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+
+// Copyright (c) 2020, ARM Limited.
+//
+// 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 "scatter_gather.h"
+#include "quant_util.h"
+
+using namespace TosaReference;
+using namespace Eigen;
+using namespace tosa;
+
+template <int InRank, int IndexRank, DType Dtype>
+OpGather<InRank, IndexRank, Dtype>::OpGather(TosaAttributeBase* attribute_, TosaQuantInfoBase* qinfo_, uint64_t id_)
+ : GraphNode(Op_GATHER, id_)
+{
+ setRequiredOperands(2, 1);
+ setRequiredRank(1, 6);
+
+ INIT_ATTRIBUTE(Axis);
+}
+
+template <int InRank, int IndexRank, DType Dtype>
+OpGather<InRank, IndexRank, Dtype>::~OpGather()
+{
+ if (attribute)
+ delete attribute;
+}
+
+template <int InRank, int IndexRank, DType Dtype>
+int OpGather<InRank, IndexRank, Dtype>::checkTensorAttributes()
+{
+ if (validateRequiredOperands())
+ return 1;
+
+ if (validateRequiredRank(inputs[0]) || validateRequiredRank(inputs[1]) || validateRequiredRank(outputs[0]))
+ {
+ return 1;
+ }
+
+ // output and input must be the same types
+ if (inputs[0]->matchType(*outputs[0]))
+ {
+ printNodeValidationError("Failure to match input and output type");
+ return 1;
+ }
+
+ in = dynamic_cast<TosaReference::TensorTemplate<TIn>*>(inputs[0]);
+ index = dynamic_cast<TosaReference::TensorTemplate<TIndex>*>(inputs[1]);
+ out = dynamic_cast<TosaReference::TensorTemplate<TOut>*>(outputs[0]);
+
+ ASSERT_MEM(in && index && out);
+
+ return 0;
+}
+
+template <int InRank, int IndexRank, DType Dtype>
+int OpGather<InRank, IndexRank, Dtype>::eval()
+{
+ int axis = attribute->axis();
+
+ // calculate size left and right to axis
+ int left_size = 1;
+ for (int i = 0; i < axis; ++i)
+ {
+ left_size *= in->getShape()[i];
+ }
+
+ int right_size = 1;
+ for (int i = axis + 1; i < in->getRank(); ++i)
+ {
+ right_size *= in->getShape()[i];
+ }
+
+ InEigenType* input_data = in->getTensor().data();
+ int32_t* index_data = index->getTensor().data();
+ OutEigenType* output_data = out->getTensor().data();
+
+ int32_t axis_size = in->getShape()[axis];
+ int32_t index_count = index->getElementCount();
+
+ // sanity check if index is valid
+ // need to check until this point since index is not known until runtime
+ for (size_t i = 0; i < index->getElementCount(); i++)
+ {
+ if (index_data[i] >= axis_size)
+ {
+ FATAL_ERROR_NODE("OpGather: index[%lu]=%i can't exceed axis_size=%i", i, index_data[i], axis_size);
+ }
+ }
+
+ // Eigen stores tensor in column-major
+ // so we iterate through dimension right to axis and the index array
+ // do memory copy with size of left size each time
+ for (int right = 0; right < right_size; ++right)
+ {
+ for (int i = 0; i < index_count; ++i)
+ {
+ std::memcpy(output_data + (right * index_count + i) * left_size,
+ input_data + (right * axis_size + index_data[i]) * left_size, sizeof(InEigenType) * left_size);
+ }
+ }
+
+ return GraphNode::eval();
+}
+
+// template explicit instantiation
+DEF_INSTANTIATE_GATHER(OpGather, AINT8);
+DEF_INSTANTIATE_GATHER(OpGather, INT16);
+DEF_INSTANTIATE_GATHER(OpGather, INT32);