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authorManuel Bottini <manuel.bottini@arm.com>2019-09-18 15:02:53 +0100
committerGeorgios Pinitas <georgios.pinitas@arm.com>2019-10-01 17:12:03 +0000
commit79f88e6d825402388bb79fc123ee2dfe01985bda (patch)
treedd598725afffccca79c91fd4a3e484561dfa891a
parent20c2b501f206e4db1c15c2334f9e8a1baf640a50 (diff)
downloadComputeLibrary-79f88e6d825402388bb79fc123ee2dfe01985bda.tar.gz
COMPMID-2313: Implement CL INSTANCE_NORMALIZATION function
Change-Id: If11799bef1bbb973d4287ffc1c6eb4c2a28bbf5f Signed-off-by: Manuel Bottini <manuel.bottini@arm.com> Reviewed-on: https://review.mlplatform.org/c/1989 Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
-rw-r--r--arm_compute/core/CL/CLKernels.h1
-rw-r--r--arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h85
-rw-r--r--arm_compute/runtime/CL/CLFunctions.h1
-rw-r--r--arm_compute/runtime/CL/functions/CLInstanceNormalizationLayer.h67
-rw-r--r--src/core/CL/CLKernelLibrary.cpp5
-rw-r--r--src/core/CL/cl_kernels/instance_normalization.cl181
-rw-r--r--src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp150
-rw-r--r--src/runtime/CL/functions/CLInstanceNormalizationLayer.cpp46
-rw-r--r--tests/validation/CL/InstanceNormalizationLayer.cpp134
9 files changed, 670 insertions, 0 deletions
diff --git a/arm_compute/core/CL/CLKernels.h b/arm_compute/core/CL/CLKernels.h
index e298247e2e..3d9b2c81cd 100644
--- a/arm_compute/core/CL/CLKernels.h
+++ b/arm_compute/core/CL/CLKernels.h
@@ -106,6 +106,7 @@
#include "arm_compute/core/CL/kernels/CLHeightConcatenateLayerKernel.h"
#include "arm_compute/core/CL/kernels/CLHistogramKernel.h"
#include "arm_compute/core/CL/kernels/CLIm2ColKernel.h"
+#include "arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h"
#include "arm_compute/core/CL/kernels/CLIntegralImageKernel.h"
#include "arm_compute/core/CL/kernels/CLL2NormalizeLayerKernel.h"
#include "arm_compute/core/CL/kernels/CLLKTrackerKernel.h"
diff --git a/arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h b/arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h
new file mode 100644
index 0000000000..bc016d1ceb
--- /dev/null
+++ b/arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h
@@ -0,0 +1,85 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef __ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYERKERNEL_H__
+#define __ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYERKERNEL_H__
+
+#include "arm_compute/core/CL/ICLKernel.h"
+
+namespace arm_compute
+{
+class ICLTensor;
+
+/** Interface for performing an instance normalization */
+class CLInstanceNormalizationLayerKernel : public ICLKernel
+{
+public:
+ /** Constructor */
+ CLInstanceNormalizationLayerKernel();
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ CLInstanceNormalizationLayerKernel(const CLInstanceNormalizationLayerKernel &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ CLInstanceNormalizationLayerKernel &operator=(const CLInstanceNormalizationLayerKernel &) = delete;
+ /** Default Move Constructor. */
+ CLInstanceNormalizationLayerKernel(CLInstanceNormalizationLayerKernel &&) = default;
+ /** Default move assignment operator */
+ CLInstanceNormalizationLayerKernel &operator=(CLInstanceNormalizationLayerKernel &&) = default;
+ /** Default destructor */
+ ~CLInstanceNormalizationLayerKernel() = default;
+
+ /** Set the input and output tensors.
+ *
+ * @param[in, out] input Source tensor. Data types supported: F16/F32. Data layout supported: NCHW
+ * @param[out] output Destination tensor. Data types and data layouts supported: same as @p input.
+ * @param[in] gamma (Optional) The scale scalar value applied to the normalized tensor. Defaults to 1.0
+ * @param[in] beta (Optional) The offset scalar value applied to the normalized tensor. Defaults to 0.0
+ * @param[in] epsilon (Optional) Lower bound value for the normalization. Defaults to 1e-12
+ */
+ void configure(ICLTensor *input, ICLTensor *output, float gamma = 1.0f, float beta = 0.0f, float epsilon = 1e-12f);
+
+ /** Static function to check if given info will lead to a valid configuration of @ref CLInstanceNormalizationLayer.
+ *
+ * @param[in] input Source tensor info. In case of @p output tensor = nullptr this tensor will store the result of the normalization.
+ * Data types supported: F16/F32. Data layout supported: NHWC, NCHW
+ * @param[in] output Destination tensor info. Data types and data layouts supported: same as @p input.
+ * @param[in] gamma (Optional) The scale scalar value applied to the normalized tensor. Defaults to 1.0
+ * @param[in] beta (Optional) The offset scalar value applied to the normalized tensor. Defaults to 0.0
+ * @param[in] epsilon (Optional) Lower bound value for the normalization. Defaults to 1e-12
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, float gamma = 1.0f, float beta = 0.0f, float epsilon = 1e-12f);
+
+ // Inherited methods overridden:
+ void run(const Window &window, cl::CommandQueue &queue) override;
+
+private:
+ ICLTensor *_input;
+ ICLTensor *_output;
+ float _gamma;
+ float _beta;
+ float _epsilon;
+ bool _run_in_place;
+};
+} // namespace arm_compute
+#endif /*__ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYERKERNEL_H__ */
diff --git a/arm_compute/runtime/CL/CLFunctions.h b/arm_compute/runtime/CL/CLFunctions.h
index 007ee707c5..e647819bff 100644
--- a/arm_compute/runtime/CL/CLFunctions.h
+++ b/arm_compute/runtime/CL/CLFunctions.h
@@ -90,6 +90,7 @@
#include "arm_compute/runtime/CL/functions/CLHOGMultiDetection.h"
#include "arm_compute/runtime/CL/functions/CLHarrisCorners.h"
#include "arm_compute/runtime/CL/functions/CLHistogram.h"
+#include "arm_compute/runtime/CL/functions/CLInstanceNormalizationLayer.h"
#include "arm_compute/runtime/CL/functions/CLIntegralImage.h"
#include "arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h"
#include "arm_compute/runtime/CL/functions/CLLSTMLayer.h"
diff --git a/arm_compute/runtime/CL/functions/CLInstanceNormalizationLayer.h b/arm_compute/runtime/CL/functions/CLInstanceNormalizationLayer.h
new file mode 100644
index 0000000000..e13826aeff
--- /dev/null
+++ b/arm_compute/runtime/CL/functions/CLInstanceNormalizationLayer.h
@@ -0,0 +1,67 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef __ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYER_H__
+#define __ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYER_H__
+
+#include "arm_compute/runtime/CL/ICLSimpleFunction.h"
+
+namespace arm_compute
+{
+class ICLTensor;
+
+/** Basic function to perform a Instance normalization.
+ *
+ * This function runs the following kernels:
+ * -# @ref CLInstanceNormalizationLayerKernel
+ */
+class CLInstanceNormalizationLayer : public ICLSimpleFunction
+{
+public:
+ /** Default constructor */
+ CLInstanceNormalizationLayer();
+ /** Set the input and output tensors.
+ *
+ * @param[in, out] input Source tensor. In case of @p output tensor = nullptr this tensor will store the result of the normalization.
+ * Data types supported: F16/F32. Data layout supported: NHWC, NCHW
+ * @param[out] output Destination tensor. Data types and data layouts supported: same as @p input.
+ * @param[in] gamma (Optional) The scale scalar value applied to the normalized tensor. Defaults to 1.0
+ * @param[in] beta (Optional) The offset scalar value applied to the normalized tensor. Defaults to 0.0
+ * @param[in] epsilon (Optional) Lower bound value for the normalization. Defaults to 1e-12
+ */
+ void configure(ICLTensor *input, ICLTensor *output, float gamma = 1.0f, float beta = 0.0f, float epsilon = 1e-12f);
+
+ /** Static function to check if given info will lead to a valid configuration of @ref CLInstanceNormalizationLayer.
+ *
+ * @param[in] input Source tensor info. Data types supported: F16/F32. Data layout supported: NHWC, NCHW
+ * @param[in] output Destination tensor info. Data types and data layouts supported: same as @p input.
+ * @param[in] gamma (Optional) The scale scalar value applied to the normalized tensor. Defaults to 1.0
+ * @param[in] beta (Optional) The offset scalar value applied to the normalized tensor. Defaults to 0.0
+ * @param[in] epsilon (Optional) Lower bound value for the normalization. Defaults to 1e-12
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *output, float gamma = 1.0f, float beta = 0.0f, float epsilon = 1e-12f);
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYER_H__ */
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 978e35fef6..fa5193fde2 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -371,6 +371,7 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map =
{ "init_level", "optical_flow_pyramid_lk.cl" },
{ "init_level_max", "optical_flow_pyramid_lk.cl" },
{ "init_level_max_initial_estimate", "optical_flow_pyramid_lk.cl" },
+ { "instance_normalization", "instance_normalization.cl" },
{ "integral_horizontal", "integral_image.cl" },
{ "integral_vertical", "integral_image.cl" },
{ "IYUV_to_NV12_bt709", "color_convert.cl" },
@@ -823,6 +824,10 @@ const std::map<std::string, std::string> CLKernelLibrary::_program_source_map =
#include "./cl_kernels/im2col.clembed"
},
{
+ "instance_normalization.cl",
+#include "./cl_kernels/instance_normalization.clembed"
+ },
+ {
"integral_image.cl",
#include "./cl_kernels/integral_image.clembed"
},
diff --git a/src/core/CL/cl_kernels/instance_normalization.cl b/src/core/CL/cl_kernels/instance_normalization.cl
new file mode 100644
index 0000000000..699597e8a8
--- /dev/null
+++ b/src/core/CL/cl_kernels/instance_normalization.cl
@@ -0,0 +1,181 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "helpers.h"
+
+#if defined(VEC_SIZE) && defined(DATA_TYPE) && defined(GAMMA) && defined(BETA) && defined(EPSILON) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z)
+/** This function normalizes the input 2D tensor across the first dimension with respect to mean and standard deviation of the same dimension.
+ *
+ * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16
+ * @attention Data type should be passed using the -DDATA_TYPE=data_type compile flag, e.g. -DDATA_TYPE=float
+ * @attention The scale scalar value applied to the normalized tensor should be passed using the -DGAMMA=value compile flag, e.g. -DGAMMA=1.3
+ * @attention The offset scalar value applied to the normalized tensor should be passed using the -DBETA=value compile flag, e.g. -DBETA=2.4
+ * @attention Normalization epsilon parameter should be given as a preprocessor argument with -DEPSILON=value. e.g. -DEPSILON=0.001f
+ * @attention Dimensions X, Y, and Z should be given as a preprocessor argument with -DDIM_X=value, -DDIM_Y=value, -DDIM_Z=value. e.g. -DDIM_X=6, -DDIM_Y=2, -DDIM_Z=7
+ *
+ * @param[in] input_ptr Pointer to the first source tensor. Supported data types: F16/F32
+ * @param[in] input_stride_x Stride of the first source tensor in X dimension (in bytes)
+ * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] input_stride_y Stride of the first source tensor in Y dimension (in bytes)
+ * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] input_stride_z Stride of the first source tensor in Z dimension (in bytes)
+ * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source tensor
+ * @param[out] output_ptr (Optional) Pointer to the destination tensor. Supported data types: same as @p input_ptr
+ * @param[in] output_stride_x (Optional) Stride of the destination tensor in X dimension (in bytes)
+ * @param[in] output_step_x (Optional) output_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] output_stride_y (Optional) Stride of the destination tensor in Y dimension (in bytes)
+ * @param[in] output_step_y (Optional) output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] output_stride_z (Optional) Stride of the destination tensor in Z dimension (in bytes)
+ * @param[in] output_step_z (Optional) output_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] output_offset_first_element_in_bytes (Optional) The offset of the first element in the destination tensor
+ */
+__kernel void instance_normalization(
+ TENSOR4D_DECLARATION(input)
+#ifndef IN_PLACE
+ ,
+ TENSOR4D_DECLARATION(output)
+#endif /* IN_PLACE */
+)
+{
+ DATA_TYPE sum = 0.f;
+ DATA_TYPE sum_sq = 0.f;
+
+#if defined(NHWC)
+
+ const int pc = get_global_id(0);
+ const int pn = get_global_id(2);
+ const int elements_plane = DIM_Y * DIM_Z;
+ const int elements_x_y = DIM_X * DIM_Y;
+ const int elements_x_y_z = DIM_X * DIM_Y * DIM_Z;
+
+ for(int i_w = 0; i_w < DIM_Y; ++i_w)
+ {
+ for(int i_h = 0; i_h < DIM_Z; ++i_h)
+ {
+ DATA_TYPE data = *((__global DATA_TYPE *)input_ptr + pc + i_w * DIM_X + i_h * elements_x_y + pn * elements_x_y_z);
+ sum += data;
+ sum_sq += data * data;
+ }
+ }
+
+#else // !defined(NHWC)
+ const int elements_plane = DIM_X * DIM_Y;
+ const int plane_address = get_global_id(2) * elements_plane;
+ int i = 0;
+
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ part_sum = 0.f;
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ part_sum_sq = 0.f;
+ // Calculate partial sum
+ for(; i <= (elements_plane - VEC_SIZE); i += VEC_SIZE)
+ {
+ // Load data
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_ptr + i + plane_address);
+ part_sum += data;
+ part_sum_sq += data * data;
+ }
+ // Perform reduction
+#if VEC_SIZE > 8
+ part_sum.s01234567 += part_sum.s89abcdef;
+ part_sum_sq.s01234567 += part_sum_sq.s89abcdef;
+#endif // VEC_SIZE > 8
+#if VEC_SIZE > 4
+ part_sum.s0123 += part_sum.s4567;
+ part_sum_sq.s0123 += part_sum_sq.s4567;
+#endif // VEC_SIZE > 4
+#if VEC_SIZE > 2
+ part_sum.s01 += part_sum.s23;
+ part_sum_sq.s01 += part_sum_sq.s23;
+#endif // VEC_SIZE > 2
+ part_sum.s0 += part_sum.s1;
+ part_sum_sq.s0 += part_sum_sq.s1;
+ // Left-overs loop
+ for(; i < elements_plane; ++i)
+ {
+ DATA_TYPE data = *((__global DATA_TYPE *)input_ptr + i + plane_address);
+ part_sum.s0 += data;
+ part_sum_sq.s0 += data * data;
+ }
+
+ sum = part_sum.s0;
+ sum_sq = part_sum_sq.s0;
+
+#endif // defined(NHWC)
+
+ const DATA_TYPE mean_float = ((float)sum / elements_plane);
+ const DATA_TYPE mean = (DATA_TYPE)mean_float;
+ const float var_float = ((float)sum_sq / elements_plane) - (mean_float * mean_float);
+ const float multip_float = GAMMA / sqrt(var_float + EPSILON);
+ const DATA_TYPE multip = (DATA_TYPE)multip_float;
+
+#if defined(NHWC)
+
+ for(int i_w = 0; i_w < DIM_Y; ++i_w)
+ {
+ for(int i_h = 0; i_h < DIM_Z; ++i_h)
+ {
+ __global DATA_TYPE *input_address = (__global DATA_TYPE *)input_ptr + pc + i_w * DIM_X + i_h * elements_x_y + pn * elements_x_y_z;
+#ifdef IN_PLACE
+ __global DATA_TYPE *output_address = input_address;
+#else /* !IN_PLACE */
+ __global DATA_TYPE *output_address = (__global DATA_TYPE *)output_ptr + pc + i_w * DIM_X + i_h * elements_x_y + pn * elements_x_y_z;
+#endif /* IN_PLACE */
+ *(output_address) = (*(input_address) - mean) * multip + (DATA_TYPE)BETA;
+ }
+ }
+
+#else // !defined(NHWC)
+ i = 0;
+ for(; i <= (elements_plane - VEC_SIZE); i += VEC_SIZE)
+ {
+ __global DATA_TYPE *input_address = (__global DATA_TYPE *)input_ptr + i + plane_address;
+#ifdef IN_PLACE
+ __global DATA_TYPE *output_address = input_address;
+#else /* !IN_PLACE */
+ __global DATA_TYPE *output_address = (__global DATA_TYPE *)output_ptr + i + plane_address;
+#endif /* IN_PLACE */
+
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_address);
+
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ res = (data - mean) * multip + (DATA_TYPE)BETA;
+ VSTORE(VEC_SIZE)
+ (res, 0, (__global DATA_TYPE *)output_address);
+ }
+ for(; i < elements_plane; ++i)
+ {
+ __global DATA_TYPE *input_address = (__global DATA_TYPE *)input_ptr + i + plane_address;
+#ifdef IN_PLACE
+ __global DATA_TYPE *output_address = input_address;
+#else /* !IN_PLACE */
+ __global DATA_TYPE *output_address = (__global DATA_TYPE *)output_ptr + i + plane_address;
+#endif /* IN_PLACE */
+ *(output_address) = (*(input_address) - mean) * multip + (DATA_TYPE)BETA;
+ }
+#endif // defined(NHWC)
+}
+#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(GAMMA) && defined(BETA) && defined(EPSILON) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) */
diff --git a/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
new file mode 100644
index 0000000000..a03322b61d
--- /dev/null
+++ b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
@@ -0,0 +1,150 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h"
+
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/CL/CLValidate.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Window.h"
+
+#include "support/ToolchainSupport.h"
+
+namespace arm_compute
+{
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, float gamma, float beta, float epsilon)
+{
+ ARM_COMPUTE_UNUSED(gamma);
+ ARM_COMPUTE_UNUSED(beta);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(epsilon == 0.f, "Epsilon must be different than 0");
+
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
+
+ if(output != nullptr && output->total_size() != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
+ }
+
+ return Status{};
+}
+
+std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
+{
+ // We handle the planes manually
+ Window win = calculate_max_window(*input, Steps(1));
+
+ // Output auto initialization if not yet initialized
+ auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type());
+
+ // CLInstanceNormalizationLayerKernel doesn't need padding so update_window_and_padding() can be skipped
+ Coordinates coord;
+ coord.set_num_dimensions(output->num_dimensions());
+ output->set_valid_region(ValidRegion(coord, output->tensor_shape()));
+ return std::make_pair(Status{}, win);
+}
+} // namespace
+
+CLInstanceNormalizationLayerKernel::CLInstanceNormalizationLayerKernel()
+ : _input(nullptr), _output(nullptr), _gamma(1), _beta(0), _epsilon(1e-12), _run_in_place(false)
+{
+}
+
+void CLInstanceNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *output, float gamma, float beta, float epsilon)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input);
+
+ _input = input;
+ _output = output == nullptr ? input : output;
+ _gamma = gamma;
+ _beta = beta;
+ _epsilon = epsilon;
+
+ _run_in_place = (output == nullptr) || (output == input);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(_input->info(), _output->info(), gamma, beta, epsilon));
+ const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
+
+ CLBuildOptions build_opts;
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
+ build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
+ build_opts.add_option("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0)));
+ build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1)));
+ build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2)));
+ build_opts.add_option("-DGAMMA=" + float_to_string_with_full_precision(gamma));
+ build_opts.add_option("-DBETA=" + float_to_string_with_full_precision(beta));
+ build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(epsilon));
+ build_opts.add_option_if(_run_in_place, "-DIN_PLACE");
+ build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("instance_normalization", build_opts.options()));
+
+ // Configure kernel window
+ auto win_config = validate_and_configure_window(_input->info(), _output->info());
+ ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
+ ICLKernel::configure_internal(std::get<1>(win_config));
+}
+
+Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, float gamma, float beta, float epsilon)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, gamma, beta, epsilon));
+ ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), (output == nullptr ? input->clone().get() : output->clone().get()))));
+ return Status{};
+}
+
+void CLInstanceNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
+
+ Window collapsed_window = window.collapse(window, Window::DimZ);
+
+ // We will process the planes together
+ if(_input->info()->data_layout() == DataLayout::NCHW)
+ {
+ collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1));
+ collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
+ }
+ else
+ {
+ collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1));
+ collapsed_window.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(3), 1));
+ }
+
+ unsigned int idx = 0;
+ add_4D_tensor_argument(idx, _input, collapsed_window);
+ if(!_run_in_place)
+ {
+ add_4D_tensor_argument(idx, _output, collapsed_window);
+ }
+
+ enqueue(queue, *this, collapsed_window, lws_hint());
+}
+} // namespace arm_compute \ No newline at end of file
diff --git a/src/runtime/CL/functions/CLInstanceNormalizationLayer.cpp b/src/runtime/CL/functions/CLInstanceNormalizationLayer.cpp
new file mode 100644
index 0000000000..2b0987fa2f
--- /dev/null
+++ b/src/runtime/CL/functions/CLInstanceNormalizationLayer.cpp
@@ -0,0 +1,46 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/runtime/CL/functions/CLInstanceNormalizationLayer.h"
+
+#include "arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernel.h"
+#include "arm_compute/core/Types.h"
+
+namespace arm_compute
+{
+CLInstanceNormalizationLayer::CLInstanceNormalizationLayer()
+{
+}
+
+void CLInstanceNormalizationLayer::configure(ICLTensor *input, ICLTensor *output, float gamma, float beta, float epsilon)
+{
+ auto k = arm_compute::support::cpp14::make_unique<CLInstanceNormalizationLayerKernel>();
+ k->configure(input, output, gamma, beta, epsilon);
+ _kernel = std::move(k);
+}
+
+Status CLInstanceNormalizationLayer::validate(const ITensorInfo *input, const ITensorInfo *output, float gamma, float beta, float epsilon)
+{
+ return CLInstanceNormalizationLayerKernel::validate(input, output, gamma, beta, epsilon);
+}
+} // namespace arm_compute \ No newline at end of file
diff --git a/tests/validation/CL/InstanceNormalizationLayer.cpp b/tests/validation/CL/InstanceNormalizationLayer.cpp
new file mode 100644
index 0000000000..165ab1fa9c
--- /dev/null
+++ b/tests/validation/CL/InstanceNormalizationLayer.cpp
@@ -0,0 +1,134 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/functions/CLInstanceNormalizationLayer.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/PaddingCalculator.h"
+#include "tests/datasets/ShapeDatasets.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/InstanceNormalizationLayerFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+/** Tolerance for float operations */
+AbsoluteTolerance<float> tolerance_f32(0.001f);
+AbsoluteTolerance<float> tolerance_f16(2.f);
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(InstanceNormalizationLayer)
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32), // Mismatching data type input/output
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32), // Mismatching shape input/output
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 2, DataType::F32), // Number of Input channels != 1
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::S16), // DataType != F32
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32)
+ }),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F16),
+ TensorInfo(TensorShape(256U, 64U, 32U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::S16),
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(128U, 64U, 32U, 4U), 1, DataType::F32)
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, true, true, true, true })),
+ input_info, output_info, expected)
+{
+ bool is_valid = bool(CLInstanceNormalizationLayer::validate(&input_info.clone()->set_is_resizable(false),
+ &output_info.clone()->set_is_resizable(false)
+ ));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+template <typename T>
+using CLInstanceNormalizationLayerFixture = InstanceNormalizationLayerValidationFixture<CLTensor, CLAccessor, CLInstanceNormalizationLayer, T>;
+
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLInstanceNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(datasets::Small4DShapes(),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ framework::dataset::make("InPlace", { false, true })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLInstanceNormalizationLayerFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(datasets::Large4DShapes(),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ framework::dataset::make("InPlace", { false, true })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+TEST_SUITE_END() // FP32
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLInstanceNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(datasets::SmallShapes(),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ framework::dataset::make("InPlace", { false, true })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, CLInstanceNormalizationLayerFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(datasets::LargeShapes(),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
+ framework::dataset::make("InPlace", { false, true })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+TEST_SUITE_END() // FP16
+TEST_SUITE_END() // InstanceNormalizationLayer
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute