use tract_num_traits::AsPrimitive;
use crate::internal::*;
#[derive(Debug, Default, Clone, new, Hash)]
pub struct Range {
pub start: Tensor,
pub end: Tensor,
pub step: Tensor,
}
impl_dyn_hash!(Range);
impl Op for Range {
fn name(&self) -> Cow<str> {
"Range".into()
}
op_as_typed_op!();
}
impl EvalOp for Range {
fn is_stateless(&self) -> bool {
self.start.datum_type() != TDim::datum_type()
|| (self.start.to_scalar::<TDim>().unwrap().to_i64().is_ok()
&& self.end.to_scalar::<TDim>().unwrap().to_i64().is_ok()
&& self.step.to_scalar::<TDim>().unwrap().to_i64().is_ok())
}
fn eval(&self, _inputs: TVec<TValue>) -> TractResult<TVec<TValue>> {
let tensor = self.make(None)?;
Ok(tvec!(tensor.into_tvalue()))
}
fn state(
&self,
_session: &mut SessionState,
_node_id: usize,
) -> TractResult<Option<Box<dyn OpState>>> {
if self.is_stateless() {
Ok(None)
} else {
Ok(Some(Box::new(self.clone())))
}
}
}
impl OpState for Range {
fn eval(
&mut self,
session: &mut SessionState,
_op: &dyn Op,
_inputs: TVec<TValue>,
) -> TractResult<TVec<TValue>> {
Ok(tvec!(self.make(Some(&session.resolved_symbols))?.into_tvalue()))
}
}
trivial_op_state_freeeze!(Range);
impl Range {
fn make_t<T: Datum + for<'a> std::ops::Add<&'a T, Output = T>>(
start: &Tensor,
step: &Tensor,
len: usize,
) -> TractResult<Tensor> {
unsafe {
let mut result = Tensor::uninitialized::<T>(&[len])?;
let mut v = start.to_scalar::<T>()?.clone();
let step = step.to_scalar::<T>()?;
for i in 0..len {
result.as_slice_mut_unchecked::<T>()[i] = v.clone();
v = v + step;
}
Ok(result)
}
}
fn make(&self, values: Option<&SymbolValues>) -> TractResult<Tensor> {
if self.start.datum_type() == TDim::datum_type() {
let none = SymbolValues::default();
let values = values.unwrap_or(&none);
let start = self.start.to_scalar::<TDim>()?.eval(values).to_i64()?;
let end = self.end.to_scalar::<TDim>()?.eval(values).to_i64()?;
let step = self.step.to_scalar::<TDim>()?.eval(values).to_i64()?;
#[allow(clippy::cast_abs_to_unsigned)]
let len = ((end - start).abs() as usize).divceil(step.abs() as usize);
Self::make_t::<TDim>(&self.start, &self.step, len)
} else {
let len = dispatch_numbers!(Self::len_for_numbers(self.start.datum_type())(self))?;
dispatch_numbers!(Self::make_t(self.start.datum_type())(&self.start, &self.step, len))
}
}
fn len_for_numbers<T: Datum + AsPrimitive<f64>>(&self) -> TractResult<usize> {
let start = self.start.to_scalar::<T>()?;
let end = self.end.to_scalar::<T>()?;
let step = self.step.to_scalar::<T>()?;
Ok(((end.as_() - start.as_()) / (step.as_())).ceil() as usize)
}
}
impl TypedOp for Range {
fn output_facts(&self, _inputs: &[&TypedFact]) -> TractResult<TVec<TypedFact>> {
ensure!(self.start.datum_type() == self.end.datum_type());
ensure!(self.start.datum_type() == self.step.datum_type());
let len = if self.start.datum_type() == TDim::datum_type() {
let start = self.start.to_scalar::<TDim>()?;
let end = self.end.to_scalar::<TDim>()?;
let step = self.step.to_scalar::<TDim>()?.to_i64()?;
(end.clone() - start).divceil(step as usize)
} else {
dispatch_numbers!(Self::len_for_numbers(self.start.datum_type())(self))?.into()
};
Ok(tvec!(self.start.datum_type().fact(&[len])))
}
fn concretize_dims(
&self,
_source: &TypedModel,
node: &TypedNode,
target: &mut TypedModel,
_mapping: &HashMap<OutletId, OutletId>,
values: &SymbolValues,
) -> TractResult<TVec<OutletId>> {
let op = if self.start.datum_type() == TDim::datum_type() {
let start = self.start.to_scalar::<TDim>()?.eval(values).into();
let end = self.end.to_scalar::<TDim>()?.eval(values).into();
let step = self.step.to_scalar::<TDim>()?.eval(values).into();
Self { start, end, step }
} else {
self.clone()
};
target.wire_node(&node.name, op, &[])
}
as_op!();
}