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use ndarray::*;
use crate::broadcast::multi_broadcast;
use crate::internal::*;
use super::binary::{commute, BinMiniOp};
use super::element_wise::ElementWiseOp;
bin_to_super_type!(and, And, flip: commute,
[bool, u8, u16, u32, u64, i8, i16, i32, i64] => |c, &a, &b| *c = (a as i64 != 0 && b as i64 != 0) as _);
bin_to_super_type!(or, Or, flip: commute,
[bool, u8, u16, u32, u64, i8, i16, i32, i64] => |c, &a, &b| *c = (a as i64 != 0 || b as i64 != 0) as _);
bin_to_super_type!(xor, Xor, flip: commute, [bool] => |c, &a, &b| *c = a ^ b);
bin_to_bool!(equals, Equals, flip: commute,
[bool, u8, u16, u32, u64, i8, i16, i32, i64, f32, f64, TDim] => |c, a, b | *c = a == b
);
bin_to_bool!(not_equals, NotEquals, flip: commute,
[bool, u8, u16, u32, u64, i8, i16, i32, i64, f32, f64, TDim] => |c, a, b | *c = a != b
);
bin_to_bool!(less, Less,
codegen_unary: codegen_compare_to_zero,
[bool, u8, u16, u32, u64, i8, i16, i32, i64, f32, f64] => |c, &a, &b | *c = a < b);
bin_to_bool!(less_equal, LessEqual,
codegen_unary: codegen_compare_to_zero,
[bool, u8, u16, u32, u64, i8, i16, i32, i64, f32, f64] => |c, &a, &b | *c = a <= b);
bin_to_bool!(greater, Greater,
codegen_unary: codegen_compare_to_zero,
[bool, u8, u16, u32, u64, i8, i16, i32, i64, f32, f64] => |c, &a, &b | *c = a > b);
bin_to_bool!(greater_equal, GreaterEqual,
codegen_unary: codegen_compare_to_zero,
[bool, u8, u16, u32, u64, i8, i16, i32, i64, f32, f64] => |c, &a, &b | *c = a >= b);
fn codegen_compare_to_zero(
op: &dyn BinMiniOp,
model: &TypedModel,
node: &TypedNode,
a: &Arc<Tensor>,
) -> TractResult<Option<TypedModelPatch>> {
if let Some(a) = a.as_uniform() {
if (a.datum_type().is_signed() || a.datum_type().is_float())
&& a == Tensor::zero_scalar_dt(a.datum_type())?
{
let op: Box<dyn ElementWiseMiniOp> = if op.is::<Less>() {
Box::new(GreaterThanZero {})
} else if op.is::<LessEqual>() {
Box::new(GreaterEqualThanZero {})
} else if op.is::<Greater>() {
Box::new(LessThanZero {})
} else if op.is::<GreaterEqual>() {
Box::new(LessEqualThanZero {})
} else {
unreachable!();
};
return Ok(Some(TypedModelPatch::replace_single_op(
model,
node,
&node.inputs,
ElementWiseOp(op),
)?));
}
}
Ok(None)
}
element_wise_oop!(less_than_zero, LessThanZero, [f16, f32, f64, i8, i16, i32, i64] => bool |_op, xs, ys| {
xs.iter().zip(ys.iter_mut()).for_each(|(x,y)| *y = *x < num_traits::Zero::zero());
Ok(())
});
element_wise_oop!(less_equal_than_zero, LessEqualThanZero, [f16, f32, f64, i8, i16, i32, i64] => bool |_op, xs, ys| {
xs.iter().zip(ys.iter_mut()).for_each(|(x,y)| *y = *x <= num_traits::Zero::zero());
Ok(())
});
element_wise_oop!(greater_than_zero, GreaterThanZero, [f16, f32, f64, i8, i16, i32, i64] => bool |_op, xs, ys| {
xs.iter().zip(ys.iter_mut()).for_each(|(x,y)| *y = *x > num_traits::Zero::zero());
Ok(())
});
element_wise_oop!(greater_equal_than_zero, GreaterEqualThanZero, [f16, f32, f64, i8, i16, i32, i64] => bool |_op, xs, ys| {
xs.iter().zip(ys.iter_mut()).for_each(|(x,y)| *y = *x >= num_traits::Zero::zero());
Ok(())
});
element_wise!(not, Not, [bool] => |_, vs| {
vs.iter_mut().for_each(|a| *a = !*a);
Ok(())
});
#[derive(Debug, Clone, new, Default, Hash)]
pub struct Iff;
impl_dyn_hash!(Iff);
impl Iff {
pub unsafe fn eval_t<T: Datum>(
cond: &ArrayViewD<bool>,
out: &mut Tensor,
t: &Tensor,
f: &Tensor,
) {
Zip::from(out.to_array_view_mut_unchecked::<T>())
.and_broadcast(cond)
.and_broadcast(t.to_array_view_unchecked::<T>())
.and_broadcast(f.to_array_view_unchecked::<T>())
.for_each(|r, c, t, f| *r = if *c { t.clone() } else { f.clone() })
}
}
impl Op for Iff {
fn name(&self) -> Cow<str> {
"Iff".into()
}
op_core_mir!();
op_as_typed_op!();
}
impl EvalOp for Iff {
fn is_stateless(&self) -> bool {
true
}
fn eval(&self, mut inputs: TVec<Arc<Tensor>>) -> TractResult<TVec<Arc<Tensor>>> {
let (cond, t, f) = args_3!(inputs);
let shape: TVec<usize> = multi_broadcast(&[cond.shape(), t.shape(), f.shape()])
.ok_or_else(|| {
format_err!(
"Incompatible shapes {:?}, {:?} and {:?}",
cond.shape(),
t.shape(),
f.shape()
)
})?;
unsafe {
let mut result = Tensor::uninitialized_dt(t.datum_type(), &*shape)?;
let cond = cond.to_array_view::<bool>()?;
dispatch_datum_by_size!(Self::eval_t(t.datum_type())(&cond, &mut result, &t, &f));
Ok(tvec!(result.into_arc_tensor()))
}
}
}
impl TypedOp for Iff {
as_op!();
fn output_facts(&self, inputs: &[&TypedFact]) -> TractResult<TVec<TypedFact>> {
anyhow::ensure!(inputs.len() == 3, "Iff expects 3 intputs.");
if inputs[1].datum_type != inputs[2].datum_type {
bail!("Then and else tensors type mismatch ({:?} and {:?}).", inputs[1], inputs[2]);
}
if inputs[0].rank() != inputs[1].rank() || inputs[0].rank() != inputs[2].rank() {
bail!("Inconsistent ranks, {:?}", inputs);
}
let shape = multi_broadcast(&[
inputs[0].shape.to_tvec(),
inputs[1].shape.to_tvec(),
inputs[2].shape.to_tvec(),
])
.unwrap();
Ok(tvec!(inputs[1].datum_type.fact(shape)))
}
fn invariants(
&self,
inputs: &[&TypedFact],
_outputs: &[&TypedFact],
) -> TractResult<Invariants> {
let a = &inputs[0];
let b = &inputs[1];
let c = &inputs[2];
assert!(a.rank() == b.rank() && b.rank() == c.rank());
let rank = a.rank();
Ok((0..rank)
.into_iter()
.map(|axis| AxisInfo {
inputs: tvec!(Some(axis), Some(axis), Some(axis)),
outputs: tvec!(Some(axis)),
period: 1,
disposable: true,
})
.collect())
}
}
