Data types supported: F16/F32. (Written to only for border_size != 0)
* @param[in] output Destination tensor info. Data types and data layouts supported: same as @p input.
- * @param[in] axis Dimension along which to reduce. Supported reduction axis : 0, 1, 2
+ * @param[in] axis Axis along which to reduce. Negative values wrap around. Maximum supported actual reduction axis : 2
* @param[in] epsilon (Optional) Lower bound value for the normalization.
*
* @return a status
*/
- static Status validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, float epsilon = 1e-12f);
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, int axis, float epsilon = 1e-12f);
// Inherited methods overridden:
void run() override;
diff --git a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
index cb2e294..00af590 100644
--- a/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
+++ b/src/core/CL/kernels/CLL2NormalizeLayerKernel.cpp
@@ -35,29 +35,32 @@
#include "support/ToolchainSupport.h"
-using namespace arm_compute;
-
+namespace arm_compute
+{
CLL2NormalizeLayerKernel::CLL2NormalizeLayerKernel()
- : _input(nullptr), _sum(nullptr), _output(nullptr), _axis(0), _epsilon(1e-12)
+ : _input(nullptr), _sum(nullptr), _output(nullptr), _actual_axis(0), _epsilon(1e-12)
{
}
namespace
{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, unsigned int axis, float epsilon)
+constexpr int max_input_tensor_dim = 3;
+
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
{
ARM_COMPUTE_UNUSED(epsilon);
+ const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, sum, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 2, "Axis greater than 2 is not supported");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis > 2, "Actual axis greater than 2 is not supported");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis >= TensorShape::num_max_dimensions, "Actual normalization axis greater than max number of dimensions");
// Reduce shape on axis
TensorShape sum_shape = input->tensor_shape();
- sum_shape.set(axis, 1);
+ sum_shape.set(actual_axis, 1);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(sum->tensor_shape(), sum_shape);
if(output->total_size() != 0)
@@ -92,7 +95,7 @@
}
} // namespace
-void CLL2NormalizeLayerKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, unsigned int axis, float epsilon)
+void CLL2NormalizeLayerKernel::configure(const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, int axis, float epsilon)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon));
@@ -100,7 +103,7 @@
_input = input;
_sum = sum;
_output = output;
- _axis = axis;
+ _actual_axis = wrap_around(axis, max_input_tensor_dim);
_epsilon = epsilon;
const unsigned int num_elems_processed_per_iteration = 16;
@@ -113,7 +116,7 @@
// Create kernel
std::string kernel_name;
unsigned int idx = 0;
- switch(axis)
+ switch(_actual_axis)
{
case 0:
kernel_name = "x";
@@ -128,7 +131,7 @@
idx = num_arguments_per_3D_tensor() * 3;
break;
default:
- ARM_COMPUTE_ERROR("Not supported");
+ ARM_COMPUTE_ERROR("Axis not supported");
}
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("l2_normalize_" + kernel_name, build_opts));
@@ -149,7 +152,7 @@
ICLKernel::configure_internal(std::get<1>(win_config));
}
-Status CLL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, unsigned int axis, float epsilon)
+Status CLL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, sum, output, axis, epsilon));
ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get())));
@@ -164,7 +167,7 @@
Window window_sum(window);
- switch(_axis)
+ switch(_actual_axis)
{
case 0:
{
@@ -218,3 +221,4 @@
ARM_COMPUTE_ERROR("Not supported");
}
}
+} // namespace arm_compute
\ No newline at end of file
diff --git a/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp b/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp
index efdcc44..9900446 100644
--- a/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp
@@ -40,6 +40,8 @@
{
namespace
{
+constexpr int max_input_tensor_dim = 3;
+
template <typename T, int S>
void l2_normalize_X(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window)
{
@@ -141,19 +143,20 @@
while(window.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(sum_slice));
}
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, unsigned int axis, float epsilon)
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
{
ARM_COMPUTE_UNUSED(epsilon);
+ const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, sum, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 2, "Axis greater than 2 is not supported");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Normalization axis greater than max number of dimensions");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis > 2, "Actual axis greater than 2 is not supported");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis >= TensorShape::num_max_dimensions, "Actual normalization axis greater than max number of dimensions");
// Reduce shape on axis
TensorShape sum_shape = input->tensor_shape();
- sum_shape.set(axis, 1);
+ sum_shape.set(actual_axis, 1);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(sum->tensor_shape(), sum_shape);
if(output->total_size() != 0)
@@ -167,10 +170,11 @@
return Status{};
}
-std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *sum, ITensorInfo *output, unsigned int axis)
+std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *sum, ITensorInfo *output, int axis)
{
+ const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
const unsigned int num_elems_processed_per_iteration = 16 / data_size_from_type(input->data_type());
- const unsigned int num_elems_processed_per_iteration_sum = (axis == 0) ? 1 : num_elems_processed_per_iteration;
+ const unsigned int num_elems_processed_per_iteration_sum = (actual_axis == 0) ? 1 : num_elems_processed_per_iteration;
Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
@@ -191,11 +195,11 @@
} // namespace
NEL2NormalizeLayerKernel::NEL2NormalizeLayerKernel()
- : _input(nullptr), _sum(nullptr), _output(nullptr), _axis(0), _epsilon(1e-12)
+ : _input(nullptr), _sum(nullptr), _output(nullptr), _actual_axis(0), _epsilon(1e-12)
{
}
-void NEL2NormalizeLayerKernel::configure(const ITensor *input, const ITensor *sum, ITensor *output, unsigned int axis, float epsilon)
+void NEL2NormalizeLayerKernel::configure(const ITensor *input, const ITensor *sum, ITensor *output, int axis, float epsilon)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon));
@@ -203,7 +207,7 @@
_input = input;
_sum = sum;
_output = output;
- _axis = axis;
+ _actual_axis = wrap_around(axis, max_input_tensor_dim);
_epsilon = epsilon;
// Configure kernel window
@@ -213,7 +217,7 @@
INEKernel::configure(std::get<1>(win_config));
}
-Status NEL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, unsigned int axis, float epsilon)
+Status NEL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, sum, output, axis, epsilon));
ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), sum->clone().get(), output->clone().get(), axis)));
@@ -227,7 +231,7 @@
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
- switch(_axis)
+ switch(_actual_axis)
{
case 0:
switch(_input->info()->data_type())
diff --git a/src/runtime/CL/functions/CLL2NormalizeLayer.cpp b/src/runtime/CL/functions/CLL2NormalizeLayer.cpp
index 136cb5e..e76e4f6 100644
--- a/src/runtime/CL/functions/CLL2NormalizeLayer.cpp
+++ b/src/runtime/CL/functions/CLL2NormalizeLayer.cpp
@@ -34,25 +34,31 @@
namespace arm_compute
{
+namespace
+{
+constexpr int max_input_tensor_dim = 3;
+} // namespace
+
CLL2NormalizeLayer::CLL2NormalizeLayer(std::shared_ptr<IMemoryManager> memory_manager)
: _memory_group(std::move(memory_manager)), _reduce_func(), _normalize_kernel(), _sumsq()
{
}
-void CLL2NormalizeLayer::configure(ICLTensor *input, ICLTensor *output, unsigned int axis, float epsilon)
+void CLL2NormalizeLayer::configure(ICLTensor *input, ICLTensor *output, int axis, float epsilon)
{
// Manage intermediate buffers
_memory_group.manage(&_sumsq);
// Configure kernels
- _reduce_func.configure(input, &_sumsq, axis, ReductionOperation::SUM_SQUARE);
+ const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
+ _reduce_func.configure(input, &_sumsq, actual_axis, ReductionOperation::SUM_SQUARE);
_normalize_kernel.configure(input, &_sumsq, output, axis, epsilon);
// Allocate intermediate tensor
_sumsq.allocator()->allocate();
}
-Status CLL2NormalizeLayer::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, float epsilon)
+Status CLL2NormalizeLayer::validate(const ITensorInfo *input, const ITensorInfo *output, int axis, float epsilon)
{
TensorShape shape(input->tensor_shape());
@@ -61,10 +67,11 @@
sum_sq.set_data_type(input->data_type());
sum_sq.set_tensor_shape(shape);
- ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperation::validate(input, &sum_sq, axis, ReductionOperation::SUM_SQUARE));
+ const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
+ ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperation::validate(input, &sum_sq, actual_axis, ReductionOperation::SUM_SQUARE));
// Reduce shape on axis
- shape.set(axis, 1);
+ shape.set(actual_axis, 1);
sum_sq.set_tensor_shape(shape);
ARM_COMPUTE_RETURN_ON_ERROR(CLL2NormalizeLayerKernel::validate(input, &sum_sq, output, axis, epsilon));
diff --git a/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp b/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp
index c9ab5c9..88ffdbf 100644
--- a/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp
+++ b/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp
@@ -28,25 +28,31 @@
namespace arm_compute
{
+namespace
+{
+constexpr int max_input_tensor_dim = 3;
+} // namespace
+
NEL2NormalizeLayer::NEL2NormalizeLayer(std::shared_ptr<IMemoryManager> memory_manager)
: _memory_group(std::move(memory_manager)), _reduce_func(), _normalize_kernel(), _sumsq()
{
}
-void NEL2NormalizeLayer::configure(ITensor *input, ITensor *output, unsigned int axis, float epsilon)
+void NEL2NormalizeLayer::configure(ITensor *input, ITensor *output, int axis, float epsilon)
{
// Manage intermediate buffers
_memory_group.manage(&_sumsq);
// Configure Kernels
- _reduce_func.configure(input, &_sumsq, axis, ReductionOperation::SUM_SQUARE);
+ const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
+ _reduce_func.configure(input, &_sumsq, actual_axis, ReductionOperation::SUM_SQUARE);
_normalize_kernel.configure(input, &_sumsq, output, axis, epsilon);
// Allocate intermediate tensors
_sumsq.allocator()->allocate();
}
-Status NEL2NormalizeLayer::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, float epsilon)
+Status NEL2NormalizeLayer::validate(const ITensorInfo *input, const ITensorInfo *output, int axis, float epsilon)
{
TensorShape shape(input->tensor_shape());
@@ -55,10 +61,11 @@
sum_sq.set_data_type(input->data_type());
sum_sq.set_tensor_shape(shape);
- ARM_COMPUTE_RETURN_ON_ERROR(NEReductionOperation::validate(input, &sum_sq, axis, ReductionOperation::SUM_SQUARE));
+ const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
+ ARM_COMPUTE_RETURN_ON_ERROR(NEReductionOperation::validate(input, &sum_sq, actual_axis, ReductionOperation::SUM_SQUARE));
// Reduce shape on axis
- shape.set(axis, 1);
+ shape.set(actual_axis, 1);
sum_sq.set_tensor_shape(shape);
ARM_COMPUTE_RETURN_ON_ERROR(NEL2NormalizeLayerKernel::validate(input, &sum_sq, output, axis, epsilon));
diff --git a/tests/validation/CL/L2NormalizeLayer.cpp b/tests/validation/CL/L2NormalizeLayer.cpp
index fdbfa3e..beedd81 100644
--- a/tests/validation/CL/L2NormalizeLayer.cpp
+++ b/tests/validation/CL/L2NormalizeLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -46,8 +46,8 @@
constexpr AbsoluteTolerance<float> tolerance_f32(0.00001f);
constexpr AbsoluteTolerance<float> tolerance_f16(0.2f);
-auto data = concat(combine(framework::dataset::make("DataLayout", { DataLayout::NCHW }), framework::dataset::make("Axis", { 0, 1, 2 })), combine(framework::dataset::make("DataLayout", { DataLayout::NHWC }),
- framework::dataset::make("Axis", { 1, 2 })));
+auto data = concat(combine(framework::dataset::make("DataLayout", { DataLayout::NCHW }), framework::dataset::make("Axis", { -1, 0, 2 })), combine(framework::dataset::make("DataLayout", { DataLayout::NHWC }),
+ framework::dataset::make("Axis", { -2, 2 })));
} // namespace
@@ -61,8 +61,9 @@
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Mismatching shape input/output
TensorInfo(TensorShape(128U, 64U), 2, DataType::F32), // Number of Input channels != 1
TensorInfo(TensorShape(128U, 64U), 1, DataType::S16), // DataType != F32
- TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis >= num_max_dimensions
- TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis > 2
+ TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
}),
framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(128U, 64U), 1, DataType::F16),
@@ -71,10 +72,19 @@
TensorInfo(TensorShape(128U, 64U), 1, DataType::S16),
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
})),
- framework::dataset::make("Axis", { 0U, 0U, 0U, 0U, static_cast<unsigned int>(TensorShape::num_max_dimensions), 3U, 0U })),
- framework::dataset::make("Expected", { false, false, false, false, false, false, true })),
+ framework::dataset::make("Axis", {
+ 0,
+ 0,
+ 0,
+ 0,
+ static_cast<int>(TensorShape::num_max_dimensions),
+ 3,
+ -2,
+ 0 })),
+ framework::dataset::make("Expected", { false, false, false, false, true, true, true, true })),
input_info, output_info, axis, expected)
{
bool is_valid = bool(CLL2NormalizeLayer::validate(&input_info.clone()->set_is_resizable(false),
diff --git a/tests/validation/NEON/L2NormalizeLayer.cpp b/tests/validation/NEON/L2NormalizeLayer.cpp
index 3164a65..17147c1 100644
--- a/tests/validation/NEON/L2NormalizeLayer.cpp
+++ b/tests/validation/NEON/L2NormalizeLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -59,8 +59,9 @@
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Mismatching shape input/output
TensorInfo(TensorShape(128U, 64U), 2, DataType::F32), // Number of Input channels != 1
TensorInfo(TensorShape(128U, 64U), 1, DataType::S16), // DataType != F32
- TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis >= num_max_dimensions
- TensorInfo(TensorShape(128U, 64U), 1, DataType::F32), // Axis > 2
+ TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
}),
framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(128U, 64U), 1, DataType::F16),
@@ -69,10 +70,19 @@
TensorInfo(TensorShape(128U, 64U), 1, DataType::S16),
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U), 1, DataType::F32),
TensorInfo(TensorShape(128U, 64U), 1, DataType::F32)
})),
- framework::dataset::make("Axis", { 0U, 0U, 0U, 0U, static_cast<unsigned int>(TensorShape::num_max_dimensions), 3U, 0U })),
- framework::dataset::make("Expected", { false, false, false, false, false, false, true })),
+ framework::dataset::make("Axis", {
+ 0,
+ 0,
+ 0,
+ 0,
+ static_cast<int>(TensorShape::num_max_dimensions),
+ 3,
+ -2,
+ 0 })),
+ framework::dataset::make("Expected", { false, false, false, false, true, true, true, true })),
input_info, output_info, axis, expected)
{
bool is_valid = bool(NEL2NormalizeLayer::validate(&input_info.clone()->set_is_resizable(false),
@@ -89,7 +99,7 @@
TEST_SUITE(FP32)
FIXTURE_DATA_TEST_CASE(RunSmall, NEL2NormalizeLayerFixture<float>, framework::DatasetMode::PRECOMMIT,
combine(combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- framework::dataset::make("Axis", { 0, 1, 2 })),
+ framework::dataset::make("Axis", { -1, 0, 2 })),
framework::dataset::make("Epsilon", { 1e-12 })))
{
// Validate output
@@ -98,7 +108,7 @@
FIXTURE_DATA_TEST_CASE(RunLarge, NEL2NormalizeLayerFixture<float>, framework::DatasetMode::NIGHTLY,
combine(combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- framework::dataset::make("Axis", { 0, 1, 2 })),
+ framework::dataset::make("Axis", { -1, 0, 2 })),
framework::dataset::make("Epsilon", { 1e-12 })))
{
// Validate output
@@ -110,7 +120,7 @@
TEST_SUITE(FP16)
FIXTURE_DATA_TEST_CASE(RunSmall, NEL2NormalizeLayerFixture<half>, framework::DatasetMode::PRECOMMIT,
combine(combine(combine(combine(datasets::SmallShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- framework::dataset::make("Axis", { 0, 1, 2 })),
+ framework::dataset::make("Axis", { -1, 0, 2 })),
framework::dataset::make("Epsilon", { 1e-12 })))
{
// Validate output
@@ -119,7 +129,7 @@
FIXTURE_DATA_TEST_CASE(RunLarge, NEL2NormalizeLayerFixture<half>, framework::DatasetMode::NIGHTLY,
combine(combine(combine(combine(datasets::LargeShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
- framework::dataset::make("Axis", { 0, 1, 2 })),
+ framework::dataset::make("Axis", { -1, 0, 2 })),
framework::dataset::make("Epsilon", { 1e-12 })))
{
// Validate output
diff --git a/tests/validation/fixtures/L2NormalizeLayerFixture.h b/tests/validation/fixtures/L2NormalizeLayerFixture.h
index 574722b..e3e1510 100644
--- a/tests/validation/fixtures/L2NormalizeLayerFixture.h
+++ b/tests/validation/fixtures/L2NormalizeLayerFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -40,12 +40,16 @@
{
namespace validation
{
+namespace
+{
+constexpr int max_input_tensor_dim = 3;
+} // namespace
template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
class L2NormalizeLayerValidationFixture : public framework::Fixture
{
public:
template <typename...>
- void setup(TensorShape shape, DataType data_type, DataLayout data_layout, unsigned int axis, float epsilon)
+ void setup(TensorShape shape, DataType data_type, DataLayout data_layout, int axis, float epsilon)
{
_target = compute_target(shape, data_type, data_layout, axis, epsilon);
_reference = compute_reference(shape, data_type, data_layout, axis, epsilon);
@@ -59,7 +63,7 @@
library->fill(tensor, distribution, 0);
}
- TensorType compute_target(TensorShape shape, DataType data_type, DataLayout data_layout, unsigned int axis, float epsilon)
+ TensorType compute_target(TensorShape shape, DataType data_type, DataLayout data_layout, int axis, float epsilon)
{
if(data_layout == DataLayout::NHWC)
{
@@ -93,20 +97,21 @@
return dst;
}
- SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, DataLayout data_layout, unsigned int axis, float epsilon)
+ SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, DataLayout data_layout, int axis, float epsilon)
{
+ uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
if(data_layout == DataLayout::NHWC)
{
- switch(axis)
+ switch(actual_axis)
{
case 0:
- axis = 2;
+ actual_axis = 2;
break;
case 1:
- axis = 0;
+ actual_axis = 0;
break;
case 2:
- axis = 1;
+ actual_axis = 1;
break;
default:
break;
@@ -118,7 +123,7 @@
// Fill reference
fill(src);
- return reference::l2_normalize<T>(src, axis, epsilon);
+ return reference::l2_normalize<T>(src, actual_axis, epsilon);
}
TensorType _target{};