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/*
* 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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