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use crate::internal::*;

use super::RmDims;

#[derive(Debug, Clone, new, Default)]
pub struct Squeeze {
    axes: Option<Vec<usize>>,
}

impl Squeeze {
    fn compute_shape<D: DimLike>(&self, input: &[D]) -> TractResult<TVec<D>> {
        if let Some(ref axes) = self.axes {
            let mut shape: TVec<D> = input.iter().cloned().collect();
            for &axis in axes.iter().rev() {
                if shape.remove(axis) != D::one() {
                    bail!("Attempt to squeeze an axis which dimension in not one");
                }
            }
            Ok(shape)
        } else {
            Ok(input.into_iter().filter(|&d| d != &D::one()).cloned().collect())
        }
    }

    /// Evaluates the operation given the input tensors.
    fn eval_t<T: Datum>(&self, input: Arc<Tensor>) -> TractResult<TVec<Arc<Tensor>>> {
        let shape = self.compute_shape(input.shape())?;
        Ok(tvec![input.into_tensor().into_array::<T>()?.into_shape(&*shape)?.into_arc_tensor()])
    }
}

impl Op for Squeeze {
    fn name(&self) -> Cow<str> {
        "Squeeze".into()
    }

    fn declutter(
        &self,
        model: &TypedModel,
        node: &TypedNode,
    ) -> TractResult<Option<TypedModelPatch>> {
        if let Some(dims) = &self.axes {
            return Ok(Some(TypedModelPatch::single_unary_op(
                model,
                node,
                RmDims::new(dims.clone()),
            )?));
        }
        Ok(None)
    }

    op_as_typed_op!();
}

impl StatelessOp for Squeeze {
    /// Evaluates the operation given the input tensors.
    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 Squeeze {
    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)?;
        if let Some(ref axes) = self.axes {
            s.equals(&outputs[0].rank, (&inputs[0].rank).bex() - axes.len() as i32)?;
        }
        s.given(&inputs[0].shape, move |s, shape| {
            let output_shape = self.compute_shape(&shape)?;
            s.equals(&outputs[0].shape, output_shape)
        })
    }

    inference_op_as_op!();
    to_typed!();
}

impl TypedOp for Squeeze {
    typed_op_as_op!();

    fn output_facts(&self, inputs: &[&TypedTensorInfo]) -> TractResult<TVec<TypedTensorInfo>> {
        Ok(tvec!(TypedTensorInfo::dt_shape(
            inputs[0].datum_type,
            &*self.compute_shape(&*inputs[0].shape.to_tvec())?,
        )?))
    }
}