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use crate::internal::*;
use ndarray::*;
#[derive(Debug, Clone, new, Hash)]
pub struct ScatterNd;
impl_dyn_hash!(ScatterNd);
impl Op for ScatterNd {
fn name(&self) -> Cow<str> {
"ScatterNd".into()
}
op_core_mir!();
op_as_typed_op!();
}
impl ScatterNd {
unsafe fn eval_t<T: Datum>(
&self,
data: Arc<Tensor>,
indices: &ArrayViewD<i64>,
updates: Arc<Tensor>,
) -> TractResult<Arc<Tensor>> {
let mut data = data.into_tensor().into_array_unchecked::<T>();
let updates_view = updates.to_array_view_unchecked::<T>();
for coords in tract_ndarray::indices(&indices.shape()[..indices.ndim() - 1]) {
let mut indices_into_data = indices.view();
let mut updates = updates_view.view();
for x in coords.slice() {
indices_into_data.index_axis_inplace(Axis(0), *x);
updates.index_axis_inplace(Axis(0), *x);
}
let mut data = data.view_mut();
for x in indices_into_data {
data.index_axis_inplace(Axis(0), *x as usize);
}
data.assign(&updates)
}
let mut tensor = data.into_tensor();
tensor.set_datum_type(updates.datum_type());
Ok(tensor.into_arc_tensor())
}
}
impl TypedOp for ScatterNd {
as_op!();
fn output_facts(&self, inputs: &[&TypedFact]) -> TractResult<TVec<TypedFact>> {
Ok(tvec!(TypedFact::dt_shape(inputs[0].datum_type, inputs[0].shape.to_tvec())))
}
}
impl EvalOp for ScatterNd {
fn is_stateless(&self) -> bool {
true
}
fn eval(&self, mut inputs: TVec<Arc<Tensor>>) -> TractResult<TVec<Arc<Tensor>>> {
let (data, indices, updates) = args_3!(inputs);
let indices = indices.cast_to::<i64>()?;
let indices = indices.to_array_view::<i64>()?;
if data.datum_type() != updates.datum_type() {
bail!(
"Data and update must be of the same type, got {:?} and {:?}",
data.datum_type(),
updates.datum_type()
);
}
unsafe {
Ok(tvec!(dispatch_datum_by_size!(Self::eval_t(data.datum_type())(
&self, data, &indices, updates
))?))
}
}
}