Merge pull request !3726 from zhaozhenlong/lite/op/prior_boxtags/v0.7.0-beta
| @@ -173,7 +173,8 @@ union PrimitiveType { | |||
| Div, | |||
| Where, | |||
| OneHot, | |||
| Lstm | |||
| Lstm, | |||
| PriorBox | |||
| } | |||
| enum QuantType: int { | |||
| @@ -722,3 +722,17 @@ table OneHot { | |||
| table Lstm{ | |||
| bidirection: bool = false; | |||
| } | |||
| table PriorBox { | |||
| min_sizes: [int]; | |||
| max_sizes: [int]; | |||
| aspect_ratios: [float]; | |||
| variances: [float]; | |||
| image_size_w: int; | |||
| image_size_h: int; | |||
| step_w: float; | |||
| step_h: float; | |||
| clip: bool = true; | |||
| flip: bool = true; | |||
| offset: float; | |||
| } | |||
| @@ -131,6 +131,8 @@ Primitive *Primitive::CreatePrimitive(schema::Primitive *primitive) { | |||
| return new lite::Resize(const_cast<schema::Primitive *>(primitive)); | |||
| case schema::PrimitiveType_OneHot: | |||
| return new lite::OneHot(const_cast<schema::Primitive *>(primitive)); | |||
| case schema::PrimitiveType_PriorBox: | |||
| return new lite::PriorBox(const_cast<schema::Primitive *>(primitive)); | |||
| default: | |||
| break; | |||
| } | |||
| @@ -660,7 +660,14 @@ class StridedSlice : public Primitive { | |||
| std::vector<int> new_axis_mask_; | |||
| std::vector<int> shrink_axis_mask_; | |||
| }; | |||
| class PriorBox : public Primitive { | |||
| public: | |||
| explicit PriorBox(schema::Primitive *primitive) : Primitive(primitive) {} | |||
| const schema::PriorBox *GetAttrbute() const { return this->primitive->value_as_PriorBox(); } | |||
| int InferShape(std::vector<tensor::Tensor *> inputs, std::vector<tensor::Tensor *> outputs) override; | |||
| }; | |||
| } // namespace lite | |||
| } // namespace mindspore | |||
| #endif // MINDSPORE_LITE_SRC_OPS_OPS_H_ | |||
| @@ -0,0 +1,62 @@ | |||
| /** | |||
| * Copyright 2019-2020 Huawei Technologies Co., Ltd | |||
| * | |||
| * Licensed under the Apache License, Version 2.0 (the "License"); | |||
| * you may not use this file except in compliance with the License. | |||
| * You may obtain a copy of the License at | |||
| * | |||
| * http://www.apache.org/licenses/LICENSE-2.0 | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, software | |||
| * distributed under the License is distributed on an "AS IS" BASIS, | |||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * See the License for the specific language governing permissions and | |||
| * limitations under the License. | |||
| */ | |||
| #include "src/ops/ops.h" | |||
| #include "include/errorcode.h" | |||
| #include "utils/log_adapter.h" | |||
| #include "src/ir/tensor.h" | |||
| namespace mindspore::lite { | |||
| namespace { | |||
| constexpr int kPriorBoxPoints = 4; | |||
| constexpr int kPriorBoxN = 1; | |||
| constexpr int kPriorBoxW = 1; | |||
| constexpr int kPriorBoxC = 2; | |||
| } // namespace | |||
| int PriorBox::InferShape(std::vector<tensor::Tensor *> inputs_, std::vector<tensor::Tensor *> outputs_) { | |||
| auto param = GetAttrbute(); | |||
| MS_ASSERT(param != nullptr); | |||
| std::vector<float> different_aspect_ratios{1.0f}; | |||
| auto aspect_ratios = param->aspect_ratios(); | |||
| MS_ASSERT(aspect_ratios != nullptr); | |||
| for (auto i = 0; i < aspect_ratios->size(); i++) { | |||
| float ratio = (*aspect_ratios)[i]; | |||
| bool exist = std::any_of(different_aspect_ratios.begin(), different_aspect_ratios.end(), [&](float v) { | |||
| return abs(ratio - v) < 1e-6; | |||
| }); | |||
| if (!exist) { | |||
| different_aspect_ratios.emplace_back(ratio); | |||
| if (param->flip()) { | |||
| different_aspect_ratios.emplace_back(1.0f / ratio); | |||
| } | |||
| } | |||
| } | |||
| int32_t num_priors_box = param->min_sizes()->size() * different_aspect_ratios.size() + param->max_sizes()->size(); | |||
| auto input = inputs_.at(0); | |||
| MS_ASSERT(input != nullptr); | |||
| int32_t h = input->Height() * input->Width() * num_priors_box * kPriorBoxPoints; | |||
| std::vector<int> output_shape{kPriorBoxN, h, kPriorBoxW, kPriorBoxC}; | |||
| auto output = outputs_.at(0); | |||
| MS_ASSERT(output != nullptr); | |||
| output->set_shape(output_shape); | |||
| output->set_data_type(kNumberTypeFloat32); | |||
| output->SetFormat(input->GetFormat()); | |||
| return RET_OK; | |||
| } | |||
| } // namespace mindspore::lite | |||
| @@ -62,6 +62,7 @@ | |||
| #include "src/runtime/kernel/arm/opclib/fp32/unsqueeze.h" | |||
| #include "src/runtime/kernel/arm/opclib/fp32/one_hot.h" | |||
| #include "src/runtime/kernel/arm/opclib/fp32/strided_slice.h" | |||
| #include "src/runtime/kernel/arm/base/prior_box.h" | |||
| namespace mindspore::kernel { | |||
| FillParameter *PopulateFillParam(const lite::Primitive *primitive) { | |||
| @@ -990,6 +991,60 @@ OpParameter *PopulateAddNParam(const lite::Primitive *primitive) { | |||
| return parameter; | |||
| } | |||
| PriorBoxParameter *PopulatePriorBoxParameter(const lite::Primitive *primitive) { | |||
| PriorBoxParameter *param = new (std::nothrow) PriorBoxParameter(); | |||
| if (param == nullptr) { | |||
| MS_LOG(ERROR) << "new PriorBoxParameter failed."; | |||
| return nullptr; | |||
| } | |||
| param->op_parameter_.type_ = primitive->Type(); | |||
| auto prior_box_param = primitive->Value()->value_as_PriorBox(); | |||
| if (prior_box_param->min_sizes()->size() > PRIOR_BOX_MAX_NUM) { | |||
| MS_LOG(ERROR) << "PriorBox min_sizes size exceeds max num " << PRIOR_BOX_MAX_NUM << ", got " | |||
| << prior_box_param->min_sizes(); | |||
| delete (param); | |||
| return nullptr; | |||
| } | |||
| param->min_sizes_size = prior_box_param->min_sizes()->size(); | |||
| if (prior_box_param->max_sizes()->size() > PRIOR_BOX_MAX_NUM) { | |||
| MS_LOG(ERROR) << "PriorBox max_sizes size exceeds max num " << PRIOR_BOX_MAX_NUM << ", got " | |||
| << prior_box_param->max_sizes(); | |||
| delete (param); | |||
| return nullptr; | |||
| } | |||
| param->max_sizes_size = prior_box_param->max_sizes()->size(); | |||
| (void)memcpy(param->max_sizes, prior_box_param->max_sizes()->data(), | |||
| prior_box_param->max_sizes()->size() * sizeof(int32_t)); | |||
| (void)memcpy(param->min_sizes, prior_box_param->min_sizes()->data(), | |||
| prior_box_param->min_sizes()->size() * sizeof(int32_t)); | |||
| if (prior_box_param->aspect_ratios()->size() > PRIOR_BOX_MAX_NUM) { | |||
| MS_LOG(ERROR) << "PriorBox aspect_ratios size exceeds max num " << PRIOR_BOX_MAX_NUM << ", got " | |||
| << prior_box_param->aspect_ratios(); | |||
| delete (param); | |||
| return nullptr; | |||
| } | |||
| param->aspect_ratios_size = prior_box_param->aspect_ratios()->size(); | |||
| (void)memcpy(param->aspect_ratios, prior_box_param->aspect_ratios()->data(), | |||
| prior_box_param->aspect_ratios()->size() * sizeof(float)); | |||
| if (prior_box_param->variances()->size() != PRIOR_BOX_VAR_NUM) { | |||
| MS_LOG(ERROR) << "PriorBox variances size should be " << PRIOR_BOX_VAR_NUM << ", got " | |||
| << prior_box_param->variances()->size(); | |||
| delete (param); | |||
| return nullptr; | |||
| } | |||
| (void)memcpy(param->variances, prior_box_param->variances()->data(), PRIOR_BOX_VAR_NUM * sizeof(float)); | |||
| param->flip = prior_box_param->flip(); | |||
| param->clip = prior_box_param->clip(); | |||
| param->offset = prior_box_param->offset(); | |||
| param->image_size_h = prior_box_param->image_size_h(); | |||
| param->image_size_w = prior_box_param->image_size_w(); | |||
| param->step_h = prior_box_param->step_h(); | |||
| param->step_w = prior_box_param->step_w(); | |||
| return param; | |||
| } | |||
| OpParameter *PopulateParameter(const lite::Primitive *primitive) { | |||
| MS_EXCEPTION_IF_NULL(primitive); | |||
| auto op_type = primitive->Type(); | |||
| @@ -1109,6 +1164,8 @@ OpParameter *PopulateParameter(const lite::Primitive *primitive) { | |||
| return reinterpret_cast<OpParameter *>(PopulateOneHotParameter(primitive)); | |||
| case schema::PrimitiveType_AddN: | |||
| return reinterpret_cast<OpParameter *>(PopulateAddNParam(primitive)); | |||
| case schema::PrimitiveType_PriorBox: | |||
| return reinterpret_cast<OpParameter *>(PopulatePriorBoxParameter(primitive)); | |||
| default: | |||
| break; | |||
| } | |||
| @@ -0,0 +1,193 @@ | |||
| /** | |||
| * Copyright 2020 Huawei Technologies Co., Ltd | |||
| * | |||
| * Licensed under the Apache License, Version 2.0 (the "License"); | |||
| * you may not use this file except in compliance with the License. | |||
| * You may obtain a copy of the License at | |||
| * | |||
| * http://www.apache.org/licenses/LICENSE-2.0 | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, software | |||
| * distributed under the License is distributed on an "AS IS" BASIS, | |||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * See the License for the specific language governing permissions and | |||
| * limitations under the License. | |||
| */ | |||
| #include <vector> | |||
| #include <cmath> | |||
| #include "src/runtime/kernel/arm/base/prior_box.h" | |||
| #include "schema/model_generated.h" | |||
| #include "src/kernel_factory.h" | |||
| #include "include/errorcode.h" | |||
| #include "include/context.h" | |||
| #include "src/runtime/runtime_api.h" | |||
| using mindspore::lite::KernelRegistrar; | |||
| using mindspore::lite::RET_ERROR; | |||
| using mindspore::lite::RET_NULL_PTR; | |||
| using mindspore::lite::RET_OK; | |||
| using mindspore::schema::PrimitiveType_PriorBox; | |||
| namespace mindspore::kernel { | |||
| namespace { | |||
| constexpr int kInputNum = 2; | |||
| constexpr int kOutputNum = 1; | |||
| } // namespace | |||
| int PriorBoxCPUKernel::Init() { | |||
| if (prior_box_param_ == nullptr) { | |||
| MS_LOG(ERROR) << "PriorBoxParameter nullptr"; | |||
| return RET_NULL_PTR; | |||
| } | |||
| MS_ASSERT(inputs_.size() == kInputNum); | |||
| MS_ASSERT(outputs_.size() == kOutputNum); | |||
| auto ret = GeneratePriorBox(); | |||
| return ret; | |||
| } | |||
| int PriorBoxCPUKernel::GeneratePriorBox() { | |||
| const int fmap_w = inputs_[0]->Width(); | |||
| const int fmap_h = inputs_[0]->Height(); | |||
| const int image_w = prior_box_param_->image_size_w > 0 ? prior_box_param_->image_size_w : inputs_[1]->Width(); | |||
| const int image_h = prior_box_param_->image_size_h > 0 ? prior_box_param_->image_size_h : inputs_[1]->Height(); | |||
| const float step_w = | |||
| prior_box_param_->step_w > 0.0f ? prior_box_param_->step_w : static_cast<float>(image_w) / fmap_w; | |||
| const float step_h = | |||
| prior_box_param_->step_h > 0.0f ? prior_box_param_->step_h : static_cast<float>(image_h) / fmap_h; | |||
| std::vector<float> different_aspect_ratios{1.0f}; | |||
| auto aspect_ratios = prior_box_param_->aspect_ratios; | |||
| MS_ASSERT(aspect_ratios != nullptr); | |||
| for (auto i = 0; i < prior_box_param_->aspect_ratios_size; i++) { | |||
| float ratio = aspect_ratios[i]; | |||
| bool exist = std::any_of(different_aspect_ratios.begin(), different_aspect_ratios.end(), | |||
| [&](float v) { return abs(ratio - v) < 1e-6; }); | |||
| if (!exist) { | |||
| different_aspect_ratios.emplace_back(ratio); | |||
| if (prior_box_param_->flip) { | |||
| different_aspect_ratios.emplace_back(1.0f / ratio); | |||
| } | |||
| } | |||
| } | |||
| for (int i = 0; i < fmap_h; i++) { | |||
| float cy = i + prior_box_param_->offset; | |||
| for (int j = 0; j < fmap_w; j++) { | |||
| float cx = j + prior_box_param_->offset; | |||
| for (auto k = 0; k < prior_box_param_->min_sizes_size; k++) { | |||
| float min_size = prior_box_param_->min_sizes[k]; | |||
| output_.emplace_back((cx - min_size / step_w * 0.5f) / fmap_w); | |||
| output_.emplace_back((cy - min_size / step_h * 0.5f) / fmap_h); | |||
| output_.emplace_back((cx + min_size / step_w * 0.5f) / fmap_w); | |||
| output_.emplace_back((cy + min_size / step_h * 0.5f) / fmap_h); | |||
| if (prior_box_param_->max_sizes_size > 0) { | |||
| float max_size = prior_box_param_->max_sizes[k]; | |||
| float prime = sqrt(min_size * max_size); | |||
| output_.emplace_back((cx - prime / step_w * 0.5f) / fmap_w); | |||
| output_.emplace_back((cy - prime / step_h * 0.5f) / fmap_h); | |||
| output_.emplace_back((cx + prime / step_w * 0.5f) / fmap_w); | |||
| output_.emplace_back((cy + prime / step_h * 0.5f) / fmap_h); | |||
| } | |||
| for (auto v : different_aspect_ratios) { | |||
| if (abs(v - 1.0f) < 1e-6) { | |||
| continue; | |||
| } | |||
| float as_square_root = sqrt(v); | |||
| float box_w = min_size * as_square_root; | |||
| float box_h = min_size / as_square_root; | |||
| output_.emplace_back((cx - box_w / step_w * 0.5f) / fmap_w); | |||
| output_.emplace_back((cy - box_h / step_h * 0.5f) / fmap_h); | |||
| output_.emplace_back((cx + box_w / step_w * 0.5f) / fmap_w); | |||
| output_.emplace_back((cy + box_h / step_h * 0.5f) / fmap_h); | |||
| } | |||
| } | |||
| } | |||
| } | |||
| // do clip | |||
| if (prior_box_param_->clip) { | |||
| for (auto item : output_) { | |||
| if (item > 1.0f) { | |||
| item = 1.0f; | |||
| } | |||
| if (item < 0.0f) { | |||
| item = 0.0f; | |||
| } | |||
| } | |||
| } | |||
| // variance | |||
| for (auto i = 0; i < outputs_[0]->Height() / PRIOR_BOX_VAR_NUM; i++) { | |||
| for (auto j = 0; j < PRIOR_BOX_VAR_NUM; j++) { | |||
| output_.emplace_back(prior_box_param_->variances[j]); | |||
| } | |||
| } | |||
| return RET_OK; | |||
| } | |||
| int PriorBoxCPUKernel::PriorBoxImpl(int task_id) { | |||
| auto src = output_.data(); | |||
| auto output = outputs_.at(0); | |||
| if (output == nullptr) { | |||
| return RET_NULL_PTR; | |||
| } | |||
| auto ret = PriorBox(src, reinterpret_cast<float *>(output->Data()), output_.size(), task_id, thread_count_); | |||
| return ret; | |||
| } | |||
| int RunPriorBox(int task_id, LiteParallelGroupEnv *penv, void *cdata) { | |||
| auto prior_box = reinterpret_cast<PriorBoxCPUKernel *>(cdata); | |||
| auto error_code = prior_box->PriorBoxImpl(task_id); | |||
| if (error_code != RET_OK) { | |||
| MS_LOG(ERROR) << "Resize Run error task_id[" << task_id << "] error_code[" << error_code << "]"; | |||
| return RET_ERROR; | |||
| } | |||
| return RET_OK; | |||
| } | |||
| int PriorBoxCPUKernel::Run() { | |||
| int error_code = LiteBackendParallelLaunch(RunPriorBox, this, thread_count_); | |||
| if (error_code != RET_OK) { | |||
| MS_LOG(ERROR) << "PriorBox run error, error_code[" << error_code << "]"; | |||
| return RET_ERROR; | |||
| } | |||
| return RET_OK; | |||
| } | |||
| kernel::LiteKernel *CpuPriorBoxKernelCreator(const std::vector<lite::tensor::Tensor *> &inputs, | |||
| const std::vector<lite::tensor::Tensor *> &outputs, | |||
| OpParameter *opParameter, const Context *ctx, | |||
| const kernel::KernelKey &desc) { | |||
| if (opParameter == nullptr) { | |||
| MS_LOG(ERROR) << "Input opParameter is nullptr!"; | |||
| return nullptr; | |||
| } | |||
| if (desc.type != schema::PrimitiveType_PriorBox) { | |||
| MS_LOG(ERROR) << "PriorBox invalid desc type " << desc.type; | |||
| return nullptr; | |||
| } | |||
| auto *kernel = new (std::nothrow) PriorBoxCPUKernel(opParameter, inputs, outputs, ctx); | |||
| if (kernel == nullptr) { | |||
| MS_LOG(ERROR) << "new PriorBoxCPUKernel fail!"; | |||
| return nullptr; | |||
| } | |||
| auto ret = kernel->Init(); | |||
| if (ret != RET_OK) { | |||
| delete kernel; | |||
| MS_LOG(ERROR) << "Init kernel failed, name: " << opParameter->name_ << ", type: " | |||
| << schema::EnumNamePrimitiveType(static_cast<schema::PrimitiveType>(opParameter->type_)); | |||
| return nullptr; | |||
| } | |||
| return kernel; | |||
| } | |||
| REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_PriorBox, CpuPriorBoxKernelCreator) | |||
| REG_KERNEL(kCPU, kNumberTypeInt8, PrimitiveType_PriorBox, CpuPriorBoxKernelCreator) | |||
| } // namespace mindspore::kernel | |||
| @@ -0,0 +1,53 @@ | |||
| /** | |||
| * Copyright 2020 Huawei Technologies Co., Ltd | |||
| * | |||
| * Licensed under the Apache License, Version 2.0 (the "License"); | |||
| * you may not use this file except in compliance with the License. | |||
| * You may obtain a copy of the License at | |||
| * | |||
| * http://www.apache.org/licenses/LICENSE-2.0 | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, software | |||
| * distributed under the License is distributed on an "AS IS" BASIS, | |||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * See the License for the specific language governing permissions and | |||
| * limitations under the License. | |||
| */ | |||
| #ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_BASE_PRIOR_BOX_H_ | |||
| #define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_BASE_PRIOR_BOX_H_ | |||
| #include <vector> | |||
| #include "src/lite_kernel.h" | |||
| #include "src/runtime/kernel/arm/opclib/reshape_parameter.h" | |||
| #include "src/runtime/kernel/arm/opclib/prior_box.h" | |||
| using mindspore::lite::Context; | |||
| namespace mindspore::kernel { | |||
| class PriorBoxCPUKernel : public LiteKernel { | |||
| public: | |||
| PriorBoxCPUKernel(OpParameter *parameter, const std::vector<lite::tensor::Tensor *> &inputs, | |||
| const std::vector<lite::tensor::Tensor *> &outputs, const Context *ctx) | |||
| : LiteKernel(parameter, inputs, outputs), ctx_(ctx), thread_count_(ctx->threadNum) { | |||
| prior_box_param_ = reinterpret_cast<PriorBoxParameter *>(opParameter); | |||
| } | |||
| ~PriorBoxCPUKernel() = default; | |||
| int Init() override; | |||
| int ReSize() override { return 0; } | |||
| int Run() override; | |||
| int PriorBoxImpl(int task_id); | |||
| protected: | |||
| int thread_count_; | |||
| const Context *ctx_; | |||
| private: | |||
| std::vector<float> output_; | |||
| PriorBoxParameter *prior_box_param_; | |||
| int GeneratePriorBox(); | |||
| }; | |||
| } // namespace mindspore::kernel | |||
| #endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_BASE_PRIOR_BOX_H_ | |||
| @@ -0,0 +1,30 @@ | |||
| /** | |||
| * Copyright 2020 Huawei Technologies Co., Ltd | |||
| * | |||
| * Licensed under the Apache License, Version 2.0 (the "License"); | |||
| * you may not use this file except in compliance with the License. | |||
| * You may obtain a copy of the License at | |||
| * | |||
| * http://www.apache.org/licenses/LICENSE-2.0 | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, software | |||
| * distributed under the License is distributed on an "AS IS" BASIS, | |||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * See the License for the specific language governing permissions and | |||
| * limitations under the License. | |||
| */ | |||
| #include <memory.h> | |||
| #include "src/runtime/kernel/arm/opclib/errorcode.h" | |||
| #include "src/runtime/kernel/arm/opclib/prior_box.h" | |||
| int PriorBox(const float *input_data, float *output_data, const size_t size, const int tid, const int thread_num) { | |||
| size_t unit_size = size / thread_num; | |||
| if (tid == thread_num - 1) { | |||
| size_t tail_size = size - unit_size * tid; | |||
| (void)memcpy(output_data + tid * unit_size, input_data + tid * unit_size, tail_size * sizeof(float)); | |||
| } else { | |||
| (void)memcpy(output_data + tid * unit_size, input_data + tid * unit_size, unit_size * sizeof(float)); | |||
| } | |||
| return OPCLIB_OK; | |||
| } | |||
| @@ -0,0 +1,45 @@ | |||
| /** | |||
| * Copyright 2020 Huawei Technologies Co., Ltd | |||
| * | |||
| * Licensed under the Apache License, Version 2.0 (the "License"); | |||
| * you may not use this file except in compliance with the License. | |||
| * You may obtain a copy of the License at | |||
| * | |||
| * http://www.apache.org/licenses/LICENSE-2.0 | |||
| * | |||
| * Unless required by applicable law or agreed to in writing, software | |||
| * distributed under the License is distributed on an "AS IS" BASIS, | |||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |||
| * See the License for the specific language governing permissions and | |||
| * limitations under the License. | |||
| */ | |||
| #ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_OPCLIB_PRIOR_BOX_H_ | |||
| #define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_OPCLIB_PRIOR_BOX_H_ | |||
| #ifdef ENABLE_NEON | |||
| #include <arm_neon.h> | |||
| #endif | |||
| #include <memory.h> | |||
| #include "src/runtime/kernel/arm/opclib/op_base.h" | |||
| #define PRIOR_BOX_MAX_NUM 8 | |||
| #define PRIOR_BOX_VAR_NUM 4 | |||
| struct PriorBoxParameter { | |||
| OpParameter op_parameter_; | |||
| int32_t min_sizes_size; | |||
| int32_t min_sizes[PRIOR_BOX_MAX_NUM]; | |||
| int32_t max_sizes_size; | |||
| int32_t max_sizes[PRIOR_BOX_MAX_NUM]; | |||
| int32_t aspect_ratios_size; | |||
| float aspect_ratios[PRIOR_BOX_MAX_NUM]; | |||
| float variances[PRIOR_BOX_VAR_NUM]; | |||
| int32_t image_size_w; | |||
| int32_t image_size_h; | |||
| float step_w; | |||
| float step_h; | |||
| bool clip; | |||
| bool flip; | |||
| float offset; | |||
| }; | |||
| int PriorBox(const float *input_data, float *output_data, const size_t size, const int tid, const int thread_num); | |||
| #endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_OPCLIB_PRIOR_BOX_H_ | |||