1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
use crate::infer::*;
use crate::internal::*;
#[derive(Debug, Clone, new, Hash)]
pub struct PermuteAxes {
pub axes: Option<Vec<usize>>,
}
tract_linalg::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)
}
}
fn eval_t<T: Datum>(&self, input: Arc<Tensor>) -> TractResult<TVec<Arc<Tensor>>> {
if let Some(ref axes) = self.axes {
Ok(tvec![input
.into_tensor()
.into_array::<T>()?
.permuted_axes(&**axes)
.into_arc_tensor()])
} else {
Ok(tvec![input.into_tensor().into_array::<T>()?.reversed_axes().into_arc_tensor()])
}
}
}
impl Op for PermuteAxes {
fn name(&self) -> Cow<str> {
"PermuteAxes".into()
}
fn info(&self) -> TractResult<Vec<String>> {
Ok(vec![format!("{:?}", self.axes)])
}
op_hir!();
not_a_typed_op!();
not_a_pulsed_op!();
}
impl StatelessOp for PermuteAxes {
fn eval(&self, mut inputs: TVec<Arc<Tensor>>) -> TractResult<TVec<Arc<Tensor>>> {
let input = args_1!(inputs);
dispatch_datum!(Self::eval_t(input.datum_type())(self, input))
}
}
impl InferenceRulesOp for PermuteAxes {
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 i32)?;
}
Ok(())
}
#[allow(unused_variables)]
fn to_typed(
&self,
source: &InferenceModel,
node: &InferenceNode,
target: &mut TypedModel,
mapping: &HashMap<OutletId, OutletId>,
) -> TractResult<TVec<OutletId>> {
let fact = target.outlet_fact(mapping[&node.inputs[0]])?;
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());
}
let op = AxisOp::Permute(axes.iter().cloned().collect());
target.wire_node(&*node.name, op, &[mapping[&node.inputs[0]]])
} else {
let axes = (0..fact.rank()).rev().collect();
let op = AxisOp::Permute(axes);
target.wire_node(&*node.name, op, &[mapping[&node.inputs[0]]])
}
}
as_op!();
}