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Commit 26ce057d authored by Shucai Xiao's avatar Shucai Xiao
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tmp implementation.

parent df0d0d9f
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Showing with 21 additions and 53 deletions
src/include/migraphx/operators.hpp
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......@@ -766,7 +766,7 @@ struct gather
}
// for scalar output
if(lens.size() == 0)
if(lens.empty())
{
return {type, {1}, {0}};
}
......@@ -774,65 +774,33 @@ struct gather
return {type, lens};
}
// template <class T>
// void compute_index(const T& out_idx,
// const int axis_index,
// const std::vector<std::size_t>& vec_indices,
// const std::size_t max_dim,
// T& in_idx) const
// {
// in_idx = out_idx;
// std::size_t idx = vec_indices.at(out_idx[axis_index]);
// if(idx >= max_dim)
// {
// MIGRAPHX_THROW("Gather: indices are out of range in input tensor");
// }
// in_idx[axis_index] = idx;
// }
argument compute(const shape& output_shape, std::vector<argument> args) const
{
argument result{output_shape};
// negative axis means counting dimensions from back
int axis_index = (axis < 0) ? (args[0].get_shape().lens().size() + axis) : axis;
auto data_shape = args[0].get_shape();
int axis_index = (axis < 0) ? (data_shape.lens().size() + axis) : axis;
// max dimension in axis
// std::size_t max_dim = args[0].get_shape().lens()[axis_index];
// std::vector<std::size_t> vec_indices;
// args[1].visit([&](auto indices) { vec_indices.assign(indices.begin(), indices.end()); });
visit_all(result, args[0])([&](auto output, auto data) {
args[1].visit([&](auto indices) {
if(indices.get_shape().scalar())
{
if(output_shape.scalar())
std::vector<std::size_t> vec_indices;
args[1].visit([&](auto indices) { vec_indices.assign(indices.begin(), indices.end()); });
if (output_shape.scalar())
{
output[0] = data[indices.front()];
output[0] = data[vec_indices.front()];
}
else
{
shape_for_each(output.get_shape(), [&](const auto& out_idx) {
auto out_lens = data_shape.lens();
out_lens[axis_index] = vec_indices.size();
migraphx::shape out_comp_shape{output_shape.type(), out_lens};
shape_for_each(out_comp_shape, [&](const auto& out_idx) {
auto data_idx = out_idx;
data_idx.insert(data_idx.begin() + axis_index, indices.front());
output(out_idx.begin(), out_idx.end()) =
data(data_idx.begin(), data_idx.end());
data_idx[axis_index] = vec_indices[data_idx[axis_index]];
//output(out_idx.begin(), out_idx.end()) = data(data_idx.begin(), data_idx.end());
output[out_comp_shape.index(out_idx)] = data(data_idx.begin(), data_idx.end());
});
}
}
else
{
auto ind_lens = indices.get_shape().lens();
shape_for_each(output.get_shape(), [&](const auto& out_idx) {
auto data_idx = out_idx;
auto start_it = data_idx.begin() + axis_index;
auto end_it = data_idx.begin() + axis_index + ind_lens.size();
std::vector<std::size_t> ind_idx(start_it, end_it);
data_idx.erase(start_it, end_it);
data_idx.insert(start_it, indices(ind_idx.begin(), ind_idx.end()));
output(out_idx.begin(), out_idx.end()) =
data(data_idx.begin(), data_idx.end());
});
}
});
});
return result;
......
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