| /* |
| * Copyright (c) 2022 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. |
| */ |
| #ifdef ENABLE_EXPERIMENTAL_DYNAMIC_FUSION |
| #include "arm_compute/core/experimental/OperatorGraph.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "src/core/experimental/dynamic_fusion/WorkloadImpl/OperatorGraphImpl.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| |
| namespace arm_compute |
| { |
| namespace experimental |
| { |
| namespace dynamic_fusion |
| { |
| namespace |
| { |
| void check_dependency_graph_op_success(OperatorGraph &graph, const Status &status) |
| { |
| if(!bool(status)) |
| { |
| graph.impl()->status = Status{ status.error_code(), "Cycles or loops are not allowed" }; |
| } |
| } |
| |
| // Check if there are more than one roots in the graph |
| void check_multiple_roots(OperatorGraph &graph) |
| { |
| if(graph.impl()->graph.get_root_ops().size() > 1) |
| { |
| graph.impl()->status = Status{ ErrorCode::RUNTIME_ERROR, "Multiple roots are not allowed" }; |
| } |
| } |
| |
| void check_execution_shape(OperatorGraph &graph, const ITensorInfo &dst_info) |
| { |
| const auto roots = graph.impl()->graph.get_root_ops(); |
| for(auto root : roots) |
| { |
| // We assume exactly 1 dst tensor for all operators |
| const auto root_info = graph.impl()->tensors[graph.impl()->graph.dst_tensors(root)[0]]->get_tensor_info(); |
| for(unsigned int dim = 0; dim < root_info->num_dimensions(); ++dim) |
| { |
| if(root_info->dimension(dim) != dst_info.dimension(dim)) |
| { |
| graph.impl()->status = Status{ ErrorCode::RUNTIME_ERROR, "Cannot change execution space" }; |
| return; |
| } |
| } |
| } |
| } |
| } // namespace |
| |
| OpTensor::OpTensor(Id id) |
| : _id{ id } |
| { |
| } |
| |
| OpTensor::Id OpTensor::id() const |
| { |
| return _id; |
| } |
| |
| bool operator<(const OpTensor &t0, const OpTensor &t1) |
| { |
| return t0.id() < t1.id(); |
| } |
| |
| Operator::Operator(Id id) |
| : _id{ id } |
| { |
| } |
| |
| Operator::Id Operator::id() const |
| { |
| return _id; |
| } |
| |
| bool operator<(const Operator &op0, const Operator &op1) |
| { |
| return op0.id() < op1.id(); |
| } |
| |
| OperatorGraph::OperatorGraph() |
| : _impl{ std::make_unique<Implementation>() } |
| { |
| } |
| |
| OperatorGraph::~OperatorGraph() = default; |
| |
| OperatorGraph::Implementation *OperatorGraph::impl() |
| { |
| return _impl.get(); |
| } |
| |
| const OperatorGraph::Implementation *OperatorGraph::impl() const |
| { |
| return _impl.get(); |
| } |
| |
| Status validate(const OperatorGraph &graph) |
| { |
| return graph.impl()->status; |
| } |
| |
| OpTensor add_tensor(OperatorGraph &graph, ITensorInfo &info) |
| { |
| auto id = graph.impl()->graph.add_tensor(); |
| OpTensor op_tensor(id); |
| graph.impl()->add_tensor(id, &info); |
| return op_tensor; |
| } |
| |
| Operator add_op_conv2d(OperatorGraph &graph, const Conv2dDescriptor &desc, OpTensor input, OpTensor weights, OpTensor bias, OpTensor dst) |
| { |
| // Check if map is empty as a complex operator can only be root |
| if(!graph.impl()->graph.get_root_ops().empty()) |
| { |
| graph.impl()->status = Status{ ErrorCode::RUNTIME_ERROR, "Cannot add multiple complex operators" }; |
| return Operator{}; |
| } |
| |
| std::pair<Status, DependencyGraph::Id> status_id; |
| |
| if(bias.id() == -1) |
| { |
| status_id = graph.impl()->graph.add_operator({ input.id(), weights.id() }, { dst.id() }); |
| } |
| else |
| { |
| status_id = graph.impl()->graph.add_operator({ input.id(), weights.id(), bias.id() }, { dst.id() }); |
| } |
| |
| check_dependency_graph_op_success(graph, status_id.first); |
| |
| Operator op_node(status_id.second); |
| |
| // Infer TensorInfo |
| OpTensorContent *dst_tensor = graph.impl()->tensors[dst.id()].get(); |
| if(dst_tensor->get_tensor_info()->total_size() == 0) |
| { |
| auto src = graph.impl()->tensors[input.id()]->get_tensor_info(); |
| auto wts = graph.impl()->tensors[weights.id()]->get_tensor_info(); |
| auto shape = misc::shape_calculator::compute_deep_convolution_shape(src->tensor_shape(), src->data_layout(), wts->tensor_shape(), PadStrideInfo(desc.stride.x(), desc.stride.y(), desc.pad.left, |
| desc.pad.right, |
| desc.pad.top, desc.pad.bottom, DimensionRoundingType::FLOOR)); // use the default DimensionRoundingType |
| |
| auto_init_if_empty(*(dst_tensor->get_tensor_info()), src->clone()->set_tensor_shape(shape)); |
| } |
| |
| // Check execution space |
| auto dst_info = dst_tensor->get_tensor_info(); |
| check_execution_shape(graph, *dst_info); |
| |
| ITensorDescPack<OpTensorContent> tensors; |
| tensors.add_const_tensor(ACL_SRC_0, graph.impl()->tensors[input.id()].get()); |
| tensors.add_const_tensor(ACL_SRC_1, graph.impl()->tensors[weights.id()].get()); |
| if(bias.id() != -1) |
| { |
| tensors.add_const_tensor(ACL_SRC_2, graph.impl()->tensors[bias.id()].get()); |
| } |
| tensors.add_const_tensor(ACL_DST_0, graph.impl()->tensors[dst.id()].get()); |
| |
| graph.impl()->add_node<Conv2dContent>(status_id.second, desc, tensors); |
| check_multiple_roots(graph); |
| |
| return op_node; |
| } |
| |
| Operator add_op_conv2d(OperatorGraph &graph, const Conv2dDescriptor &desc, OpTensor input, OpTensor weights, OpTensor dst) |
| { |
| return add_op_conv2d(graph, desc, input, weights, OpTensor(-1), dst); |
| } |
| |
| void force_conv2d_method(OperatorGraph &graph, Operator conv2d, ConvolutionMethod method) |
| { |
| auto node = utils::cast::polymorphic_downcast<Conv2dContent *>(graph.impl()->operators[conv2d.id()].get()); |
| node->set_method(method); |
| } |
| |
| Operator add_op_elementwise_op(OperatorGraph &graph, const ElementwiseDescriptor &desc, OpTensor lhs, OpTensor rhs, OpTensor dst) |
| { |
| auto id = graph.impl()->graph.add_operator({ rhs.id(), lhs.id() }, { dst.id() }); |
| check_dependency_graph_op_success(graph, id.first); |
| |
| Operator op_node(id.second); |
| |
| // Infer TensorInfo |
| auto node_lhs = graph.impl()->tensors[lhs.id()]->get_tensor_info(); |
| auto node_rhs = graph.impl()->tensors[rhs.id()]->get_tensor_info(); |
| OpTensorContent *node_dst = graph.impl()->tensors[dst.id()].get(); |
| |
| if(node_dst->get_tensor_info()->total_size() == 0) |
| { |
| const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*node_rhs, *node_lhs); |
| auto_init_if_empty(*(node_dst->get_tensor_info()), node_lhs->clone()->set_tensor_shape(broadcast_pair.first)); |
| } |
| |
| // Check execution space |
| auto dst_info = node_dst->get_tensor_info(); |
| check_execution_shape(graph, *dst_info); |
| |
| ITensorDescPack<OpTensorContent> tensors; |
| tensors.add_const_tensor(ACL_SRC_0, graph.impl()->tensors[lhs.id()].get()); |
| tensors.add_const_tensor(ACL_SRC_1, graph.impl()->tensors[rhs.id()].get()); |
| tensors.add_const_tensor(ACL_DST_0, graph.impl()->tensors[dst.id()].get()); |
| graph.impl()->add_node<ElementwiseContent>(id.second, desc, tensors); |
| check_multiple_roots(graph); |
| |
| return op_node; |
| } |
| |
| Operator add_op_floor(OperatorGraph &graph, const FloorDescriptor &desc, OpTensor src, OpTensor dst) |
| { |
| auto id = graph.impl()->graph.add_operator({ src.id() }, { dst.id() }); |
| check_dependency_graph_op_success(graph, id.first); |
| |
| Operator op_node(id.second); |
| |
| // Infer TensorInfo |
| auto node_src = graph.impl()->tensors[src.id()]->get_tensor_info(); |
| OpTensorContent *node_dst = graph.impl()->tensors[dst.id()].get(); |
| |
| if(node_dst->get_tensor_info()->total_size() == 0) |
| { |
| auto_init_if_empty(*(node_dst->get_tensor_info()), *node_src); |
| } |
| |
| // Check execution space |
| auto dst_info = node_dst->get_tensor_info(); |
| check_execution_shape(graph, *dst_info); |
| |
| ITensorDescPack<OpTensorContent> tensors; |
| tensors.add_const_tensor(ACL_SRC_0, graph.impl()->tensors[src.id()].get()); |
| tensors.add_const_tensor(ACL_DST_0, graph.impl()->tensors[dst.id()].get()); |
| graph.impl()->add_node<FloorContent>(id.second, desc, tensors); |
| check_multiple_roots(graph); |
| |
| return op_node; |
| } |
| } // namespace dynamic_fusion |
| } // namespace experimental |
| } // namespace arm_compute |
| #endif /* ENABLE_EXPERIMENTAL_DYNAMIC_FUSION */ |