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author | SiCong Li <sicong.li@arm.com> | 2022-01-28 18:24:39 +0000 |
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committer | SiCong Li <sicong.li@arm.com> | 2022-05-06 15:01:45 +0000 |
commit | b63b1196adea8b07dd8db77c2492a212650deba0 (patch) | |
tree | b264035197873f56c69784bec68cad7041b5d423 /src/core/experimental/dynamic_fusion/OperatorGraph.cpp | |
parent | 3bb72b69566f18ad5c9446d318d2fc2b5f6dba42 (diff) | |
download | ComputeLibrary-b63b1196adea8b07dd8db77c2492a212650deba0.tar.gz |
Integrate Dynamic Fusion patches
* Add public interfaces:
* OperatorGraph: Describe a workload that could contain fused kernels
* IWorkload: Generic interface for workloads built from OperatorGraph
* ClWorkload: OpenCL workloads built from OperatorGraph
* ClCompositeOperator: Runtime async operator to execute a ClWorkload
* DependencyGraph (will likely be deprecated in later iterations)
* Add example
* cl_fused_conv2d_elementwise_add.cpp to explain how to use the new
interfaces
* Add internal translation layer
* Refactor ClKernelBuildingAPI
* Remove non-tile based gemm native kernel component
* Minor interface changes
* Add integration tests
Resolves COMPMID-5161
Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: Ib987ed79289ab0bcbd3130d54f5793408d9f1240
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7510
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/experimental/dynamic_fusion/OperatorGraph.cpp')
-rw-r--r-- | src/core/experimental/dynamic_fusion/OperatorGraph.cpp | 236 |
1 files changed, 236 insertions, 0 deletions
diff --git a/src/core/experimental/dynamic_fusion/OperatorGraph.cpp b/src/core/experimental/dynamic_fusion/OperatorGraph.cpp new file mode 100644 index 0000000000..5dbf2f660d --- /dev/null +++ b/src/core/experimental/dynamic_fusion/OperatorGraph.cpp @@ -0,0 +1,236 @@ +/* + * 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. + */ +#ifndef ENABLE_EXPERIMENTAL_DYNAMIC_FUSION +#error "This experimental feature must be enabled with -DENABLE_EXPERIMENTAL_DYNAMIC_FUSION" +#endif /* 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_add(OperatorGraph &graph, const AddDescriptor &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<AddContent>(id.second, desc, tensors); + check_multiple_roots(graph); + + return op_node; +} +} // namespace dynamic_fusion +} // namespace experimental +} // namespace arm_compute
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