diff options
Diffstat (limited to 'runtimes/neurun/src/frontend/model.cc')
| -rw-r--r-- | runtimes/neurun/src/frontend/model.cc | 480 |
1 files changed, 0 insertions, 480 deletions
diff --git a/runtimes/neurun/src/frontend/model.cc b/runtimes/neurun/src/frontend/model.cc deleted file mode 100644 index 3aa2aa2ff..000000000 --- a/runtimes/neurun/src/frontend/model.cc +++ /dev/null @@ -1,480 +0,0 @@ -/* - * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved - * - * 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 <NeuralNetworks.h> -#include <NeuralNetworksEx.h> - -#include <cassert> -#include <stdexcept> -#include <new> - -#include "cpp14/memory.h" - -#include "graph/Graph.h" -#include "frontend/wrapper/model.h" -#include "frontend/wrapper/memory.h" -#include "model/operation/Node.Include.h" - -int ANeuralNetworksModel_create(ANeuralNetworksModel **model) -{ - if (model == nullptr) - { - return ANEURALNETWORKS_UNEXPECTED_NULL; - } - - *model = new (std::nothrow) ANeuralNetworksModel{}; - if (*model == nullptr) - { - return ANEURALNETWORKS_OUT_OF_MEMORY; - } - - return ANEURALNETWORKS_NO_ERROR; -} - -void ANeuralNetworksModel_free(ANeuralNetworksModel *model) { delete model; } - -int ANeuralNetworksModel_addOperand(ANeuralNetworksModel *model, - const ANeuralNetworksOperandType *type) -{ - if ((model == nullptr) || (type == nullptr)) - { - return ANEURALNETWORKS_UNEXPECTED_NULL; - } - - if (model->isFinished()) - { - return ANEURALNETWORKS_BAD_STATE; - } - - // scale and zeroPoint should be zero for scalars and non-fixed point tensors - // Quantized: - // scale: a 32 bit floating point value greater than zero - // zeroPoint: a 32 bit integer, in range [0, 255] - if (type->type == ANEURALNETWORKS_TENSOR_QUANT8_ASYMM) - { - if (!(type->scale > 0.0f)) - { - return ANEURALNETWORKS_BAD_DATA; - } - - if ((type->zeroPoint < 0) || (type->zeroPoint > 255)) - { - return ANEURALNETWORKS_BAD_DATA; - } - } - else if ((type->scale != 0.0f) || (type->zeroPoint != 0)) - { - return ANEURALNETWORKS_BAD_DATA; - } - - // dimensionCount should be zero for scalars - if ((type->dimensionCount != 0) && - ((type->type == ANEURALNETWORKS_FLOAT32) || (type->type == ANEURALNETWORKS_INT32) || - (type->type == ANEURALNETWORKS_UINT32))) - { - return ANEURALNETWORKS_BAD_DATA; - } - - ::neurun::model::operand::Shape shape(type->dimensionCount); - ::neurun::model::operand::TypeInfo typeInfo((OperandCode)(type->type), type->scale, - type->zeroPoint); - - for (uint32_t axis = 0; axis < type->dimensionCount; ++axis) - { - shape.dim(axis) = type->dimensions[axis]; - } - - model->deref().addOperand(shape, typeInfo); - - // NOTE We do NOT allocate CLTensor here as we do not how to interpret this one. - // TensorFlow Lite may interpret a rank-4 tensor either as a feature map (with batch) or - // a convolution kernel. - - return ANEURALNETWORKS_NO_ERROR; -} - -int ANeuralNetworksModel_setOperandValue(ANeuralNetworksModel *model, int32_t index, - const void *buffer, size_t length) -{ - const bool isOptional = ((buffer == nullptr) && (length == 0)); - - if ((model == nullptr) || ((buffer == nullptr) && (length != 0))) - { - return ANEURALNETWORKS_UNEXPECTED_NULL; - } - - if (model->isFinished()) - { - return ANEURALNETWORKS_BAD_STATE; - } - - // Negative index value is not allowed - if (index < 0) - { - return ANEURALNETWORKS_BAD_DATA; - } - const neurun::model::operand::Index ind{static_cast<uint32_t>(index)}; - - if (!model->deref().operands().exist(ind)) - { - return ANEURALNETWORKS_BAD_DATA; - } - - auto &obj = model->deref().operands().at(ind); - if ((obj.operandSize() != length) && !isOptional) - { - return ANEURALNETWORKS_BAD_DATA; - } - if (!obj.setAsConstant()) - { - return ANEURALNETWORKS_BAD_DATA; - } - - using ::neurun::model::operand::CachedData; - using ::neurun::model::operand::ExternalData; - - // Remain operands.at(ind).data()->base() as nullptr for optional operand - // This will be filled when model finished - if (isOptional) - { - model->setOptionalOperand(ind); - } - - // NNAPI spec in NeuralNetworks.h - // For values of length greater than ANEURALNETWORKS_MAX_SIZE_OF_IMMEDIATELY_COPIED_VALUES, - // the application is responsible for not changing the content of this region - // until all executions using this model have completed - if (length <= ANEURALNETWORKS_MAX_SIZE_OF_IMMEDIATELY_COPIED_VALUES) - { - model->deref().setOperandValue(ind, nnfw::cpp14::make_unique<CachedData>( - reinterpret_cast<const uint8_t *>(buffer), length)); - } - else - { - model->deref().setOperandValue(ind, nnfw::cpp14::make_unique<ExternalData>( - reinterpret_cast<const uint8_t *>(buffer), length)); - } - - return ANEURALNETWORKS_NO_ERROR; -} - -int ANeuralNetworksModel_setOperandValueFromMemory(ANeuralNetworksModel *model, int32_t index, - const ANeuralNetworksMemory *memory, - size_t offset, size_t length) -{ - if ((model == nullptr) || (memory == nullptr)) - { - return ANEURALNETWORKS_UNEXPECTED_NULL; - } - - if (model->isFinished()) - { - return ANEURALNETWORKS_BAD_STATE; - } - - // Negative index value is not allowed - if (index < 0) - { - return ANEURALNETWORKS_BAD_DATA; - } - const neurun::model::operand::Index ind{static_cast<uint32_t>(index)}; - - if (!model->deref().operands().exist(ind)) - { - return ANEURALNETWORKS_BAD_DATA; - } - - auto &obj = model->deref().operands().at(ind); - if ((obj.operandSize() != length) || (memory->size() < (offset + length))) - { - return ANEURALNETWORKS_BAD_DATA; - } - if (!obj.setAsConstant()) - { - return ANEURALNETWORKS_BAD_DATA; - } - - using ::neurun::model::operand::ExternalData; - - model->deref().setOperandValue( - ind, nnfw::cpp14::make_unique<ExternalData>( - reinterpret_cast<const uint8_t *>(memory->base() + offset), length)); - - return ANEURALNETWORKS_NO_ERROR; -} - -int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model, - ANeuralNetworksOperationType type, uint32_t inputCount, - const uint32_t *inputs, uint32_t outputCount, - const uint32_t *outputs) -{ - if ((model == nullptr) || (inputs == nullptr) || (outputs == nullptr)) - { - return ANEURALNETWORKS_UNEXPECTED_NULL; - } - - const ANeuralNetworksOperationType FIRST_OPERATION = ANEURALNETWORKS_ADD; - const ANeuralNetworksOperationType LAST_OPERATION = ANEURALNETWORKS_TRANSPOSE; - if ((type < FIRST_OPERATION) || (type > LAST_OPERATION)) - { - return ANEURALNETWORKS_BAD_DATA; - } - - if (model->isFinished()) - { - return ANEURALNETWORKS_BAD_STATE; - } - - for (uint32_t i = 0; i < outputCount; i++) - { - const ::neurun::model::operand::Index ind{outputs[i]}; - auto &obj = model->deref().operands().at(ind); - - if (!obj.setAsOperationOutput()) - { - return ANEURALNETWORKS_BAD_DATA; - } - } - - auto &graph = model->deref(); - - auto node_param = - neurun::model::operation::Node::InitParam{inputCount, inputs, outputCount, outputs}; - - try - { - switch (type) - { - case ANEURALNETWORKS_CONV_2D: - { - // inputCount is either 7 or 10 acccording to NN API specification. - // - Padding is implicit when inputCount is 7 - // - Padding is explicit when inputCount is 10 - assert(inputCount == 7 || inputCount == 10); - assert(outputCount == 1); - - if (inputCount == 7) - { - using GraphNode = neurun::model::operation::Conv2DNode; - - graph.addOperation(nnfw::cpp14::make_unique<GraphNode>(node_param)); - } - else - { - throw std::runtime_error{"Explicit padding in Conv2D is not supported, yet"}; - } - - break; - } - case ANEURALNETWORKS_MAX_POOL_2D: - { - // inputCount is either 7 or 10 acccording to NN API specification. - // - Padding is implicit when inputCount is 7 - // - Padding is explicit when inputCount is 10 - assert(inputCount == 7 || inputCount == 10); - assert(outputCount == 1); - - if (inputCount == 7) - { - using GraphNode = neurun::model::operation::MaxPool2DNode; - - graph.addOperation(nnfw::cpp14::make_unique<GraphNode>(node_param)); - } - else - { - throw std::runtime_error{"Explicit padding in MaxPool2D is not supported, yet"}; - } - - break; - } - case ANEURALNETWORKS_AVERAGE_POOL_2D: - { - // inputCount is either 7 or 10 acccording to NN API specification. - // - Padding is implicit when inputCount is 7 - // - Padding is explicit when inputCount is 10 - assert(inputCount == 7 || inputCount == 10); - assert(outputCount == 1); - - if (inputCount == 7) - { - using GraphNode = neurun::model::operation::AvgPool2DNode; - - graph.addOperation(nnfw::cpp14::make_unique<GraphNode>(node_param)); - } - else - { - throw std::runtime_error{"Explicit padding in AvgPool2D is not supported, yet"}; - } - - break; - } - case ANEURALNETWORKS_CONCATENATION: - { - using GraphNode = neurun::model::operation::ConcatNode; - - graph.addOperation(nnfw::cpp14::make_unique<GraphNode>(node_param)); - - break; - } - case ANEURALNETWORKS_RESHAPE: - { - using GraphNode = neurun::model::operation::ReshapeNode; - - graph.addOperation(nnfw::cpp14::make_unique<GraphNode>(node_param)); - - break; - } - case ANEURALNETWORKS_FULLY_CONNECTED: - { - using GraphNode = neurun::model::operation::FullyConnectedNode; - - graph.addOperation(nnfw::cpp14::make_unique<GraphNode>(node_param)); - - break; - } - case ANEURALNETWORKS_SOFTMAX: - { - using GraphNode = neurun::model::operation::SoftmaxNode; - - graph.addOperation(nnfw::cpp14::make_unique<GraphNode>(node_param)); - - break; - } - default: - throw std::runtime_error{"Not supported operation"}; - }; - } - catch (const std::exception &e) - { - return ANEURALNETWORKS_BAD_STATE; - } - - return ANEURALNETWORKS_NO_ERROR; -} - -int ANeuralNetworksModel_addOperationEx(ANeuralNetworksModel *model, - ANeuralNetworksOperationTypeEx type, uint32_t inputCount, - const uint32_t *inputs, uint32_t outputCount, - const uint32_t *outputs) -{ - if ((model == nullptr) || (inputs == nullptr) || (outputs == nullptr)) - { - return ANEURALNETWORKS_UNEXPECTED_NULL; - } - - if (model->isFinished()) - { - return ANEURALNETWORKS_BAD_STATE; - } - - const ANeuralNetworksOperationTypeEx FIRST_OPERATION = ANEURALNETWORKS_GATHER_EX; - const ANeuralNetworksOperationTypeEx LAST_OPERATION = ANEURALNETWORKS_PRELU_EX; - if ((type < FIRST_OPERATION) || (type > LAST_OPERATION)) - { - return ANEURALNETWORKS_BAD_DATA; - } - - for (uint32_t i = 0; i < outputCount; i++) - { - const ::neurun::model::operand::Index ind{outputs[i]}; - auto &obj = model->deref().operands().at(ind); - - if (!obj.setAsOperationOutput()) - { - return ANEURALNETWORKS_BAD_DATA; - } - } - - // Workaround: to avoid compile error by unused-parameter, use inputCount - if (inputCount == 0) - { - return ANEURALNETWORKS_BAD_DATA; - } - - try - { - switch (type) - { - default: - throw std::runtime_error{"Not supported operation"}; - } - } - catch (const std::exception &e) - { - return ANEURALNETWORKS_BAD_STATE; - } - - return ANEURALNETWORKS_NO_ERROR; -} - -int ANeuralNetworksModel_identifyInputsAndOutputs(ANeuralNetworksModel *model, uint32_t inputCount, - const uint32_t *inputs, uint32_t outputCount, - const uint32_t *outputs) -{ - if ((model == nullptr) || (inputs == nullptr) || (outputs == nullptr)) - { - return ANEURALNETWORKS_UNEXPECTED_NULL; - } - - if (model->isFinished()) - { - return ANEURALNETWORKS_BAD_STATE; - } - - // NOTE ::neurun::model::operand::Index uses int as its underlying type as various NNAPI - // functions such as ANeuralNetworksModel_setOperandValue use int to represent operand index - // - // ANeuralNetworksModel_identifyInputsAndOutputs, however, uses uint32_t to represent operand - // index. - // - // Below, static_cast<int>(...) is introduced to eliminate compiler warning. - for (uint32_t n = 0; n < inputCount; ++n) - { - const neurun::model::operand::Index ind{static_cast<uint32_t>(inputs[n])}; - model->deref().addInput(ind); - - auto &obj = model->deref().operands().at(ind); - if (!obj.setAsModelInput()) - { - return ANEURALNETWORKS_BAD_DATA; - } - } - - for (uint32_t n = 0; n < outputCount; ++n) - { - const neurun::model::operand::Index ind{static_cast<uint32_t>(outputs[n])}; - model->deref().addOutput(ind); - - auto &obj = model->deref().operands().at(ind); - // Model output cannot become model input - if (obj.isModelInput()) - { - return ANEURALNETWORKS_BAD_DATA; - } - } - - return ANEURALNETWORKS_NO_ERROR; -} - -int ANeuralNetworksModel_finish(ANeuralNetworksModel *model) -{ - if (model == nullptr) - { - return ANEURALNETWORKS_UNEXPECTED_NULL; - } - - return model->finish(); -} |