aboutsummaryrefslogtreecommitdiff
path: root/src/core
diff options
context:
space:
mode:
Diffstat (limited to 'src/core')
-rw-r--r--src/core/NEON/NEKernels.h1
-rw-r--r--src/core/NEON/kernels/NESoftmaxLayerKernel.h141
-rw-r--r--src/core/cpu/kernels/CpuSoftmaxKernel.cpp (renamed from src/core/NEON/kernels/NESoftmaxLayerKernel.cpp)184
-rw-r--r--src/core/cpu/kernels/CpuSoftmaxKernel.h107
-rw-r--r--src/core/cpu/kernels/softmax/impl/NEON/list.h (renamed from src/core/NEON/kernels/softmax/impl/NEON/list.h)4
-rw-r--r--src/core/cpu/kernels/softmax/impl/SVE/list.h (renamed from src/core/NEON/kernels/softmax/impl/SVE/list.h)0
6 files changed, 207 insertions, 230 deletions
diff --git a/src/core/NEON/NEKernels.h b/src/core/NEON/NEKernels.h
index c636e5b3be..66309f9296 100644
--- a/src/core/NEON/NEKernels.h
+++ b/src/core/NEON/NEKernels.h
@@ -117,7 +117,6 @@
#include "src/core/NEON/kernels/NESobel3x3Kernel.h"
#include "src/core/NEON/kernels/NESobel5x5Kernel.h"
#include "src/core/NEON/kernels/NESobel7x7Kernel.h"
-#include "src/core/NEON/kernels/NESoftmaxLayerKernel.h"
#include "src/core/NEON/kernels/NESpaceToBatchLayerKernel.h"
#include "src/core/NEON/kernels/NESpaceToDepthLayerKernel.h"
#include "src/core/NEON/kernels/NEStackLayerKernel.h"
diff --git a/src/core/NEON/kernels/NESoftmaxLayerKernel.h b/src/core/NEON/kernels/NESoftmaxLayerKernel.h
deleted file mode 100644
index 70e2417fc2..0000000000
--- a/src/core/NEON/kernels/NESoftmaxLayerKernel.h
+++ /dev/null
@@ -1,141 +0,0 @@
-/*
- * Copyright (c) 2017-2021 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_NESOFTMAXLAYERKERNEL_H
-#define ARM_COMPUTE_NESOFTMAXLAYERKERNEL_H
-
-#include "src/core/NEON/INEKernel.h"
-#include "src/core/NEON/INESimpleKernel.h"
-
-namespace arm_compute
-{
-class ITensor;
-
-/** Interface for the identifying the max value of 1D Logits */
-class NELogits1DMaxKernel : public INESimpleKernel
-{
-public:
- const char *name() const override
- {
- return "NELogits1DMaxKernel";
- }
- /** Default constructor */
- NELogits1DMaxKernel();
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NELogits1DMaxKernel(const NELogits1DMaxKernel &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NELogits1DMaxKernel &operator=(const NELogits1DMaxKernel &) = delete;
- /** Allow instances of this class to be moved */
- NELogits1DMaxKernel(NELogits1DMaxKernel &&) = default;
- /** Allow instances of this class to be moved */
- NELogits1DMaxKernel &operator=(NELogits1DMaxKernel &&) = default;
- /** Default destructor */
- ~NELogits1DMaxKernel() = default;
- /** Set the input and output tensors.
- *
- * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
- * @param[out] output Destination tensor. Data types supported: same as @p input
- */
- void configure(const ITensor *input, ITensor *output);
- /** Static function to check if given info will lead to a valid configuration of @ref NELogits1DMaxKernel
- *
- * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
- * @param[in] output Destination tensor. Data types supported: same as @p input
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input, const ITensorInfo *output);
-
- // Inherited methods overridden:
- void run(const Window &window, const ThreadInfo &info) override;
- BorderSize border_size() const override;
-
-private:
- BorderSize _border_size;
-};
-
-/** Interface for softmax computation for QASYMM8 with pre-computed max. */
-template <bool IS_LOG = false>
-class NELogits1DSoftmaxKernel : public INEKernel
-{
-public:
- const char *name() const override
- {
- if(IS_LOG)
- {
- return "NELogits1DSoftmaxKernel";
- }
- else
- {
- return "NELogits1DLogSoftmaxKernel";
- }
- }
- /** Default constructor */
- NELogits1DSoftmaxKernel();
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NELogits1DSoftmaxKernel(const NELogits1DSoftmaxKernel &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers) */
- NELogits1DSoftmaxKernel &operator=(const NELogits1DSoftmaxKernel &) = delete;
- /** Allow instances of this class to be moved */
- NELogits1DSoftmaxKernel(NELogits1DSoftmaxKernel &&) = default;
- /** Allow instances of this class to be moved */
- NELogits1DSoftmaxKernel &operator=(NELogits1DSoftmaxKernel &&) = default;
- /** Default destructor */
- ~NELogits1DSoftmaxKernel() = default;
- /** Set the input and output tensors.
- *
- * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
- * @param[in] max Max values tensor. Same shape as input with dimension 0 set to 1.
- * Data types supported: same as @p input.
- * @param[out] output Destination tensor. Data types supported: same as @p input.
- * @param[in] beta A scaling factor for the exponent.
- *
- * @param tmp Auxiliary tensor. Must be type F32 and same shape as the input.
- */
- void configure(const ITensor *input, const ITensor *max, ITensor *output, const float beta, ITensor *tmp);
- /** Static function to check if given info will lead to a valid configuration of @ref NELogits1DSoftmaxKernel
- *
- * @param[in] input Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
- * @param[in] max Max values tensor info. Same shape as input with dimension 0 set to 1.
- * Data types supported: same as @p input.
- * @param[in] output Destination tensor info. Data types supported: same as @p input.
- * @param[in] beta A scaling factor for the exponent.
- * @param[in] tmp Tensor info of auxiliary. Must be type F32 and same shape as the input.
- *
- * @return a status
- */
- static Status validate(const ITensorInfo *input, const ITensorInfo *max,
- const ITensorInfo *output, const float beta, const ITensorInfo *tmp);
-
- // Inherited methods overridden:
- void run(const Window &window, const ThreadInfo &info) override;
-
-private:
- const ITensor *_input;
- const ITensor *_max;
- ITensor *_output;
- float _beta;
- ITensor *_tmp; //Temporary. Used internally
-};
-} // namespace arm_compute
-#endif /*ARM_COMPUTE_NESOFTMAXLAYERKERNEL_H */
diff --git a/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp b/src/core/cpu/kernels/CpuSoftmaxKernel.cpp
index fe09f1ec59..a8542b6be1 100644
--- a/src/core/NEON/kernels/NESoftmaxLayerKernel.cpp
+++ b/src/core/cpu/kernels/CpuSoftmaxKernel.cpp
@@ -21,7 +21,7 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
-#include "src/core/NEON/kernels/NESoftmaxLayerKernel.h"
+#include "src/core/cpu/kernels/CpuSoftmaxKernel.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
@@ -33,12 +33,16 @@
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
-#include "src/core/NEON/kernels/softmax/impl/NEON/list.h"
-#include "src/core/NEON/kernels/softmax/impl/SVE/list.h"
#include "src/core/common/Registrars.h"
+#include "src/core/cpu/kernels/softmax/impl/NEON/list.h"
+#include "src/core/cpu/kernels/softmax/impl/SVE/list.h"
namespace arm_compute
{
+namespace cpu
+{
+namespace kernels
+{
namespace
{
struct SoftmaxSelectorData
@@ -208,98 +212,90 @@ Status validate_arguments_logits_1d_max(const ITensorInfo &input, const ITensorI
} // namespace
-NELogits1DMaxKernel::NELogits1DMaxKernel()
- : _border_size()
+CpuLogits1DMaxKernel::CpuLogits1DMaxKernel()
{
}
-BorderSize NELogits1DMaxKernel::border_size() const
+void CpuLogits1DMaxKernel::configure(const ITensorInfo *src, ITensorInfo *dst)
{
- return _border_size;
-}
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
-void NELogits1DMaxKernel::configure(const ITensor *input, ITensor *output)
-{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_ERROR_ON_NULLPTR(input->info(), output->info());
// Perform validation step
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_logits_1d_max(*input->info(), *output->info()));
- // Configure kernel window
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_logits_1d_max(*src, *dst));
// Softmax across the x dimension
- const TensorShape output_shape = TensorShape(input->info()->tensor_shape()).set(0, 1);
+ const TensorShape output_shape = TensorShape(src->tensor_shape()).set(0, 1);
// Output auto initialization if not yet initialized
- auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->quantization_info());
+ auto_init_if_empty(*dst, output_shape, 1, src->data_type(), src->quantization_info());
- Window win = calculate_max_window(*input->info(), Steps());
+ Window win = calculate_max_window(*src, Steps());
Coordinates coord;
- coord.set_num_dimensions(output->info()->num_dimensions());
- output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));
-
- _input = input;
- _output = output;
-
- const int input_width = input->info()->valid_region().shape.x();
- const int num_elems_processed_per_iteration = 16U / data_size_from_type(input->info()->data_type());
- const int num_elems_read_per_iteration = ceil_to_multiple(input_width, num_elems_processed_per_iteration);
+ coord.set_num_dimensions(dst->num_dimensions());
+ dst->set_valid_region(ValidRegion(coord, dst->tensor_shape()));
- _border_size = BorderSize(0, num_elems_read_per_iteration - input_width, 0, 0);
-
- INEKernel::configure(win);
+ ICpuKernel::configure(win);
}
-Status NELogits1DMaxKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
+Status CpuLogits1DMaxKernel::validate(const ITensorInfo *src, const ITensorInfo *dst)
{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_logits_1d_max(*input, *output));
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_logits_1d_max(*src, *dst));
return Status{};
}
-void NELogits1DMaxKernel::run(const Window &window, const ThreadInfo &info)
+void CpuLogits1DMaxKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
- ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
+
+ const auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
+ auto dst = tensors.get_tensor(TensorType::ACL_DST);
- const auto *uk = get_implementation_logits_max(SoftmaxSelectorData{ _input->info()->data_type() });
- uk->ukernel(_input, _output, window);
+ const auto *uk = get_implementation_logits_max(SoftmaxSelectorData{ src->info()->data_type() });
+ uk->ukernel(src, dst, window);
+}
+
+const char *CpuLogits1DMaxKernel::name() const
+{
+ return "CpuLogits1DMaxKernel";
}
namespace
{
-Status validate_arguments_logits_softmax(const ITensorInfo &input, const ITensorInfo &max,
- const ITensorInfo &output, const float beta, const ITensorInfo &tmp, bool is_log)
+Status validate_arguments_logits_softmax(const ITensorInfo &src, const ITensorInfo &max,
+ const ITensorInfo &dst, const float beta, const ITensorInfo &tmp, bool is_log)
{
ARM_COMPUTE_UNUSED(beta);
// Check input
- ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&input);
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
+ ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(&src);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
- const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input.data_type());
+ const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(src.data_type());
// Check max
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input, &max);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(TensorShape(input.tensor_shape()).set(0, 1), max.tensor_shape());
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(&input, &max);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src, &max);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(TensorShape(src.tensor_shape()).set(0, 1), max.tensor_shape());
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(&src, &max);
// Check output if configured
- if(output.total_size() != 0)
+ if(dst.total_size() != 0)
{
- const QuantizationInfo output_quantization = is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(input.data_type(), is_log) : output.quantization_info();
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&input, &output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&input, &output);
- ARM_COMPUTE_RETURN_ERROR_ON(output.quantization_info() != output_quantization);
+ const QuantizationInfo output_quantization = is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(src.data_type(), is_log) : dst.quantization_info();
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(&src, &dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&src, &dst);
+ ARM_COMPUTE_RETURN_ERROR_ON(dst.quantization_info() != output_quantization);
}
// Check tmp if configured
if(tmp.total_size() != 0)
{
- const DataType tmp_data_type = is_quantized_asymmetric ? DataType::F32 : input.data_type();
+ const DataType tmp_data_type = is_quantized_asymmetric ? DataType::F32 : src.data_type();
ARM_COMPUTE_RETURN_ERROR_ON(tmp.data_type() != tmp_data_type);
// We could potentially reduce tmp memory if we could predict or make an assumption
// on the maximum number of threads that will run in parallel.
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&input, &tmp);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&src, &tmp);
}
return Status{};
@@ -307,74 +303,90 @@ Status validate_arguments_logits_softmax(const ITensorInfo &input, const ITensor
} // namespace
template <bool IS_LOG>
-NELogits1DSoftmaxKernel<IS_LOG>::NELogits1DSoftmaxKernel()
- : _input(nullptr), _max(nullptr), _output(nullptr), _beta(1.0f), _tmp(nullptr)
+CpuLogits1DSoftmaxKernel<IS_LOG>::CpuLogits1DSoftmaxKernel()
+ : _beta(1.0f)
{
}
template <bool IS_LOG>
-void NELogits1DSoftmaxKernel<IS_LOG>::configure(const ITensor *input, const ITensor *max, ITensor *output, const float beta, ITensor *tmp)
+void CpuLogits1DSoftmaxKernel<IS_LOG>::configure(const ITensorInfo *src, const ITensorInfo *max, ITensorInfo *dst, const float beta, ITensorInfo *tmp)
{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, max, output, tmp);
- ARM_COMPUTE_ERROR_ON_NULLPTR(input->info(), max->info(), output->info(), tmp->info());
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src, max, dst, tmp);
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src, max, dst, tmp);
// Perform validation step
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_logits_softmax(*input->info(), *max->info(), *output->info(), beta, *tmp->info(), IS_LOG));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_logits_softmax(*src, *max, *dst, beta, *tmp, IS_LOG));
+
+ _beta = beta;
// Configure kernel window
- const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(input->info()->data_type());
+ const bool is_quantized_asymmetric = is_data_type_quantized_asymmetric(src->data_type());
// Output auto initialization if not yet initialized
- const QuantizationInfo output_quantization = is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(input->info()->data_type(), IS_LOG) : output->info()->quantization_info();
- auto_init_if_empty(*output->info(), TensorInfo(*input->info()).set_quantization_info(output_quantization).reset_padding());
+ const QuantizationInfo output_quantization = is_quantized_asymmetric ? arm_compute::get_softmax_output_quantization_info(src->data_type(), IS_LOG) : dst->quantization_info();
+ auto_init_if_empty(*dst, TensorInfo(*src).set_quantization_info(output_quantization).reset_padding());
// Tmp auto initialization if not yet initialized
- const DataType tmp_data_type = is_quantized_asymmetric ? DataType::F32 : input->info()->data_type();
- auto_init_if_empty(*tmp->info(), TensorInfo(*input->info()).set_data_type(tmp_data_type).reset_padding());
+ const DataType tmp_data_type = is_quantized_asymmetric ? DataType::F32 : src->data_type();
+ auto_init_if_empty(*tmp, TensorInfo(*src).set_data_type(tmp_data_type).reset_padding());
// Configure kernel window
- Window win = calculate_max_window(*max->info(), Steps());
+ Window win = calculate_max_window(*max, Steps());
Coordinates coord;
- coord.set_num_dimensions(output->info()->num_dimensions());
- output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));
-
- _input = input;
- _max = max;
- _output = output;
- _beta = beta;
- _tmp = tmp;
+ coord.set_num_dimensions(dst->num_dimensions());
+ dst->set_valid_region(ValidRegion(coord, dst->tensor_shape()));
- INEKernel::configure(win);
+ ICpuKernel::configure(win);
}
template <bool IS_LOG>
-Status NELogits1DSoftmaxKernel<IS_LOG>::validate(const ITensorInfo *input, const ITensorInfo *max,
- const ITensorInfo *output, const float beta, const ITensorInfo *tmp)
+Status CpuLogits1DSoftmaxKernel<IS_LOG>::validate(const ITensorInfo *src, const ITensorInfo *max,
+ const ITensorInfo *dst, const float beta, const ITensorInfo *tmp)
{
- ARM_COMPUTE_ERROR_ON_NULLPTR(input, max, output, tmp);
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_logits_softmax(*input, *max, *output, beta, *tmp, IS_LOG));
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src, max, dst, tmp);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_logits_softmax(*src, *max, *dst, beta, *tmp, IS_LOG));
return Status{};
}
template <bool IS_LOG>
-void NELogits1DSoftmaxKernel<IS_LOG>::run(const Window &window, const ThreadInfo &info)
+void CpuLogits1DSoftmaxKernel<IS_LOG>::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
- ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
- const unsigned int num_elems_processed_per_iteration = _input->info()->valid_region().shape.x();
- const unsigned int tmp_size_for_thread = _tmp->info()->element_size() * num_elems_processed_per_iteration;
+ const auto src = tensors.get_const_tensor(TensorType::ACL_SRC_0);
+ auto max = tensors.get_tensor(TensorType::ACL_SRC_1);
+ auto dst = tensors.get_tensor(TensorType::ACL_DST_0);
+ auto tmp = tensors.get_tensor(TensorType::ACL_DST_1);
- ARM_COMPUTE_ERROR_ON(_tmp->info()->total_size() < (info.num_threads * tmp_size_for_thread));
+ const unsigned int num_elems_processed_per_iteration = src->info()->valid_region().shape.x();
+ const unsigned int tmp_size_for_thread = tmp->info()->element_size() * num_elems_processed_per_iteration;
- void *tmp_for_thread = _tmp->buffer() + (info.thread_id * tmp_size_for_thread);
+ ARM_COMPUTE_ERROR_ON(tmp->info()->total_size() < (info.num_threads * tmp_size_for_thread));
+
+ void *tmp_for_thread = tmp->buffer() + (info.thread_id * tmp_size_for_thread);
+
+ const auto *uk = get_implementation_logits(SoftmaxSelectorData{ src->info()->data_type() });
+ uk->ukernel(src, max, tmp_for_thread, dst, _beta, IS_LOG, window);
+}
- const auto *uk = get_implementation_logits(SoftmaxSelectorData{ _input->info()->data_type() });
- uk->ukernel(_input, _max, tmp_for_thread, _output, _beta, IS_LOG, window);
+template <bool IS_LOG>
+const char *CpuLogits1DSoftmaxKernel<IS_LOG>::name() const
+{
+ if(IS_LOG)
+ {
+ return "CpuLogits1DSoftmaxKernel";
+ }
+ else
+ {
+ return "CpuLogits1DLogSoftmaxKernel";
+ }
}
-template class NELogits1DSoftmaxKernel<true>;
-template class NELogits1DSoftmaxKernel<false>;
+template class CpuLogits1DSoftmaxKernel<true>;
+template class CpuLogits1DSoftmaxKernel<false>;
+} // namespace kernels
+} // namespace cpu
} // namespace arm_compute
diff --git a/src/core/cpu/kernels/CpuSoftmaxKernel.h b/src/core/cpu/kernels/CpuSoftmaxKernel.h
new file mode 100644
index 0000000000..aa10467965
--- /dev/null
+++ b/src/core/cpu/kernels/CpuSoftmaxKernel.h
@@ -0,0 +1,107 @@
+/*
+ * Copyright (c) 2017-2021 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_CPU_SOFTMAXKERNEL_H
+#define ARM_COMPUTE_CPU_SOFTMAXKERNEL_H
+
+#include "src/core/common/Macros.h"
+#include "src/core/cpu/ICpuKernel.h"
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace kernels
+{
+/** Interface for the identifying the max value of 1D Logits */
+class CpuLogits1DMaxKernel : public ICpuKernel
+{
+public:
+ /** Constructor */
+ CpuLogits1DMaxKernel();
+ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuLogits1DMaxKernel);
+ /** Set the input and output tensors.
+ *
+ * @param[in] src Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+ * @param[out] dst Destination tensor info. Data types supported: same as @p input
+ */
+ void configure(const ITensorInfo *src, ITensorInfo *dst);
+ /** Static function to check if given info will lead to a valid configuration of @ref CpuLogits1DMaxKernel
+ *
+ * @param[in] src Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+ * @param[in] dst Destination tensor info. Data types supported: same as @p input
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *src, const ITensorInfo *dst);
+
+ // Inherited methods overridden:
+ void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
+ const char *name() const override;
+};
+
+/** Interface for softmax computation for QASYMM8 with pre-computed max. */
+template <bool IS_LOG = false>
+class CpuLogits1DSoftmaxKernel : public ICpuKernel
+{
+public:
+ /** Default constructor */
+ CpuLogits1DSoftmaxKernel();
+ ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuLogits1DSoftmaxKernel);
+
+ /** Set the input and output tensors.
+ *
+ * @param[in] src Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+ * @param[in] max Max values tensor info. Same shape as input with dimension 0 set to 1.
+ * Data types supported: same as @p input.
+ * @param[out] dst Destination tensor info. Data types supported: same as @p input.
+ * @param[in] beta A scaling factor for the exponent.
+ *
+ * @param tmp Auxiliary tensor info. Must be type F32 and same shape as the input.
+ */
+ void configure(const ITensorInfo *src, const ITensorInfo *max, ITensorInfo *dst, const float beta, ITensorInfo *tmp);
+ /** Static function to check if given info will lead to a valid configuration of @ref CpuLogits1DSoftmaxKernel
+ *
+ * @param[in] src Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
+ * @param[in] max Max values tensor info. Same shape as input with dimension 0 set to 1.
+ * Data types supported: same as @p input.
+ * @param[in] dst Destination tensor info. Data types supported: same as @p input.
+ * @param[in] beta A scaling factor for the exponent.
+ * @param[in] tmp Tensor info of auxiliary. Must be type F32 and same shape as the input.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *src, const ITensorInfo *max,
+ const ITensorInfo *dst, const float beta, const ITensorInfo *tmp);
+
+ // Inherited methods overridden:
+ void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
+ const char *name() const override;
+
+private:
+ float _beta;
+};
+} // namespace kernels
+} // namespace cpu
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_CPU_SOFTMAXKERNEL_H */
diff --git a/src/core/NEON/kernels/softmax/impl/NEON/list.h b/src/core/cpu/kernels/softmax/impl/NEON/list.h
index a8f781f439..1aa7e8fac7 100644
--- a/src/core/NEON/kernels/softmax/impl/NEON/list.h
+++ b/src/core/cpu/kernels/softmax/impl/NEON/list.h
@@ -24,10 +24,10 @@
#ifndef SRC_CORE_NEON_KERNELS_SOFTMAX_LIST_H
#define SRC_CORE_NEON_KERNELS_SOFTMAX_LIST_H
-#include "src/core/NEON/wrapper/wrapper.h"
-#include "support/SaturateCast.h"
#include "src/core/NEON/NEFixedPoint.h"
#include "src/core/NEON/NEMath.h"
+#include "src/core/NEON/wrapper/wrapper.h"
+#include "support/SaturateCast.h"
namespace arm_compute
{
diff --git a/src/core/NEON/kernels/softmax/impl/SVE/list.h b/src/core/cpu/kernels/softmax/impl/SVE/list.h
index 0936bd5a56..0936bd5a56 100644
--- a/src/core/NEON/kernels/softmax/impl/SVE/list.h
+++ b/src/core/cpu/kernels/softmax/impl/SVE/list.h
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-19 04:25:02 +0000