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
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
use crate::internal::*;
use crate::num_traits::Zero;
#[derive(Debug, Clone, PartialEq, Eq, Hash, new)]
pub struct DynSlice {
pub axis: usize,
pub start_input: bool,
pub end_input: bool,
pub symbol: Symbol,
}
impl DynHash for DynSlice {
fn dyn_hash(&self, hasher: &mut dyn std::hash::Hasher) {
dyn_hash(self, hasher)
}
}
impl DynSlice {
pub fn suffix(&self) -> String {
format!("axis{}", self.axis)
}
}
impl Op for DynSlice {
fn name(&self) -> Cow<str> {
"DynSlice".into()
}
fn info(&self) -> TractResult<Vec<String>> {
Ok(vec![format!("axis: {}", self.axis)])
}
op_as_typed_op!();
fn same_as(&self, other: &dyn Op) -> bool {
if let Some(other) = other.downcast_ref::<Self>() {
other == self
} else {
false
}
}
}
impl EvalOp for DynSlice {
fn is_stateless(&self) -> bool {
true
}
fn eval(&self, inputs: TVec<TValue>) -> TractResult<TVec<TValue>> {
unsafe {
let start =
if self.start_input { inputs[1].cast_to_scalar::<i64>()? as usize } else { 0 };
let end = if self.end_input {
inputs[1 + self.start_input as usize].cast_to_scalar::<i64>()? as usize
} else {
inputs[0].shape()[self.axis]
};
if start >= end {
bail!("Invalid range {}-{}", start, end);
}
let mut shape: TVec<_> = inputs[0].shape().into();
shape[self.axis] = end - start;
let mut tensor = Tensor::uninitialized_dt(inputs[0].datum_type(), &shape)?;
tensor.assign_slice_unchecked(.., &inputs[0], start..end, self.axis);
Ok(tvec!(tensor.into_tvalue()))
}
}
}
impl TypedOp for DynSlice {
fn output_facts(&self, inputs: &[&TypedFact]) -> TractResult<TVec<TypedFact>> {
let mut fact = inputs[0].clone();
fact.shape.set(self.axis, self.symbol.clone().into());
Ok(tvec!(fact))
}
fn invariants(
&self,
inputs: &[&TypedFact],
_outputs: &[&TypedFact],
) -> TractResult<Invariants> {
let axes =
(0..inputs[0].rank()).filter(|&ax| self.axis != ax).map(AxisInfo::simple).collect();
Ok(axes)
}
fn change_axes(
&self,
model: &TypedModel,
node: &TypedNode,
_io: InOut,
change: &AxisOp,
) -> TractResult<Option<AxisChangeConsequence>> {
if let Some(axis) = change.transform_axis(self.axis) {
if axis != self.axis {
Ok(Some(AxisChangeConsequence::new(
model,
node,
Some(Box::new(DynSlice { axis, ..self.clone() }) as _),
change,
)))
} else {
Ok(Some(AxisChangeConsequence::new(model, node, None, change)))
}
} else {
Ok(None)
}
}
fn declutter(
&self,
model: &TypedModel,
node: &TypedNode,
) -> TractResult<Option<TypedModelPatch>> {
let inputs = model.node_input_facts(node.id)?;
let start =
if self.start_input { inputs[1].konst.clone() } else { Some(rctensor0(TDim::zero())) };
let end = if self.end_input {
inputs[1 + self.start_input as usize].konst.clone()
} else {
Some(rctensor0(inputs[0].shape[self.axis].clone()))
};
if let (Some(start), Some(end)) = (start, end) {
return Ok(Some(TypedModelPatch::replace_single_op(
model,
node,
&[node.inputs[0]],
crate::ops::array::Slice {
axis: self.axis,
start: start.cast_to::<TDim>()?.to_scalar::<TDim>()?.clone(),
end: end.cast_to::<TDim>()?.to_scalar::<TDim>()?.clone(),
},
)?));
}
Ok(None)
}
as_op!();
}