1 files changed, 126 insertions, 28 deletions

diff --git a/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
index f9e1cbec27..b13eb16556 100644
--- a/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2020 Arm Limited.
+ * Copyright (c) 2019-2021, 2023 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -29,65 +29,154 @@
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Utils.h"
+#include "arm_compute/core/utils/StringUtils.h"
+
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
-
 #include "support/StringSupport.h"
 
 namespace arm_compute
 {
 namespace
 {
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const InstanceNormalizationLayerKernelInfo &info)
+Status validate_arguments(const ITensorInfo                          *input,
+                          const ITensorInfo                          *output,
+                          const InstanceNormalizationLayerKernelInfo &info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.epsilon == 0.f, "Epsilon must be different than 0");
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);
 
-    if(output != nullptr && output->total_size() != 0)
+    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);
-        ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(), "Input and output have different number of channels");
+        ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(),
+                                        "Input and output have different number of channels");
     }
 
     return Status{};
 }
 
-std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
+Status validate_arguments_meanvar(const ITensorInfo *input, const ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32);
+
+    if (output != nullptr && output->total_size() != 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output);
+        ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(),
+                                        "Input and output have different number of channels");
+    }
+
+    return Status{};
+}
+} // namespace
+
+CLComputeMeanVariance::CLComputeMeanVariance() : _input(nullptr), _output(nullptr)
+{
+    _type = CLKernelType::ELEMENTWISE;
+}
+
+void CLComputeMeanVariance::configure(const CLCompileContext &compile_context,
+                                      ICLTensor              *input,
+                                      ICLTensor              *output,
+                                      bool                    use_mixed_precision)
 {
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input);
+    auto padding_info = get_padding_info({input, output});
+
+    _input  = input;
+    _output = output == nullptr ? input : output;
+
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_meanvar(_input->info(), _output->info()));
+    const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
+
+    CLBuildOptions build_opts;
+    build_opts.add_option("-DINTERNAL_DATA_TYPE=" +
+                          (use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
+    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_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC");
+    // Create kernel
+    _kernel = create_kernel(compile_context, "compute_mean_var", build_opts.options());
+
     // We handle the planes manually
-    Window win = calculate_max_window(*input, Steps(1));
+    Window             win           = calculate_max_window(*(input->info()), Steps(1));
+    const auto         data_layout   = input->info()->data_layout();
+    const unsigned int channel_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+    const unsigned int batches_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
+    const unsigned int input_channel = input->info()->dimension(channel_idx);
+    const unsigned int input_batches = input->info()->dimension(batches_idx);
+    const TensorShape  out_shape(input_channel, 2u, input_batches);
 
     // Output auto initialization if not yet initialized
-    auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type());
+    if (use_mixed_precision)
+    {
+        auto_init_if_empty(*_output->info(), out_shape, 1, DataType::F32);
+    }
+    else
+    {
+        auto_init_if_empty(*_output->info(), out_shape, 1, input->info()->data_type());
+    }
+    ICLKernel::configure_internal(win);
+    ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
+}
 
-    // 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);
+Status CLComputeMeanVariance::validate(const ITensorInfo *input, const ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_meanvar(input, output));
+    return Status{};
 }
-} // namespace
 
-CLInstanceNormalizationLayerKernel::CLInstanceNormalizationLayerKernel()
-    : _input(nullptr), _output(nullptr), _run_in_place(false)
+void CLComputeMeanVariance::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::DimZ, Window::Dimension(0, 1, 1));
+        collapsed_window.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(3), 1));
+    }
+    unsigned int idx = 0;
+    add_4D_tensor_argument(idx, _input, collapsed_window);
+    add_3D_tensor_argument(idx, _output, collapsed_window);
+
+    enqueue(queue, *this, collapsed_window, lws_hint());
 }
 
-void CLInstanceNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *output, const InstanceNormalizationLayerKernelInfo &info)
+CLInstanceNormalizationLayerKernel::CLInstanceNormalizationLayerKernel()
+    : _input(nullptr), _output(nullptr), _mean(nullptr), _run_in_place(false)
 {
-    configure(CLKernelLibrary::get().get_compile_context(), input, output, info);
+    _type = CLKernelType::ELEMENTWISE;
 }
 
-void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const InstanceNormalizationLayerKernelInfo &info)
+void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext                     &compile_context,
+                                                   ICLTensor                                  *input,
+                                                   ICLTensor                                  *mean_var,
+                                                   ICLTensor                                  *output,
+                                                   const InstanceNormalizationLayerKernelInfo &info)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input);
-    auto padding_info = get_padding_info({ input, output });
+    auto padding_info = get_padding_info({input, output});
 
     _input  = input;
     _output = output == nullptr ? input : output;
+    _mean   = mean_var;
 
     _run_in_place = (output == nullptr) || (output == input);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(_input->info(), _output->info(), info));
@@ -95,7 +184,9 @@ void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compi
 
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
-    build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (info.use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type())));
+    build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (info.use_mixed_precision
+                                                         ? "float"
+                                                         : 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)));
@@ -110,16 +201,21 @@ void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compi
     _kernel = create_kernel(compile_context, "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));
+    Window win = calculate_max_window(*input->info(), Steps(1));
+    if (output != nullptr)
+    {
+        auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type());
+    }
+
+    ICLKernel::configure_internal(win);
     ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
 }
 
-Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const InstanceNormalizationLayerKernelInfo &info)
+Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo                          *input,
+                                                    const ITensorInfo                          *output,
+                                                    const InstanceNormalizationLayerKernelInfo &info)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, info));
-    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{};
 }
 
@@ -131,7 +227,7 @@ void CLInstanceNormalizationLayerKernel::run(const Window &window, cl::CommandQu
     Window collapsed_window = window.collapse(window, Window::DimZ);
 
     // We will process the planes together
-    if(_input->info()->data_layout() == DataLayout::NCHW)
+    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));
@@ -144,7 +240,9 @@ void CLInstanceNormalizationLayerKernel::run(const Window &window, cl::CommandQu
 
     unsigned int idx = 0;
     add_4D_tensor_argument(idx, _input, collapsed_window);
-    if(!_run_in_place)
+    add_3D_tensor_argument(idx, _mean, collapsed_window);
+
+    if (!_run_in_place)
     {
         add_4D_tensor_argument(idx, _output, collapsed_window);
     }