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-rw-r--r--src/runtime/gpu/cl/operators/ClSoftmax.cpp186
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diff --git a/src/runtime/gpu/cl/operators/ClSoftmax.cpp b/src/runtime/gpu/cl/operators/ClSoftmax.cpp
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-/*
- * Copyright (c) 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.
- */
-#include "src/runtime/gpu/cl/operators/ClSoftmax.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "src/core/gpu/cl/kernels/ClSoftmaxKernel.h"
-#include "src/core/helpers/MemoryHelpers.h"
-#include "src/core/helpers/SoftmaxHelpers.h"
-#include "src/runtime/gpu/cl/operators/ClPermute.h"
-#include "src/runtime/gpu/cl/utils/ClAuxTensorHandler.h"
-#include "support/Cast.h"
-
-using namespace arm_compute::experimental;
-
-namespace arm_compute
-{
-namespace opencl
-{
-ClSoftmax::ClSoftmax()
- : _permute_input(std::make_unique<ClPermute>()),
- _permute_output(std::make_unique<ClPermute>()),
- _max_shift_exp_sum_kernel(std::make_unique<kernels::ClLogits1DMaxShiftExpSumKernel>()),
- _norm_kernel(std::make_unique<kernels::ClLogits1DNormKernel>()),
- _max_info(),
- _sum_info(),
- _tmp_info(),
- _permuted_src_info(),
- _permuted_dst_info(),
- _aux_mem(InternalTensorIdx::COUNT)
-{
-}
-
-void ClSoftmax::configure(const CLCompileContext &compile_context, const ITensorInfo &src, ITensorInfo &dst, const SoftmaxKernelInfo &info)
-{
- ARM_COMPUTE_ERROR_THROW_ON(validate(src, dst, info));
-
- const size_t actual_axis = static_cast<size_t>(wrap_around(info.axis, static_cast<int32_t>(src.num_dimensions())));
-
- _needs_permute = actual_axis != 0;
-
- const ITensorInfo &tmp_input_info = _needs_permute ? _permuted_src_info : src;
- ITensorInfo &tmp_output_info = _needs_permute ? _permuted_dst_info : dst;
-
- if(_needs_permute)
- {
- const auto perm_info = softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis);
- _permute_input->configure(compile_context, &src, &_permuted_src_info, perm_info);
- }
-
- DataType tmp_data_type = is_data_type_quantized_asymmetric(tmp_input_info.data_type()) ? DataType::S32 : tmp_input_info.data_type();
- _tmp_info = tmp_input_info.clone()->set_data_type(tmp_data_type);
-
- TensorShape max_sum_shape = tmp_input_info.tensor_shape();
- _max_info = tmp_input_info.clone()->set_tensor_shape(max_sum_shape);
- _sum_info = tmp_input_info.clone()->set_tensor_shape(max_sum_shape).set_data_type(tmp_data_type);
-
- // Set GPU target to kernels
- _max_shift_exp_sum_kernel->set_target(CLScheduler::get().target());
-
- _max_shift_exp_sum_kernel->configure(compile_context, tmp_input_info, _max_info, _tmp_info, _sum_info, info);
- _norm_kernel->configure(compile_context, _tmp_info, _sum_info, tmp_output_info, info);
-
- if(_needs_permute)
- {
- const auto perm_info = softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis);
- _permute_output->configure(compile_context, &_permuted_dst_info, &dst, perm_info);
- }
-
- _aux_mem[InternalTensorIdx::SUM] = MemoryInfo(offset_int_vec(InternalTensorIdx::SUM), MemoryLifetime::Temporary, _sum_info.total_size());
- _aux_mem[InternalTensorIdx::TMP] = MemoryInfo(offset_int_vec(InternalTensorIdx::TMP), MemoryLifetime::Temporary, _tmp_info.total_size());
- _aux_mem[InternalTensorIdx::MAX] = MemoryInfo(offset_int_vec(InternalTensorIdx::MAX), MemoryLifetime::Temporary, _max_info.total_size());
-
- _aux_mem[InternalTensorIdx::PERMUTED_SRC] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), MemoryLifetime::Temporary, _permuted_src_info.total_size());
- _aux_mem[InternalTensorIdx::PERMUTED_DST] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_DST), MemoryLifetime::Temporary, _permuted_dst_info.total_size());
-}
-
-Status ClSoftmax::validate(const ITensorInfo &src, const ITensorInfo &dst, const SoftmaxKernelInfo &info)
-{
- ARM_COMPUTE_RETURN_ERROR_ON_MSG(src.num_dimensions() > 4, "Only up to 4 dimensions are supported");
- ARM_COMPUTE_UNUSED(info.beta);
- ARM_COMPUTE_RETURN_ERROR_ON(info.axis < static_cast<int32_t>(-src.num_dimensions()) || static_cast<int32_t>(src.num_dimensions()) <= info.axis);
-
- const size_t actual_axis = static_cast<size_t>(wrap_around(info.axis, static_cast<int32_t>(src.num_dimensions())));
- const bool needs_permute = actual_axis != 0;
- if(needs_permute)
- {
- const PermutationVector permutation_vector = softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis);
- const TensorShape permuted_shape = misc::shape_calculator::compute_permutation_output_shape(src, permutation_vector);
- TensorInfo input_permuted(src.clone()->set_tensor_shape(permuted_shape));
- ARM_COMPUTE_RETURN_ON_ERROR(ClPermute::validate(&src, &input_permuted, permutation_vector));
- TensorInfo output_permuted(dst.clone()->set_tensor_shape(permuted_shape));
- ARM_COMPUTE_RETURN_ON_ERROR(ClPermute::validate(&output_permuted, &dst, permutation_vector));
- }
-
- // Create intermediate tensor info
- DataType tmp_data_type = is_data_type_quantized_asymmetric(src.data_type()) ? DataType::S32 : src.data_type();
- TensorInfo tensor_info_tmp(src.clone()->set_data_type(tmp_data_type).set_is_resizable(true));
-
- TensorShape max_sum_shape = src.tensor_shape();
- max_sum_shape.set(0, 1);
- TensorInfo tensor_info_max(src.clone()->set_tensor_shape(max_sum_shape).set_is_resizable(true));
- TensorInfo tensor_info_sum(src.clone()->set_tensor_shape(max_sum_shape).set_data_type(tmp_data_type).set_quantization_info(QuantizationInfo()).set_is_resizable(true));
-
- ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClLogits1DMaxShiftExpSumKernel::validate(src, tensor_info_max, tensor_info_tmp, tensor_info_sum));
- ARM_COMPUTE_RETURN_ON_ERROR(kernels::ClLogits1DNormKernel::validate(tensor_info_tmp, tensor_info_sum, dst, info));
-
- return Status{};
-}
-
-void ClSoftmax::run(ITensorPack &tensors)
-{
- auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
- auto dst = tensors.get_tensor(TensorType::ACL_DST);
-
- CLAuxTensorHandler sum(offset_int_vec(InternalTensorIdx::SUM), _sum_info, tensors, false);
- CLAuxTensorHandler tmp(offset_int_vec(InternalTensorIdx::TMP), _tmp_info, tensors, false);
- CLAuxTensorHandler max(offset_int_vec(InternalTensorIdx::MAX), _max_info, tensors, false);
-
- CLAuxTensorHandler permuted_src(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), _permuted_src_info, tensors, false);
- CLAuxTensorHandler permuted_dst(offset_int_vec(InternalTensorIdx::PERMUTED_DST), _permuted_dst_info, tensors, false);
-
- if(_needs_permute)
- {
- ITensorPack pack;
- pack.add_const_tensor(TensorType::ACL_SRC, src);
- pack.add_tensor(TensorType::ACL_DST, permuted_src.get());
- _permute_input.get()->run(pack);
- }
-
- ITensorPack sum_pack;
- ITensorPack norm_pack;
- if(_needs_permute)
- {
- sum_pack.add_const_tensor(TensorType::ACL_SRC, permuted_src.get());
- norm_pack.add_tensor(TensorType::ACL_DST, permuted_dst.get());
- }
- else
- {
- sum_pack.add_const_tensor(TensorType::ACL_SRC, src);
- norm_pack.add_tensor(TensorType::ACL_DST, dst);
- }
- sum_pack.add_tensor(TensorType::ACL_DST, tmp.get());
- sum_pack.add_tensor(TensorType::ACL_INT_0, max.get());
- sum_pack.add_tensor(TensorType::ACL_INT_1, sum.get());
-
- norm_pack.add_const_tensor(TensorType::ACL_SRC, tmp.get());
- norm_pack.add_tensor(TensorType::ACL_INT_0, sum.get());
-
- CLScheduler::get().enqueue_op(*_max_shift_exp_sum_kernel.get(), sum_pack, false);
- CLScheduler::get().enqueue_op(*_norm_kernel.get(), norm_pack, false);
-
- if(_needs_permute)
- {
- ITensorPack pack;
- pack.add_const_tensor(TensorType::ACL_SRC, permuted_dst.get());
- pack.add_tensor(TensorType::ACL_DST, dst);
- _permute_output.get()->run(pack);
- }
-}
-
-experimental::MemoryRequirements ClSoftmax::workspace() const
-{
- return _aux_mem;
-}
-} // namespace opencl
-} // namespace arm_compute \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-03 22:33:50 +0000