This commit makes ackend acl_cl to support InstanceNorm op.
Signed-off-by: jiseob.jang <jiseob.jang@samsung.com>
--- /dev/null
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ * 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_CLINSTANCENORMALIZATIONLAYERKERNELEX_H__
+#define __ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYERKERNELEX_H__
+
+#include "arm_compute/core/CL/ICLKernel.h"
+
+namespace arm_compute
+{
+class ICLTensor;
+
+/** Interface for performing an instance normalization */
+class CLInstanceNormalizationLayerKernelEx : public ICLKernel
+{
+public:
+ /** Constructor */
+ CLInstanceNormalizationLayerKernelEx();
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ CLInstanceNormalizationLayerKernelEx(const CLInstanceNormalizationLayerKernelEx &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers) */
+ CLInstanceNormalizationLayerKernelEx &
+ operator=(const CLInstanceNormalizationLayerKernelEx &) = delete;
+ /** Default Move Constructor. */
+ CLInstanceNormalizationLayerKernelEx(CLInstanceNormalizationLayerKernelEx &&) = default;
+ /** Default move assignment operator */
+ CLInstanceNormalizationLayerKernelEx &
+ operator=(CLInstanceNormalizationLayerKernelEx &&) = default;
+ /** Default destructor */
+ ~CLInstanceNormalizationLayerKernelEx() = 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 tensor applied to the normalized tensor. Defaults
+ * to nullptr
+ * @param[in] beta (Optional) The offset tensor applied to the normalized tensor. Defaults
+ * to nullptr
+ * @param[in] epsilon (Optional) Lower bound value for the normalization. Defaults to 1e-12
+ */
+ void configure(ICLTensor *input, ICLTensor *output, ICLTensor *gamma = nullptr,
+ ICLTensor *beta = nullptr, float epsilon = 1e-12f);
+
+ /** Static function to check if given info will lead to a valid configuration of @ref
+ * CLInstanceNormalizationLayerEx.
+ *
+ * @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 tensor applied to the normalized tensor. Defaults to
+ * nullptr
+ * @param[in] beta (Optional) The offset tensor applied to the normalized tensor. Defaults to
+ * nullptr
+ * @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,
+ const ITensorInfo *gamma = nullptr, const ITensorInfo *beta = nullptr,
+ float epsilon = 1e-12f);
+
+ // Inherited methods overridden:
+ void run(const Window &window, cl::CommandQueue &queue) override;
+
+private:
+ ICLTensor *_input;
+ ICLTensor *_output;
+ ICLTensor *_gamma;
+ ICLTensor *_beta;
+ float _epsilon;
+ bool _run_in_place;
+};
+} // namespace arm_compute
+#endif /*__ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYERKERNELEX_H__ */
#include <arm_compute/runtime/CL/functions/CLFullyConnectedReshapingLayer.h>
#include <arm_compute/runtime/CL/functions/CLGatherEx.h>
#include <arm_compute/runtime/CL/functions/CLHashtableLookup.h>
+#include <arm_compute/runtime/CL/functions/CLInstanceNormalizationLayerEx.h>
#include <arm_compute/runtime/CL/functions/CLLogicalNot.h>
#include <arm_compute/runtime/CL/functions/CLNeg.h>
#include <arm_compute/runtime/CL/functions/CLPixelWiseDivision.h>
--- /dev/null
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ * 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_CLINSTANCENORMALIZATIONLAYEREX_H__
+#define __ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYEREX_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 CLInstanceNormalizationLayerKernelEx
+ */
+class CLInstanceNormalizationLayerEx : public ICLSimpleFunction
+{
+public:
+ /** Default constructor */
+ CLInstanceNormalizationLayerEx();
+ /** 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 tensor applied to the normalized tensor. Defaults
+ * to nullptr
+ * @param[in] beta (Optional) The offset tensor applied to the normalized tensor. Defaults
+ * to nullptr
+ * @param[in] epsilon (Optional) Lower bound value for the normalization. Defaults to 1e-12
+ */
+ void configure(ICLTensor *input, ICLTensor *output, ICLTensor *gamma = nullptr,
+ ICLTensor *beta = nullptr, float epsilon = 1e-12f);
+
+ /** Static function to check if given info will lead to a valid configuration of @ref
+ * CLInstanceNormalizationLayerEx.
+ *
+ * @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 tensor applied to the normalized tensor. Defaults to
+ * nullptr
+ * @param[in] beta (Optional) The offset tensor applied to the normalized tensor. Defaults to
+ * nullptr
+ * @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,
+ const ITensorInfo *gamma = nullptr, const ITensorInfo *beta = nullptr,
+ float epsilon = 1e-12f);
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_CLINSTANCENORMALIZATIONLAYEREX_H__ */
{"gather_ex_1d", "gather_ex.cl"},
{"gather_ex_1d_out", "gather_ex.cl"},
{"hashtable_lookup", "hashtable_lookup.cl"},
+ {"instance_normalization_ex", "instance_normalization_ex.cl"},
{"neg_tensor", "neg_tensor.cl"},
{"permute_generic", "permute_ex.cl"},
{"pixelwise_mul_qasymm8", "pixelwise_mul_quantized.cl"},
#include "./cl_kernels/helpers_asymm.hembed"
},
{
+ "instance_normalization_ex.cl",
+#include "./cl_kernels/instance_normalization_ex.clembed"
+ },
+ {
"binary_logical_op.cl",
#include "./cl_kernels/binary_logical_op.clembed"
},
--- /dev/null
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ * 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(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 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
+ * @param[in] gamma_ptr (Optional) Pointer to the gamma tensor.
+ * Supported data types: same as @p input_ptr
+ * @param[in] gamma_stride_x (Optional) Stride of the gamma tensor in X
+ * dimension (in bytes)
+ * @param[in] gamma_step_x (Optional) output_stride_x * number of elements
+ * along X processed per workitem(in bytes)
+ * @param[in] gamma_offset_first_element_in_bytes (Optional) The offset of the first element in
+ * the gamma tensor
+ * @param[in] beta_ptr (Optional) Pointer to the beta tensor. Supported
+ * data types: same as @p input_ptr
+ * @param[in] beta_stride_x (Optional) Stride of the beta tensor in X
+ * dimension (in bytes)
+ * @param[in] beta_step_x (Optional) output_stride_x * number of elements
+ * along X processed per workitem(in bytes)
+ * @param[in] beta_offset_first_element_in_bytes (Optional) The offset of the first element in
+ * the beta tensor
+ */
+__kernel void instance_normalization_ex(TENSOR4D_DECLARATION(input),
+#ifndef IN_PLACE
+ TENSOR4D_DECLARATION(output)
+#endif /* IN_PLACE */
+#ifdef GAMMA
+ ,
+ VECTOR_DECLARATION(gamma)
+#endif // GAMMA
+#ifdef BETA
+ ,
+ VECTOR_DECLARATION(beta)
+#endif // BETA
+ )
+{
+ Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, 0);
+#ifndef IN_PLACE
+ Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0);
+#endif /* IN_PLACE */
+
+ float sum = 0.f;
+ float sum_sq = 0.f;
+
+#if defined(NHWC)
+
+ const int ch = get_global_id(0); // Current channel
+ const int batch = get_global_id(2); // Current batch
+ const int elements_plane = 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)
+ {
+ float data = (float)*((__global DATA_TYPE *)tensor4D_offset(&in, ch, i_w, i_h, batch));
+ sum += data;
+ sum_sq += data * data;
+ }
+ }
+
+#else // !defined(NHWC)
+ const int ch = get_global_id(2) % DIM_Z; // Current channel
+ const int batch = get_global_id(2) / DIM_Z; // Current batch
+ const int elements_plane = DIM_X * DIM_Y;
+
+ 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 (int y = 0; y < DIM_Y; ++y)
+ {
+ int x = 0;
+ for (; x <= (DIM_X - VEC_SIZE); x += VEC_SIZE)
+ {
+ // Load data
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch));
+ part_sum += data;
+ part_sum_sq += data * data;
+ }
+ // Left-overs loop
+ for (; x < DIM_X; ++x)
+ {
+ DATA_TYPE data = *((__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch));
+ part_sum.s0 += data;
+ part_sum_sq.s0 += 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;
+
+ sum = (float)part_sum.s0;
+ sum_sq = (float)part_sum_sq.s0;
+
+#endif // defined(NHWC)
+
+ const float mean_float = (sum / elements_plane);
+ const DATA_TYPE mean = (DATA_TYPE)mean_float;
+ const float var_float = (sum_sq / elements_plane) - (mean_float * mean_float);
+#if defined(GAMMA)
+ const float multip_float = *((__global DATA_TYPE *)gamma_ptr + ch) / sqrt(var_float + EPSILON);
+ const DATA_TYPE multip = (DATA_TYPE)multip_float;
+#else // !defined(GAMMA)
+ const DATA_TYPE multip = (DATA_TYPE)0;
+#endif // defined(GAMMA)
+#if defined(BETA)
+ const DATA_TYPE beta = *((__global DATA_TYPE *)beta_ptr + ch);
+#else // !defined(BETA)
+ const DATA_TYPE beta = 0;
+#endif // defined(BETA)
+
+#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 *)tensor4D_offset(&in, ch, i_w, i_h, batch);
+#ifdef IN_PLACE
+ __global DATA_TYPE *output_address = input_address;
+#else /* !IN_PLACE */
+ __global DATA_TYPE *output_address =
+ (__global DATA_TYPE *)tensor4D_offset(&out, ch, i_w, i_h, batch);
+#endif /* IN_PLACE */
+ *(output_address) = (*(input_address)-mean) * multip + beta;
+ }
+ }
+
+#else // !defined(NHWC)
+ for (int y = 0; y < DIM_Y; ++y)
+ {
+ int x = 0;
+ for (; x <= (DIM_X - VEC_SIZE); x += VEC_SIZE)
+ {
+ __global DATA_TYPE *input_address =
+ (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch);
+#ifdef IN_PLACE
+ __global DATA_TYPE *output_address = input_address;
+#else /* !IN_PLACE */
+ __global DATA_TYPE *output_address =
+ (__global DATA_TYPE *)tensor4D_offset(&out, x, y, ch, batch);
+#endif /* IN_PLACE */
+
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ data = VLOAD(VEC_SIZE)(0, input_address);
+
+ VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
+ res = (data - mean) * multip + beta;
+ VSTORE(VEC_SIZE)
+ (res, 0, output_address);
+ }
+ // Left-overs loop
+ for (; x < DIM_X; ++x)
+ {
+ __global DATA_TYPE *input_address =
+ (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch);
+#ifdef IN_PLACE
+ __global DATA_TYPE *output_address = input_address;
+#else /* !IN_PLACE */
+ __global DATA_TYPE *output_address =
+ (__global DATA_TYPE *)tensor4D_offset(&out, x, y, ch, batch);
+#endif /* IN_PLACE */
+ *(output_address) = (*(input_address)-mean) * multip + beta;
+ }
+ }
+#endif // defined(NHWC)
+}
+#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(EPSILON) && defined(DIM_X) && \
+ defined(DIM_Y) && defined(DIM_Z) */
--- /dev/null
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ * 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/CLInstanceNormalizationLayerKernelEx.h"
+
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLKernelLibraryEx.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,
+ const ITensorInfo *gamma, const ITensorInfo *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_NOT_IN(input, 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);
+ 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)
+{
+ // 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());
+
+ // CLInstanceNormalizationLayerKernelEx 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
+
+CLInstanceNormalizationLayerKernelEx::CLInstanceNormalizationLayerKernelEx()
+ : _input(nullptr), _output(nullptr), _gamma(nullptr), _beta(nullptr), _epsilon(1e-12),
+ _run_in_place(false)
+{
+}
+
+void CLInstanceNormalizationLayerKernelEx::configure(ICLTensor *input, ICLTensor *output,
+ ICLTensor *gamma, ICLTensor *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 ? gamma->info() : nullptr,
+ beta ? beta->info() : nullptr, 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("-DEPSILON=" + float_to_string_with_full_precision(epsilon));
+ build_opts.add_option_if(gamma, "-DGAMMA");
+ build_opts.add_option_if(beta, "-DBETA");
+ 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>(
+ CLKernelLibraryEx::get().create_kernel("instance_normalization_ex", 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 CLInstanceNormalizationLayerKernelEx::validate(const ITensorInfo *input,
+ const ITensorInfo *output,
+ const ITensorInfo *gamma,
+ const ITensorInfo *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 CLInstanceNormalizationLayerKernelEx::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));
+ }
+
+ Window vec_window;
+ vec_window.set(Window::DimX, Window::Dimension(0, 0, 0));
+
+ unsigned int idx = 0;
+ add_4D_tensor_argument(idx, _input, collapsed_window);
+ if (!_run_in_place)
+ {
+ add_4D_tensor_argument(idx, _output, collapsed_window);
+ }
+ if (_gamma)
+ {
+ add_1D_tensor_argument(idx, _gamma, vec_window);
+ }
+ if (_beta)
+ {
+ add_1D_tensor_argument(idx, _beta, vec_window);
+ }
+
+ enqueue(queue, *this, collapsed_window, lws_hint());
+}
+} // namespace arm_compute
--- /dev/null
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ * 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/CLInstanceNormalizationLayerEx.h"
+
+#include "arm_compute/core/CL/kernels/CLInstanceNormalizationLayerKernelEx.h"
+#include "arm_compute/core/Types.h"
+
+namespace arm_compute
+{
+CLInstanceNormalizationLayerEx::CLInstanceNormalizationLayerEx() {}
+
+void CLInstanceNormalizationLayerEx::configure(ICLTensor *input, ICLTensor *output,
+ ICLTensor *gamma, ICLTensor *beta, float epsilon)
+{
+ auto k = arm_compute::support::cpp14::make_unique<CLInstanceNormalizationLayerKernelEx>();
+ k->configure(input, output, gamma, beta, epsilon);
+ _kernel = std::move(k);
+}
+
+Status CLInstanceNormalizationLayerEx::validate(const ITensorInfo *input, const ITensorInfo *output,
+ const ITensorInfo *gamma, const ITensorInfo *beta,
+ float epsilon)
+{
+ return CLInstanceNormalizationLayerKernelEx::validate(input, output, gamma, beta, epsilon);
+}
+} // namespace arm_compute
_execution_builder->append(std::move(acl_fn));
}
+void KernelGenerator::visit(const model::operation::InstanceNorm &node)
+{
+ const auto ofm_index{node.getOutputs().at(0)};
+ const auto ifm_index{node.getInputs().at(model::operation::InstanceNorm::Input::INPUT)};
+ const auto gamma_index{node.getInputs().at(model::operation::InstanceNorm::Input::GAMMA)};
+ const auto beta_index{node.getInputs().at(model::operation::InstanceNorm::Input::BETA)};
+
+ auto ofm_alloc = _tensor_builder->at(ofm_index).get();
+ auto ifm_alloc = _tensor_builder->at(ifm_index).get();
+ auto gamma_alloc = _tensor_builder->at(gamma_index).get();
+ auto beta_alloc = _tensor_builder->at(beta_index).get();
+ auto epsilon = node.param().epsilon;
+ auto activation = node.param().activation;
+
+ auto fn = nnfw::cpp14::make_unique<::arm_compute::CLInstanceNormalizationLayerEx>();
+
+ fn->configure(ifm_alloc->handle(), ofm_alloc->handle(), gamma_alloc->handle(),
+ beta_alloc->handle(), epsilon);
+
+ auto acl_fn = asAclFunction(std::move(fn));
+
+ _execution_builder->append(std::move(acl_fn));
+
+ ActivationBuilder{*_execution_builder}.append(activation, ofm_alloc->handle());
+}
+
void KernelGenerator::visit(const model::operation::Logistic &node)
{
const auto ofm_index{node.getOutputs().at(0)};
void visit(const model::operation::Cast &) override;
void visit(const model::operation::Div &) override;
void visit(const model::operation::Exp &) override;
+ void visit(const model::operation::InstanceNorm &) override;
void visit(const model::operation::Logistic &) override;
void visit(const model::operation::ReduceMax &) override;
void visit(const model::operation::Comparison &) override;
void ShapeFixer::visit(const model::operation::Exp &) { /* DO NOTHING */}
+void ShapeFixer::visit(const model::operation::InstanceNorm &) { /* DO NOTHING */}
+
void ShapeFixer::visit(const model::operation::Logistic &) { /* DO NOTHING */}
void ShapeFixer::visit(const model::operation::LogicalAnd &node)
void visit(const model::operation::Cast &) override;
void visit(const model::operation::Div &) override;
void visit(const model::operation::Exp &) override;
+ void visit(const model::operation::InstanceNorm &) override;
void visit(const model::operation::Logistic &) override;
void visit(const model::operation::ReduceMax &) override;
void visit(const model::operation::Comparison &) override;
std::unordered_map<model::OpCode, backend::Backend *> op_type_map;
// By default, Custom uses cpu backend
op_type_map[model::OpCode::Custom] = backend::BackendManager::get().get("cpu");
+
#define OP(InternalName) \
{ \
const auto &backend_str = util::getConfigString(util::config::OP_BACKEND_##InternalName); \
projects / platform / core / ml / nnfw.git / commitdiff