COMPMID-797: Switch to new graph.
- Cleaned up build system
Change-Id: If2faa27ee5b31fa8b972836960ab3ef671059c8d
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/126435
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
diff --git a/arm_compute/graph/frontend/Layers.h b/arm_compute/graph/frontend/Layers.h
new file mode 100644
index 0000000..22133b8
--- /dev/null
+++ b/arm_compute/graph/frontend/Layers.h
@@ -0,0 +1,471 @@
+/*
+ * Copyright (c) 2018 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 __ARM_COMPUTE_GRAPH_LAYERS_H__
+#define __ARM_COMPUTE_GRAPH_LAYERS_H__
+
+#include "arm_compute/graph/GraphBuilder.h"
+#include "arm_compute/graph/Types.h"
+#include "arm_compute/graph/frontend/ILayer.h"
+#include "arm_compute/graph/frontend/IStream.h"
+#include "arm_compute/graph/frontend/SubStream.h"
+
+#include "arm_compute/core/utils/misc/Utility.h"
+
+#include <memory>
+#include <string>
+
+namespace arm_compute
+{
+namespace graph
+{
+namespace frontend
+{
+/** Input Layer */
+class InputLayer final : public ILayer
+{
+public:
+ /** Construct an input layer.
+ *
+ * @param[in] desc Description of input tensor.
+ * @param[in] accessor Accessor to get input tensor data from.
+ */
+ InputLayer(TensorDescriptor desc, ITensorAccessorUPtr accessor)
+ : _desc(desc), _accessor(std::move(accessor))
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { "", s.hints().target_hint };
+ return GraphBuilder::add_input_node(s.graph(), common_params, _desc, std::move(_accessor));
+ }
+
+private:
+ TensorDescriptor _desc;
+ ITensorAccessorUPtr _accessor;
+};
+
+/** Output Layer */
+class OutputLayer final : public ILayer
+{
+public:
+ /** Construct an output layer.
+ *
+ * @param[in] accessor Accessor to give output tensor data to.
+ */
+ OutputLayer(ITensorAccessorUPtr accessor)
+ : _accessor(std::move(accessor))
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { "", s.hints().target_hint };
+ NodeIdxPair input = { s.tail_node(), 0 };
+ return GraphBuilder::add_output_node(s.graph(), common_params, input, std::move(_accessor));
+ }
+
+private:
+ ITensorAccessorUPtr _accessor;
+};
+
+/** Activation Layer */
+class ActivationLayer final : public ILayer
+{
+public:
+ /** Construct an activation layer.
+ *
+ * @param[in] act_info Activation information
+ */
+ ActivationLayer(ActivationLayerInfo act_info)
+ : _act_info(act_info)
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { "", s.hints().target_hint };
+ NodeIdxPair input = { s.tail_node(), 0 };
+ return GraphBuilder::add_activation_node(s.graph(), common_params, input, _act_info);
+ }
+
+private:
+ ActivationLayerInfo _act_info;
+};
+
+/** Batchnormalization Layer */
+class BatchNormalizationLayer final : public ILayer
+{
+public:
+ /** Construct a batch normalization layer.
+ *
+ * @param[in] mean Accessor to get mean tensor data from.
+ * @param[in] var Accessor to get var tensor data from.
+ * @param[in] gamma (Optional) Accessor to get gamma tensor data from. Default: nullptr.
+ * @param[in] beta (Optional) Accessor to get beta tensor data from. Default: nullptr.
+ * @param[in] epsilon (Optional) Epsilon value. Default: 0.001.
+ */
+ BatchNormalizationLayer(ITensorAccessorUPtr mean,
+ ITensorAccessorUPtr var,
+ ITensorAccessorUPtr gamma = nullptr,
+ ITensorAccessorUPtr beta = nullptr,
+ float epsilon = 0.001f)
+ : _mean(std::move(mean)), _var(std::move(var)), _gamma(std::move(gamma)), _beta(std::move(beta)), _epsilon(epsilon)
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ ARM_COMPUTE_ERROR_ON(_mean == nullptr);
+ ARM_COMPUTE_ERROR_ON(_var == nullptr);
+
+ NodeParams common_params = { "", s.hints().target_hint };
+ NodeIdxPair input = { s.tail_node(), 0 };
+ return GraphBuilder::add_batch_normalization_node(s.graph(), common_params, input, _epsilon,
+ std::move(_mean), std::move(_var), std::move(_beta), std::move(_gamma));
+ }
+
+private:
+ ITensorAccessorUPtr _mean;
+ ITensorAccessorUPtr _var;
+ ITensorAccessorUPtr _gamma;
+ ITensorAccessorUPtr _beta;
+ float _epsilon;
+};
+
+/** Convolution Layer */
+class ConvolutionLayer final : public ILayer
+{
+public:
+ /** Construct a convolution layer.
+ *
+ * @param[in] conv_width Convolution width.
+ * @param[in] conv_height Convolution height.
+ * @param[in] ofm Output feature map.
+ * @param[in] weights Accessor to get kernel weights from.
+ * @param[in] bias Accessor to get kernel bias from.
+ * @param[in] conv_info Padding and stride information.
+ * @param[in] num_groups (Optional) Number of groups. Default: 1.
+ */
+ ConvolutionLayer(unsigned int conv_width,
+ unsigned int conv_height,
+ unsigned int ofm,
+ ITensorAccessorUPtr weights,
+ ITensorAccessorUPtr bias,
+ PadStrideInfo conv_info,
+ unsigned int num_groups = 1)
+ : _conv_width(conv_width),
+ _conv_height(conv_height),
+ _ofm(ofm),
+ _conv_info(std::move(conv_info)),
+ _num_groups(num_groups),
+ _weights(std::move(weights)),
+ _bias(std::move(bias))
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeIdxPair input = { s.tail_node(), 0 };
+ NodeParams common_params = { "", s.hints().target_hint };
+ return GraphBuilder::add_convolution_node(s.graph(), common_params, input,
+ Size2D(_conv_width, _conv_height), _ofm, _conv_info, _num_groups,
+ s.hints().convolution_method_hint,
+ std::move(_weights), std::move(_bias));
+ }
+
+private:
+ unsigned int _conv_width;
+ unsigned int _conv_height;
+ unsigned int _ofm;
+ const PadStrideInfo _conv_info;
+ unsigned int _num_groups;
+ ITensorAccessorUPtr _weights;
+ ITensorAccessorUPtr _bias;
+};
+
+/** Depthwise Convolution Layer */
+class DepthwiseConvolutionLayer final : public ILayer
+{
+public:
+ /** Construct a depthwise convolution layer.
+ *
+ * @param[in] conv_width Convolution width.
+ * @param[in] conv_height Convolution height.
+ * @param[in] weights Accessor to get kernel weights from.
+ * @param[in] bias Accessor to get kernel bias from.
+ * @param[in] conv_info Padding and stride information.
+ */
+ DepthwiseConvolutionLayer(unsigned int conv_width,
+ unsigned int conv_height,
+ ITensorAccessorUPtr weights,
+ ITensorAccessorUPtr bias,
+ PadStrideInfo conv_info)
+ : _conv_width(conv_width),
+ _conv_height(conv_height),
+ _conv_info(std::move(conv_info)),
+ _weights(std::move(weights)),
+ _bias(std::move(bias))
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeIdxPair input = { s.tail_node(), 0 };
+ NodeParams common_params = { "", s.hints().target_hint };
+ return GraphBuilder::add_depthwise_convolution_node(s.graph(), common_params,
+ input, Size2D(_conv_width, _conv_height), _conv_info,
+ s.hints().depthwise_convolution_method_hint,
+ std::move(_weights), std::move(_bias));
+ }
+
+private:
+ unsigned int _conv_width;
+ unsigned int _conv_height;
+ const PadStrideInfo _conv_info;
+ ITensorAccessorUPtr _weights;
+ ITensorAccessorUPtr _bias;
+};
+
+/** Flatten Layer */
+class FlattenLayer final : public ILayer
+{
+public:
+ /** Construct a flatten layer. */
+ FlattenLayer()
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { "", s.hints().target_hint };
+ NodeIdxPair input = { s.tail_node(), 0 };
+ return GraphBuilder::add_flatten_node(s.graph(), common_params, input);
+ }
+};
+
+/** Fully Connected Layer */
+class FullyConnectedLayer final : public ILayer
+{
+public:
+ /** Construct a fully connected layer.
+ *
+ * @param[in] num_outputs Number of outputs.
+ * @param[in] weights Accessor to get weights from.
+ * @param[in] bias Accessor to get bias from.
+ */
+ FullyConnectedLayer(unsigned int num_outputs,
+ ITensorAccessorUPtr weights,
+ ITensorAccessorUPtr bias)
+ : _num_outputs(num_outputs), _weights(std::move(weights)), _bias(std::move(bias))
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { "", s.hints().target_hint };
+ NodeIdxPair input = { s.tail_node(), 0 };
+ return GraphBuilder::add_fully_connected_layer(s.graph(), common_params, input, _num_outputs,
+ std::move(_weights), std::move(_bias));
+ }
+
+private:
+ unsigned int _num_outputs;
+ ITensorAccessorUPtr _weights;
+ ITensorAccessorUPtr _bias;
+};
+
+/** Normalization Layer */
+class NormalizationLayer final : public ILayer
+{
+public:
+ /** Construct a normalization layer.
+ *
+ * @param[in] norm_info Normalization information.
+ */
+ NormalizationLayer(NormalizationLayerInfo norm_info)
+ : _norm_info(norm_info)
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { "", s.hints().target_hint };
+ NodeIdxPair input = { s.tail_node(), 0 };
+ return GraphBuilder::add_normalization_node(s.graph(), common_params, input, _norm_info);
+ }
+
+private:
+ NormalizationLayerInfo _norm_info;
+};
+
+/** Pooling Layer */
+class PoolingLayer final : public ILayer
+{
+public:
+ /** Construct a pooling layer.
+ *
+ * @param[in] pool_info Pooling information.
+ */
+ PoolingLayer(PoolingLayerInfo pool_info)
+ : _pool_info(pool_info)
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { "", s.hints().target_hint };
+ NodeIdxPair input = { s.tail_node(), 0 };
+ return GraphBuilder::add_pooling_node(s.graph(), common_params, input, _pool_info);
+ }
+
+private:
+ PoolingLayerInfo _pool_info;
+};
+
+/** Reshape Layer */
+class ReshapeLayer final : public ILayer
+{
+public:
+ /** Construct a reshape layer.
+ *
+ * @param[in] shape Target shape.
+ */
+ ReshapeLayer(TensorShape shape)
+ : _shape(shape)
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { "", s.hints().target_hint };
+ NodeIdxPair input = { s.tail_node(), 0 };
+ return GraphBuilder::add_reshape_node(s.graph(), common_params, input, _shape);
+ }
+
+private:
+ TensorShape _shape;
+};
+
+/** Softmax Layer */
+class SoftmaxLayer final : public ILayer
+{
+public:
+ /** Construct a softmax layer.
+ *
+ * @param[in] beta (Optional) Beta value. Default 1.0.
+ */
+ SoftmaxLayer(float beta = 1.0f)
+ : _beta(beta)
+ {
+ }
+
+ NodeID create_layer(IStream &s) override
+ {
+ NodeParams common_params = { "", s.hints().target_hint };
+ NodeIdxPair input = { s.tail_node(), 0 };
+ return GraphBuilder::add_softmax_node(s.graph(), common_params, input, _beta);
+ }
+
+private:
+ float _beta;
+};
+
+/** Branch Layer */
+class BranchLayer final : public ILayer
+{
+public:
+ /** Construct a branch layer
+ *
+ * @param[in] merge_method Branch merging method
+ * @param[in] sub_stream1 First graph branch
+ * @param[in] sub_stream2 Second graph branch
+ * @param[in] rest_sub_streams Rest sub-graph branches
+ */
+ template <typename... Ts>
+ BranchLayer(BranchMergeMethod merge_method, SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams)
+ : _branch_merge_method(merge_method), _sub_streams()
+ {
+ _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream1)));
+ _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream2)));
+
+ utility::for_each([&](SubStream && sub_stream)
+ {
+ _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream)));
+ },
+ std::move(rest_sub_streams)...);
+ }
+ /** Construct a branch layer
+ *
+ * @param[in] sub_stream Sub-stream
+ */
+ template <typename... Ts>
+ BranchLayer(SubStream &&sub_stream)
+ : _branch_merge_method(BranchMergeMethod::DEPTH_CONCATENATE), _sub_streams()
+ {
+ _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream)));
+ }
+ NodeID create_layer(IStream &s) override
+ {
+ NodeID nid = EmptyNodeID;
+ NodeParams common_params = { "", s.hints().target_hint };
+ if(_sub_streams.size() == 1 && _sub_streams.at(0) != nullptr)
+ {
+ nid = _sub_streams[0]->tail_node();
+ }
+ else if(_branch_merge_method == BranchMergeMethod::DEPTH_CONCATENATE)
+ {
+ // Collect tail nodes and perform DepthConcatenate
+ std::vector<NodeIdxPair> nodes;
+ for(auto &ss : _sub_streams)
+ {
+ if(ss && (ss->tail_node() != EmptyNodeID))
+ {
+ const auto tail_node = s.graph().node(ss->tail_node());
+ if(tail_node != nullptr && tail_node->type() != NodeType::Output)
+ {
+ nodes.push_back({ ss->tail_node(), 0 });
+ }
+ }
+ }
+ nid = GraphBuilder::add_depth_concatenate_node(s.graph(), common_params, nodes);
+ }
+ else
+ {
+ ARM_COMPUTE_ERROR_ON(_sub_streams.size() != 2);
+ NodeIdxPair input0 = { _sub_streams[0]->tail_node(), 0 };
+ NodeIdxPair input1 = { _sub_streams[1]->tail_node(), 0 };
+ nid = GraphBuilder::add_elementwise_node(s.graph(), common_params, input0, input1, EltwiseOperation::ADD);
+ }
+ return nid;
+ }
+
+private:
+ BranchMergeMethod _branch_merge_method;
+ std::vector<std::unique_ptr<SubStream>> _sub_streams;
+};
+} // namespace frontend
+} // namespace graph
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_GRAPH_LAYERS_H__ */