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use crate::infer::*;
use crate::internal::*;
#[derive(Debug, Clone, new, Hash)]
pub struct PermuteAxes {
pub axes: Option<TVec<usize>>,
}
impl_dyn_hash!(PermuteAxes);
impl PermuteAxes {
fn compute_shape<D: DimLike>(&self, input: &[D]) -> TractResult<TVec<D>> {
if let Some(ref axes) = self.axes {
if input.len() != axes.len() {
bail!(
"Op expects tensor of rank {}, input is actually of rank {}.",
axes.len(),
input.len()
);
}
let mut new_shape = tvec![D::zero(); input.len()];
for (ix, &d) in axes.iter().enumerate() {
new_shape[ix] = input[d].clone();
}
Ok(new_shape)
} else {
let mut new_shape: TVec<D> = input.iter().cloned().collect();
new_shape.reverse();
Ok(new_shape)
}
}
}
impl Expansion for PermuteAxes {
fn name(&self) -> Cow<str> {
"PermuteAxes".into()
}
op_hir!();
fn info(&self) -> TractResult<Vec<String>> {
Ok(vec![format!("{:?}", self.axes)])
}
fn rules<'r, 'p: 'r, 's: 'r>(
&'s self,
s: &mut Solver<'r>,
inputs: &'p [TensorProxy],
outputs: &'p [TensorProxy],
) -> InferenceResult {
check_output_arity(&outputs, 1)?;
s.equals(&outputs[0].datum_type, &inputs[0].datum_type)?;
s.equals(&outputs[0].rank, &inputs[0].rank)?;
s.given(&inputs[0].shape, move |s, shape| {
let output_shape = self.compute_shape(&shape)?;
s.equals(&outputs[0].shape, output_shape)
})?;
if let Some(axes) = &self.axes {
s.equals(&outputs[0].rank, axes.len() as i64)?;
}
Ok(())
}
fn wire(
&self,
prefix: &str,
target: &mut TypedModel,
inputs: &[OutletId],
) -> TractResult<TVec<OutletId>> {
let fact = target.outlet_fact(inputs[0])?;
let axes = if let Some(axes) = &self.axes {
if fact.rank() != axes.len() {
bail!(
"Op expects tensor of rank {}, input is actually of rank {}.",
axes.len(),
fact.rank()
);
}
axes.clone()
} else {
(0..fact.rank()).rev().collect()
};
let mut wire: TVec<OutletId> = inputs.into();
for (ix, op) in perm_to_ops(&axes).into_iter().enumerate() {
wire = target.wire_node(format!("{}.{}-{}", prefix, op.name(), ix), op, &wire)?;
}
Ok(wire)
}
}