nabled 0.0.11

//! Arrow adapters for fixed-shape tensor workflows.

use arrow_array::types::{ArrowPrimitiveType, Float64Type};
use arrow_array::{Array, FixedSizeListArray, StructArray};
use arrow_schema::Field;
use arrow_schema::extension::{
    EXTENSION_TYPE_METADATA_KEY, EXTENSION_TYPE_NAME_KEY, ExtensionType, VariableShapeTensor,
};
use nabled_core::scalar::NabledReal;
use ndarray::{ArrayD, ArrayView1, ArrayView2, ArrayView3, ArrayViewD, Ix3};
use ndarrow::NdarrowElement;
use num_complex::Complex64;
use serde::{Deserialize, Serialize};

use super::{
    ArrowInteropError, complex64_fixed_shape_tensor_from_owned, complex64_fixed_shape_tensor_viewd,
    complex64_matrix_from_owned, complex64_matrix_view, fixed_shape_tensor_from_owned,
    fixed_shape_tensor_viewd, fixed_size_list_from_owned, fixed_size_list_view,
    variable_shape_tensor_batch_view,
};

#[derive(Debug, Deserialize, Serialize)]
struct VariableShapeTensorWireMetadata {
    #[serde(default, skip_serializing_if = "Option::is_none")]
    dim_names:     Option<Vec<String>>,
    #[serde(default, skip_serializing_if = "Option::is_none")]
    permutations:  Option<Vec<usize>>,
    #[serde(default, skip_serializing_if = "Option::is_none")]
    uniform_shape: Option<Vec<Option<i32>>>,
}

fn fixed_shape_tensor_view3<'a, T>(
    field: &'a Field,
    array: &'a FixedSizeListArray,
) -> Result<ArrayView3<'a, T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NdarrowElement,
{
    let view = fixed_shape_tensor_viewd::<T>(field, array)?;
    view.into_dimensionality::<Ix3>()
        .map_err(|error: ndarray::ShapeError| ArrowInteropError::InvalidShape(error.to_string()))
}

fn complex64_fixed_shape_tensor_view3<'a>(
    field: &'a Field,
    array: &'a FixedSizeListArray,
) -> Result<ArrayView3<'a, Complex64>, ArrowInteropError> {
    let view = complex64_fixed_shape_tensor_viewd(field, array)?;
    view.into_dimensionality::<Ix3>()
        .map_err(|error: ndarray::ShapeError| ArrowInteropError::InvalidShape(error.to_string()))
}

fn variable_shape_uniform_shape(
    field: &Field,
) -> Result<Option<Vec<Option<i32>>>, ArrowInteropError> {
    let raw_metadata =
        field.extension_type_metadata().ok_or_else(|| ndarrow::NdarrowError::InvalidMetadata {
            message: "arrow.variable_shape_tensor metadata missing".to_owned(),
        })?;
    let metadata: VariableShapeTensorWireMetadata =
        serde_json::from_str(raw_metadata).map_err(|error| {
            ndarrow::NdarrowError::InvalidMetadata {
                message: format!("arrow.variable_shape_tensor metadata parse failed: {error}"),
            }
        })?;
    Ok(metadata.uniform_shape)
}

fn reduced_uniform_shape(mut uniform_shape: Option<Vec<Option<i32>>>) -> Option<Vec<Option<i32>>> {
    if let Some(shape) = &mut uniform_shape {
        let _ = shape.pop();
    }
    uniform_shape
}

fn variable_shape_field_with_metadata(
    field: &Field,
    uniform_shape: Option<Vec<Option<i32>>>,
) -> Result<Field, ArrowInteropError> {
    let metadata_json = serde_json::to_string(&VariableShapeTensorWireMetadata {
        dim_names: None,
        permutations: None,
        uniform_shape,
    })
    .map_err(|error| ndarrow::NdarrowError::InvalidMetadata {
        message: format!("arrow.variable_shape_tensor metadata serialization failed: {error}"),
    })?;
    let mut metadata = field.metadata().clone();
    drop(metadata.insert(EXTENSION_TYPE_NAME_KEY.to_owned(), VariableShapeTensor::NAME.to_owned()));
    drop(metadata.insert(EXTENSION_TYPE_METADATA_KEY.to_owned(), metadata_json));
    Ok(Field::new(field.name(), field.data_type().clone(), field.is_nullable())
        .with_metadata(metadata))
}

fn collect_variable_shape_real_rows<T, F>(
    field: &Field,
    array: &StructArray,
    uniform_shape: Option<Vec<Option<i32>>>,
    mut op: F,
) -> Result<(Field, StructArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
    F: FnMut(&ArrayViewD<'_, T::Native>) -> Result<ArrayD<T::Native>, ArrowInteropError>,
{
    let batch = variable_shape_tensor_batch_view::<T>(field, array)?;
    let mut outputs = Vec::with_capacity(batch.len());
    for row in 0..batch.len() {
        let tensor_view = batch.row(row)?.as_array_viewd()?;
        outputs.push(op(&tensor_view)?);
    }
    Ok(ndarrow::arrays_to_variable_shape_tensor(field.name(), outputs, uniform_shape)?)
}

fn collect_variable_shape_complex_rows<F>(
    field: &Field,
    array: &StructArray,
    uniform_shape: Option<Vec<Option<i32>>>,
    mut op: F,
) -> Result<(Field, StructArray), ArrowInteropError>
where
    F: FnMut(&ArrayViewD<'_, Complex64>) -> Result<ArrayD<Complex64>, ArrowInteropError>,
{
    let mut outputs = Vec::with_capacity(array.len());
    for row in ndarrow::complex64_variable_shape_tensor_iter(field, array)? {
        let (_, tensor_view) = row?;
        outputs.push(op(&tensor_view)?);
    }
    let (field, array) = ndarrow::arrays_complex64_to_variable_shape_tensor(
        field.name(),
        outputs,
        uniform_shape.clone(),
    )?;
    Ok((variable_shape_field_with_metadata(&field, uniform_shape)?, array))
}

fn collect_variable_shape_complex_norm_rows<F>(
    field: &Field,
    array: &StructArray,
    uniform_shape: Option<Vec<Option<i32>>>,
    mut op: F,
) -> Result<(Field, StructArray), ArrowInteropError>
where
    F: FnMut(&ArrayViewD<'_, Complex64>) -> Result<ArrayD<f64>, ArrowInteropError>,
{
    let mut outputs = Vec::with_capacity(array.len());
    for row in ndarrow::complex64_variable_shape_tensor_iter(field, array)? {
        let (_, tensor_view) = row?;
        outputs.push(op(&tensor_view)?);
    }
    Ok(ndarrow::arrays_to_variable_shape_tensor(field.name(), outputs, uniform_shape)?)
}

/// Arrow-facing rank-3 CP-ALS result paired with convergence diagnostics.
pub type ArrowCpAls3WithReport<T> =
    (crate::linalg::tensor::CpAls3Result<T>, crate::linalg::tensor::CpAlsReport<T>);

/// Arrow-facing N-D CP-ALS result paired with convergence diagnostics.
pub type ArrowCpAlsNdWithReport<T> =
    (crate::linalg::tensor::CpAlsNdResult<T>, crate::linalg::tensor::CpAlsReport<T>);

/// Sum over the last axis of a canonical `arrow.fixed_shape_tensor` batch.
///
/// `field` and `array` must come from the same fixed-shape tensor column. The returned field keeps
/// the input field name and carries updated fixed-shape tensor metadata.
///
/// # Errors
/// Returns an error when the input field/array do not represent a valid fixed-shape tensor batch,
/// contain nulls, or the tensor reduction fails.
pub fn sum_last_axis<T>(
    field: &Field,
    array: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement + Default,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    let output = crate::linalg::tensor::sum_last_axis_view(&tensor_view)?;
    fixed_shape_tensor_from_owned::<T>(field.name(), output)
}

/// Compute L2 norms over the last axis of a fixed-shape tensor batch.
///
/// # Errors
/// Returns an error when the input field/array do not represent a valid fixed-shape tensor batch,
/// contain nulls, or the tensor reduction fails.
pub fn l2_norm_last_axis<T>(
    field: &Field,
    array: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement + Default,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    let output = crate::linalg::tensor::l2_norm_last_axis_view(&tensor_view)?;
    fixed_shape_tensor_from_owned::<T>(field.name(), output)
}

/// Normalize a fixed-shape tensor batch over the last axis.
///
/// # Errors
/// Returns an error when the input field/array do not represent a valid fixed-shape tensor batch,
/// contain nulls, or the tensor normalization fails.
pub fn normalize_last_axis<T>(
    field: &Field,
    array: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement + Default,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    let output = crate::linalg::tensor::normalize_last_axis_view(&tensor_view)?;
    fixed_shape_tensor_from_owned::<T>(field.name(), output)
}

/// Compute batched dot products over the last axis of two fixed-shape tensor batches.
///
/// # Errors
/// Returns an error when inputs do not represent valid fixed-shape tensors, contain nulls, or
/// dimensions are incompatible.
pub fn batched_dot_last_axis<T>(
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement + Default,
{
    let left_view = fixed_shape_tensor_viewd::<T>(left_field, left)?;
    let right_view = fixed_shape_tensor_viewd::<T>(right_field, right)?;
    let output = crate::linalg::tensor::batched_dot_last_axis_view(&left_view, &right_view)?;
    fixed_shape_tensor_from_owned::<T>(left_field.name(), output)
}

/// Permute the axes of a fixed-shape tensor batch.
///
/// # Errors
/// Returns an error when the input does not represent a valid fixed-shape tensor batch, contains
/// nulls, or the permutation is invalid.
pub fn permute_axes<T>(
    field: &Field,
    array: &FixedSizeListArray,
    permutation: &[usize],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement + Default,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    let output = crate::linalg::tensor::permute_axes_view(&tensor_view, permutation)?;
    fixed_shape_tensor_from_owned::<T>(field.name(), output)
}

/// Contract two fixed-shape tensors along explicit axis sets.
///
/// # Errors
/// Returns an error when either input is invalid, contains nulls, or contraction axes are
/// incompatible.
pub fn contract_axes<T>(
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
    left_axes: &[usize],
    right_axes: &[usize],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement + Default,
{
    let left_view = fixed_shape_tensor_viewd::<T>(left_field, left)?;
    let right_view = fixed_shape_tensor_viewd::<T>(right_field, right)?;
    let output =
        crate::linalg::tensor::contract_axes_view(&left_view, &right_view, left_axes, right_axes)?;
    fixed_shape_tensor_from_owned::<T>(left_field.name(), output)
}

/// Perform N-D batched matrix multiplication over the last two axes of fixed-shape tensors.
///
/// # Errors
/// Returns an error when either input is invalid, contains nulls, or dimensions are incompatible.
pub fn batched_matmul_last_two<T>(
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement + Default,
{
    let left_view = fixed_shape_tensor_viewd::<T>(left_field, left)?;
    let right_view = fixed_shape_tensor_viewd::<T>(right_field, right)?;
    let output = crate::linalg::tensor::batched_matmul_last_two_view(&left_view, &right_view)?;
    fixed_shape_tensor_from_owned::<T>(left_field.name(), output)
}

/// Compute batched cube-matrix vector products from fixed-shape tensor / Arrow dense inputs.
///
/// `cube` is interpreted as rank-3 `(batch, rows, cols)` tensor data and `vectors` as `(batch,
/// cols)` dense matrix data.
///
/// # Errors
/// Returns an error when inputs are invalid, contain nulls, or dimensions are incompatible.
pub fn cube_matvec<T>(
    cube_field: &Field,
    cube: &FixedSizeListArray,
    vectors: &FixedSizeListArray,
) -> Result<FixedSizeListArray, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let cube_view = fixed_shape_tensor_view3::<T>(cube_field, cube)?;
    let vectors_view = fixed_size_list_view::<T>(vectors)?;
    let output = crate::linalg::tensor::cube_matvec_view(&cube_view, &vectors_view)?;
    fixed_size_list_from_owned::<T>(output)
}

/// Compute batched cube matrix-matrix products from two rank-3 fixed-shape tensors.
///
/// # Errors
/// Returns an error when inputs are invalid, contain nulls, or dimensions are incompatible.
pub fn cube_matmat<T>(
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement + Default,
{
    let left_view = fixed_shape_tensor_view3::<T>(left_field, left)?;
    let right_view = fixed_shape_tensor_view3::<T>(right_field, right)?;
    let output = crate::linalg::tensor::cube_matmat_view(&left_view, &right_view)?;
    fixed_shape_tensor_from_owned::<T>(left_field.name(), output.into_dyn())
}

/// Flatten a rank-3 tensor batch into a dense matrix.
///
/// # Errors
/// Returns an error when the input is not rank-3, contains nulls, or flattening fails.
pub fn flatten_cubes<T>(
    field: &Field,
    array: &FixedSizeListArray,
) -> Result<FixedSizeListArray, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let cube_view = fixed_shape_tensor_view3::<T>(field, array)?;
    let output = crate::linalg::tensor::flatten_cubes_view(&cube_view)?;
    fixed_size_list_from_owned::<T>(output)
}

/// Sum over the last axis of a canonical `arrow.variable_shape_tensor` batch.
///
/// # Errors
/// Returns an error when the input field/array do not represent a valid variable-shape tensor
/// batch, contain nulls, or the tensor reduction fails.
pub fn sum_last_axis_variable<T>(
    field: &Field,
    array: &StructArray,
) -> Result<(Field, StructArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement + Default,
{
    let uniform_shape = reduced_uniform_shape(variable_shape_uniform_shape(field)?);
    collect_variable_shape_real_rows::<T, _>(field, array, uniform_shape, |tensor_view| {
        Ok(crate::linalg::tensor::sum_last_axis_view(tensor_view)?)
    })
}

/// Compute L2 norms over the last axis of a variable-shape tensor batch.
///
/// # Errors
/// Returns an error when the input field/array do not represent a valid variable-shape tensor
/// batch, contain nulls, or the tensor reduction fails.
pub fn l2_norm_last_axis_variable<T>(
    field: &Field,
    array: &StructArray,
) -> Result<(Field, StructArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let uniform_shape = reduced_uniform_shape(variable_shape_uniform_shape(field)?);
    collect_variable_shape_real_rows::<T, _>(field, array, uniform_shape, |tensor_view| {
        Ok(crate::linalg::tensor::l2_norm_last_axis_view(tensor_view)?)
    })
}

/// Normalize a variable-shape tensor batch over the last axis.
///
/// # Errors
/// Returns an error when the input field/array do not represent a valid variable-shape tensor
/// batch, contain nulls, or normalization fails.
pub fn normalize_last_axis_variable<T>(
    field: &Field,
    array: &StructArray,
) -> Result<(Field, StructArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let uniform_shape = variable_shape_uniform_shape(field)?;
    collect_variable_shape_real_rows::<T, _>(field, array, uniform_shape, |tensor_view| {
        Ok(crate::linalg::tensor::normalize_last_axis_view(tensor_view)?)
    })
}

/// Compute batched dot products over the last axis of two variable-shape tensor batches.
///
/// # Errors
/// Returns an error when inputs do not represent valid variable-shape tensors, contain nulls, or
/// dimensions are incompatible.
pub fn batched_dot_last_axis_variable<T>(
    left_field: &Field,
    left: &StructArray,
    right_field: &Field,
    right: &StructArray,
) -> Result<(Field, StructArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    if left.len() != right.len() {
        return Err(ArrowInteropError::InvalidShape(format!(
            "variable-shape tensor batch row count mismatch: {} vs {}",
            left.len(),
            right.len()
        )));
    }

    let uniform_shape = reduced_uniform_shape(variable_shape_uniform_shape(left_field)?);
    let left_batch = variable_shape_tensor_batch_view::<T>(left_field, left)?;
    let right_batch = variable_shape_tensor_batch_view::<T>(right_field, right)?;
    let mut outputs = Vec::with_capacity(left_batch.len());
    for row in 0..left_batch.len() {
        let left_view = left_batch.row(row)?.as_array_viewd()?;
        let right_view = right_batch.row(row)?.as_array_viewd()?;
        outputs.push(crate::linalg::tensor::batched_dot_last_axis_view(&left_view, &right_view)?);
    }
    Ok(ndarrow::arrays_to_variable_shape_tensor(left_field.name(), outputs, uniform_shape)?)
}

/// Sum over the last axis of a complex fixed-shape tensor batch.
///
/// # Errors
/// Returns an error when the tensor metadata is invalid, contains nulls, or the reduction fails.
pub fn sum_last_axis_complex(
    field: &Field,
    array: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError> {
    let tensor_view = complex64_fixed_shape_tensor_viewd(field, array)?;
    let output = crate::linalg::tensor::sum_last_axis_complex_view(&tensor_view)?;
    complex64_fixed_shape_tensor_from_owned(field.name(), output)
}

/// Sum over the last axis of a complex variable-shape tensor batch.
///
/// # Errors
/// Returns an error when the tensor metadata is invalid, contains nulls, or the reduction fails.
pub fn sum_last_axis_variable_complex(
    field: &Field,
    array: &StructArray,
) -> Result<(Field, StructArray), ArrowInteropError> {
    let uniform_shape = reduced_uniform_shape(variable_shape_uniform_shape(field)?);
    collect_variable_shape_complex_rows(field, array, uniform_shape, |tensor_view| {
        Ok(crate::linalg::tensor::sum_last_axis_complex_view(tensor_view)?)
    })
}

/// Compute L2 norms over the last axis of a complex fixed-shape tensor batch.
///
/// # Errors
/// Returns an error when the tensor metadata is invalid, contains nulls, or the reduction fails.
pub fn l2_norm_last_axis_complex(
    field: &Field,
    array: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError> {
    let tensor_view = complex64_fixed_shape_tensor_viewd(field, array)?;
    let output = crate::linalg::tensor::l2_norm_last_axis_complex_view(&tensor_view)?;
    fixed_shape_tensor_from_owned::<Float64Type>(field.name(), output)
}

/// Compute L2 norms over the last axis of a complex variable-shape tensor batch.
///
/// # Errors
/// Returns an error when the tensor metadata is invalid, contains nulls, or the reduction fails.
pub fn l2_norm_last_axis_variable_complex(
    field: &Field,
    array: &StructArray,
) -> Result<(Field, StructArray), ArrowInteropError> {
    let uniform_shape = reduced_uniform_shape(variable_shape_uniform_shape(field)?);
    collect_variable_shape_complex_norm_rows(field, array, uniform_shape, |tensor_view| {
        Ok(crate::linalg::tensor::l2_norm_last_axis_complex_view(tensor_view)?)
    })
}

/// Normalize a complex fixed-shape tensor batch over the last axis.
///
/// # Errors
/// Returns an error when the tensor metadata is invalid, contains nulls, or normalization fails.
pub fn normalize_last_axis_complex(
    field: &Field,
    array: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError> {
    let tensor_view = complex64_fixed_shape_tensor_viewd(field, array)?;
    let output = crate::linalg::tensor::normalize_last_axis_complex_view(&tensor_view)?;
    complex64_fixed_shape_tensor_from_owned(field.name(), output)
}

/// Normalize a complex variable-shape tensor batch over the last axis.
///
/// # Errors
/// Returns an error when the tensor metadata is invalid, contains nulls, or normalization fails.
pub fn normalize_last_axis_variable_complex(
    field: &Field,
    array: &StructArray,
) -> Result<(Field, StructArray), ArrowInteropError> {
    let uniform_shape = variable_shape_uniform_shape(field)?;
    collect_variable_shape_complex_rows(field, array, uniform_shape, |tensor_view| {
        Ok(crate::linalg::tensor::normalize_last_axis_complex_view(tensor_view)?)
    })
}

/// Compute batched complex dot products over the last axis of two fixed-shape tensor batches.
///
/// # Errors
/// Returns an error when either tensor is invalid, contains nulls, or shapes are incompatible.
pub fn batched_dot_last_axis_complex(
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError> {
    let left_view = complex64_fixed_shape_tensor_viewd(left_field, left)?;
    let right_view = complex64_fixed_shape_tensor_viewd(right_field, right)?;
    let output =
        crate::linalg::tensor::batched_dot_last_axis_complex_view(&left_view, &right_view)?;
    complex64_fixed_shape_tensor_from_owned(left_field.name(), output)
}

/// Compute batched complex dot products over the last axis of two variable-shape tensor batches.
///
/// # Errors
/// Returns an error when either tensor is invalid, contains nulls, or shapes are incompatible.
pub fn batched_dot_last_axis_variable_complex(
    left_field: &Field,
    left: &StructArray,
    right_field: &Field,
    right: &StructArray,
) -> Result<(Field, StructArray), ArrowInteropError> {
    if left.len() != right.len() {
        return Err(ArrowInteropError::InvalidShape(format!(
            "variable-shape tensor batch row count mismatch: {} vs {}",
            left.len(),
            right.len()
        )));
    }

    let uniform_shape = reduced_uniform_shape(variable_shape_uniform_shape(left_field)?);
    let mut outputs = Vec::with_capacity(left.len());
    let mut right_iter = ndarrow::complex64_variable_shape_tensor_iter(right_field, right)?;
    for left_row in ndarrow::complex64_variable_shape_tensor_iter(left_field, left)? {
        let (_, left_view) = left_row?;
        let (_, right_view) = right_iter.next().ok_or_else(|| {
            ArrowInteropError::InvalidShape(
                "variable-shape tensor batch iterator ended early".to_owned(),
            )
        })??;
        outputs.push(crate::linalg::tensor::batched_dot_last_axis_complex_view(
            &left_view,
            &right_view,
        )?);
    }
    Ok(ndarrow::arrays_complex64_to_variable_shape_tensor(
        left_field.name(),
        outputs,
        uniform_shape,
    )?)
}

/// Permute the axes of a complex fixed-shape tensor batch.
///
/// # Errors
/// Returns an error when the tensor is invalid, contains nulls, or the permutation is invalid.
pub fn permute_axes_complex(
    field: &Field,
    array: &FixedSizeListArray,
    permutation: &[usize],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError> {
    let tensor_view = complex64_fixed_shape_tensor_viewd(field, array)?;
    let output = crate::linalg::tensor::permute_axes_complex_view(&tensor_view, permutation)?;
    complex64_fixed_shape_tensor_from_owned(field.name(), output)
}

/// Contract two complex fixed-shape tensors along explicit axis sets.
///
/// # Errors
/// Returns an error when either tensor is invalid, contains nulls, or contraction axes mismatch.
pub fn contract_axes_complex(
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
    left_axes: &[usize],
    right_axes: &[usize],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError> {
    let left_view = complex64_fixed_shape_tensor_viewd(left_field, left)?;
    let right_view = complex64_fixed_shape_tensor_viewd(right_field, right)?;
    let output = crate::linalg::tensor::contract_axes_complex_view(
        &left_view,
        &right_view,
        left_axes,
        right_axes,
    )?;
    complex64_fixed_shape_tensor_from_owned(left_field.name(), output)
}

/// Perform N-D batched complex matrix multiplication over the last two axes.
///
/// # Errors
/// Returns an error when either tensor is invalid, contains nulls, or dimensions mismatch.
pub fn batched_matmul_last_two_complex(
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError> {
    let left_view = complex64_fixed_shape_tensor_viewd(left_field, left)?;
    let right_view = complex64_fixed_shape_tensor_viewd(right_field, right)?;
    let output =
        crate::linalg::tensor::batched_matmul_last_two_complex_view(&left_view, &right_view)?;
    complex64_fixed_shape_tensor_from_owned(left_field.name(), output)
}

/// Compute batched complex cube-matrix vector products from Arrow inputs.
///
/// # Errors
/// Returns an error when inputs are invalid, contain nulls, or dimensions mismatch.
pub fn cube_matvec_complex(
    cube_field: &Field,
    cube: &FixedSizeListArray,
    vectors: &FixedSizeListArray,
) -> Result<FixedSizeListArray, ArrowInteropError> {
    let cube_view = complex64_fixed_shape_tensor_view3(cube_field, cube)?;
    let vectors_view = complex64_matrix_view(vectors)?;
    let output = crate::linalg::tensor::cube_matvec_complex_view(&cube_view, &vectors_view)?;
    complex64_matrix_from_owned(output)
}

/// Compute batched complex cube matrix-matrix products from Arrow inputs.
///
/// # Errors
/// Returns an error when inputs are invalid, contain nulls, or dimensions mismatch.
pub fn cube_matmat_complex(
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError> {
    let left_view = complex64_fixed_shape_tensor_view3(left_field, left)?;
    let right_view = complex64_fixed_shape_tensor_view3(right_field, right)?;
    let output = crate::linalg::tensor::cube_matmat_complex_view(&left_view, &right_view)?;
    complex64_fixed_shape_tensor_from_owned(left_field.name(), output.into_dyn())
}

/// Evaluate two-operand Einstein summation over real fixed-shape tensors.
///
/// # Errors
/// Returns an error when expression syntax is invalid or the tensor shapes mismatch.
pub fn einsum<T>(
    expression: &str,
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let left_view = fixed_shape_tensor_viewd::<T>(left_field, left)?;
    let right_view = fixed_shape_tensor_viewd::<T>(right_field, right)?;
    let output = crate::linalg::tensor::einsum_view(expression, &left_view, &right_view)?;
    fixed_shape_tensor_from_owned::<T>(left_field.name(), output)
}

/// Evaluate two-operand Einstein summation over complex fixed-shape tensors.
///
/// # Errors
/// Returns an error when expression syntax is invalid or the tensor shapes mismatch.
pub fn einsum_complex(
    expression: &str,
    left_field: &Field,
    left: &FixedSizeListArray,
    right_field: &Field,
    right: &FixedSizeListArray,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError> {
    let left_view = complex64_fixed_shape_tensor_viewd(left_field, left)?;
    let right_view = complex64_fixed_shape_tensor_viewd(right_field, right)?;
    let output = crate::linalg::tensor::einsum_complex_view(expression, &left_view, &right_view)?;
    complex64_fixed_shape_tensor_from_owned(left_field.name(), output)
}

/// Compute rank-`R` CP decomposition for a rank-3 tensor from Arrow fixed-shape tensor input.
///
/// # Errors
/// Returns an error when the tensor is not rank-3, contains nulls, or ALS fails.
pub fn cp_als3<T>(
    field: &Field,
    array: &FixedSizeListArray,
    rank: usize,
    config: &crate::linalg::tensor::CpAlsConfig<T::Native>,
) -> Result<crate::linalg::tensor::CpAls3Result<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: crate::linalg::tensor::CpAlsScalar + NdarrowElement,
{
    let cube_view = fixed_shape_tensor_view3::<T>(field, array)?;
    Ok(crate::linalg::tensor::cp_als3_view(&cube_view, rank, config)?)
}

/// Compute rank-`R` CP decomposition plus diagnostics for a rank-3 Arrow tensor input.
///
/// # Errors
/// Returns an error when the tensor is not rank-3, contains nulls, or ALS fails.
pub fn cp_als3_with_report<T>(
    field: &Field,
    array: &FixedSizeListArray,
    rank: usize,
    config: &crate::linalg::tensor::CpAlsConfig<T::Native>,
) -> Result<ArrowCpAls3WithReport<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: crate::linalg::tensor::CpAlsScalar + NdarrowElement,
{
    let cube_view = fixed_shape_tensor_view3::<T>(field, array)?;
    Ok(crate::linalg::tensor::cp_als3_view_with_report(&cube_view, rank, config)?)
}

/// Compute reconstruction diagnostics for a rank-3 CP decomposition against an Arrow tensor.
///
/// # Errors
/// Returns an error when the tensor is not rank-3, contains nulls, or dimensions mismatch.
pub fn cp_als3_diagnostics<T>(
    field: &Field,
    array: &FixedSizeListArray,
    result: &crate::linalg::tensor::CpAls3Result<T::Native>,
) -> Result<crate::linalg::tensor::CpErrorMetrics<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    cp_als3_diagnostics_from_factors_view::<T>(
        field,
        array,
        &result.weights.view(),
        &result.factor_0.view(),
        &result.factor_1.view(),
        &result.factor_2.view(),
    )
}

/// Compute reconstruction diagnostics for a rank-3 CP decomposition from borrowed factors.
///
/// # Errors
/// Returns an error when the tensor is not rank-3, contains nulls, or dimensions mismatch.
pub fn cp_als3_diagnostics_from_factors_view<T>(
    field: &Field,
    array: &FixedSizeListArray,
    weights: &ArrayView1<'_, T::Native>,
    factor_0: &ArrayView2<'_, T::Native>,
    factor_1: &ArrayView2<'_, T::Native>,
    factor_2: &ArrayView2<'_, T::Native>,
) -> Result<crate::linalg::tensor::CpErrorMetrics<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let cube_view = fixed_shape_tensor_view3::<T>(field, array)?;
    Ok(crate::linalg::tensor::cp_als3_diagnostics_from_factors_view(
        &cube_view, weights, factor_0, factor_1, factor_2,
    )?)
}

/// Reconstruct a rank-3 tensor from CP factors into Arrow fixed-shape tensor form.
///
/// # Errors
/// Returns an error when factor dimensions are incompatible.
pub fn cp_als3_reconstruct<T>(
    field_name: &str,
    result: &crate::linalg::tensor::CpAls3Result<T::Native>,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    cp_als3_reconstruct_from_factors_view::<T>(
        field_name,
        &result.weights.view(),
        &result.factor_0.view(),
        &result.factor_1.view(),
        &result.factor_2.view(),
    )
}

/// Reconstruct a rank-3 tensor from borrowed CP factors into Arrow fixed-shape tensor form.
///
/// # Errors
/// Returns an error when factor dimensions are incompatible.
pub fn cp_als3_reconstruct_from_factors_view<T>(
    field_name: &str,
    weights: &ArrayView1<'_, T::Native>,
    factor_0: &ArrayView2<'_, T::Native>,
    factor_1: &ArrayView2<'_, T::Native>,
    factor_2: &ArrayView2<'_, T::Native>,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let output = crate::linalg::tensor::cp_als3_reconstruct_from_factors_view(
        weights, factor_0, factor_1, factor_2,
    )?;
    fixed_shape_tensor_from_owned::<T>(field_name, output.into_dyn())
}

/// Compute rank-`R` CP decomposition for an `N`-D tensor from Arrow fixed-shape tensor input.
///
/// # Errors
/// Returns an error when the tensor is invalid, contains nulls, or ALS fails.
pub fn cp_als_nd<T>(
    field: &Field,
    array: &FixedSizeListArray,
    rank: usize,
    config: &crate::linalg::tensor::CpAlsConfig<T::Native>,
) -> Result<crate::linalg::tensor::CpAlsNdResult<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: crate::linalg::tensor::CpAlsScalar + NdarrowElement,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    Ok(crate::linalg::tensor::cp_als_nd_view(&tensor_view, rank, config)?)
}

/// Compute rank-`R` CP decomposition plus diagnostics for an `N`-D Arrow tensor input.
///
/// # Errors
/// Returns an error when the tensor is invalid, contains nulls, or ALS fails.
pub fn cp_als_nd_with_report<T>(
    field: &Field,
    array: &FixedSizeListArray,
    rank: usize,
    config: &crate::linalg::tensor::CpAlsConfig<T::Native>,
) -> Result<ArrowCpAlsNdWithReport<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: crate::linalg::tensor::CpAlsScalar + NdarrowElement,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    Ok(crate::linalg::tensor::cp_als_nd_view_with_report(&tensor_view, rank, config)?)
}

/// Compute reconstruction diagnostics for an `N`-D CP decomposition against an Arrow tensor.
///
/// # Errors
/// Returns an error when the tensor is invalid, contains nulls, or dimensions mismatch.
pub fn cp_als_nd_diagnostics<T>(
    field: &Field,
    array: &FixedSizeListArray,
    result: &crate::linalg::tensor::CpAlsNdResult<T::Native>,
) -> Result<crate::linalg::tensor::CpErrorMetrics<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    cp_als_nd_diagnostics_from_factors_view::<T>(
        field,
        array,
        &result.weights.view(),
        &result.factors.iter().map(|factor| factor.view()).collect::<Vec<_>>(),
    )
}

/// Compute reconstruction diagnostics for an `N`-D CP decomposition from borrowed factors.
///
/// # Errors
/// Returns an error when the tensor is invalid, contains nulls, or dimensions mismatch.
pub fn cp_als_nd_diagnostics_from_factors_view<T>(
    field: &Field,
    array: &FixedSizeListArray,
    weights: &ArrayView1<'_, T::Native>,
    factors: &[ArrayView2<'_, T::Native>],
) -> Result<crate::linalg::tensor::CpErrorMetrics<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    Ok(crate::linalg::tensor::cp_als_nd_diagnostics_from_factors_view(
        &tensor_view,
        weights,
        factors,
    )?)
}

/// Reconstruct an `N`-D tensor from CP factors into Arrow fixed-shape tensor form.
///
/// # Errors
/// Returns an error when factor dimensions are incompatible.
pub fn cp_als_nd_reconstruct<T>(
    field_name: &str,
    result: &crate::linalg::tensor::CpAlsNdResult<T::Native>,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    cp_als_nd_reconstruct_from_factors_view::<T>(
        field_name,
        &result.weights.view(),
        &result.factors.iter().map(|factor| factor.view()).collect::<Vec<_>>(),
    )
}

/// Reconstruct an `N`-D tensor from borrowed CP factors into Arrow fixed-shape tensor form.
///
/// # Errors
/// Returns an error when factor dimensions are incompatible.
pub fn cp_als_nd_reconstruct_from_factors_view<T>(
    field_name: &str,
    weights: &ArrayView1<'_, T::Native>,
    factors: &[ArrayView2<'_, T::Native>],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let output = crate::linalg::tensor::cp_als_nd_reconstruct_from_factors_view(weights, factors)?;
    fixed_shape_tensor_from_owned::<T>(field_name, output)
}

/// Compute rank-truncated `N`-D HOSVD from Arrow fixed-shape tensor input.
///
/// # Errors
/// Returns an error when the tensor is invalid, contains nulls, or factorization fails.
pub fn hosvd_nd<T>(
    field: &Field,
    array: &FixedSizeListArray,
    ranks: &[usize],
) -> Result<crate::linalg::tensor::HosvdNdResult<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: crate::linalg::tensor::HosvdNdScalar + NdarrowElement,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    Ok(crate::linalg::tensor::hosvd_nd_view(&tensor_view, ranks)?)
}

/// Compute rank-truncated `N`-D Tucker decomposition via HOOI from Arrow tensor input.
///
/// # Errors
/// Returns an error when the tensor is invalid, contains nulls, or factorization fails.
pub fn hooi_nd<T>(
    field: &Field,
    array: &FixedSizeListArray,
    ranks: &[usize],
    config: &crate::linalg::tensor::HooiConfig<T::Native>,
) -> Result<crate::linalg::tensor::HosvdNdResult<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: crate::linalg::tensor::HooiNdScalar + NdarrowElement,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    Ok(crate::linalg::tensor::hooi_nd_view(&tensor_view, ranks, config)?)
}

/// Project an Arrow tensor into a Tucker core using ndarray-native factor matrices.
///
/// # Errors
/// Returns an error when tensor/factor dimensions are incompatible.
pub fn tucker_project<T>(
    field: &Field,
    array: &FixedSizeListArray,
    factors: &[ndarray::Array2<T::Native>],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    tucker_project_from_factors_view::<T>(
        field,
        array,
        &factors.iter().map(|factor| factor.view()).collect::<Vec<_>>(),
    )
}

/// Project an Arrow tensor into a Tucker core using borrowed per-mode factor views.
///
/// # Errors
/// Returns an error when tensor/factor dimensions are incompatible.
pub fn tucker_project_from_factors_view<T>(
    field: &Field,
    array: &FixedSizeListArray,
    factors: &[ArrayView2<'_, T::Native>],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    let output = crate::linalg::tensor::tucker_project_from_factors_view(&tensor_view, factors)?;
    fixed_shape_tensor_from_owned::<T>(field.name(), output)
}

/// Expand a Tucker core from Arrow into the original tensor space.
///
/// # Errors
/// Returns an error when core/factor dimensions are incompatible.
pub fn tucker_expand<T>(
    field: &Field,
    array: &FixedSizeListArray,
    factors: &[ndarray::Array2<T::Native>],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    tucker_expand_from_factors_view::<T>(
        field,
        array,
        &factors.iter().map(|factor| factor.view()).collect::<Vec<_>>(),
    )
}

/// Expand a Tucker core from Arrow into the original tensor space using borrowed factors.
///
/// # Errors
/// Returns an error when core/factor dimensions are incompatible.
pub fn tucker_expand_from_factors_view<T>(
    field: &Field,
    array: &FixedSizeListArray,
    factors: &[ArrayView2<'_, T::Native>],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    let output = crate::linalg::tensor::tucker_expand_from_factors_view(&tensor_view, factors)?;
    fixed_shape_tensor_from_owned::<T>(field.name(), output)
}

/// Reconstruct an `N`-D tensor from an ndarray-native HOSVD/Tucker result.
///
/// # Errors
/// Returns an error when factor dimensions are incompatible.
pub fn hosvd_nd_reconstruct<T>(
    field_name: &str,
    result: &crate::linalg::tensor::HosvdNdResult<T::Native>,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    hosvd_nd_reconstruct_from_factors_view::<T>(
        field_name,
        &result.core.view(),
        &result.factors.iter().map(|factor| factor.view()).collect::<Vec<_>>(),
    )
}

/// Reconstruct an `N`-D tensor from borrowed HOSVD/Tucker factors.
///
/// # Errors
/// Returns an error when factor dimensions are incompatible.
pub fn hosvd_nd_reconstruct_from_factors_view<T>(
    field_name: &str,
    core: &ArrayViewD<'_, T::Native>,
    factors: &[ArrayView2<'_, T::Native>],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let output = crate::linalg::tensor::hosvd_nd_reconstruct_from_factors_view(core, factors)?;
    fixed_shape_tensor_from_owned::<T>(field_name, output)
}

/// Compute Tensor-Train decomposition from Arrow fixed-shape tensor input.
///
/// # Errors
/// Returns an error when the tensor is invalid, contains nulls, or decomposition fails.
pub fn tt_svd<T>(
    field: &Field,
    array: &FixedSizeListArray,
    config: &crate::linalg::tensor::TtSvdConfig<T::Native>,
) -> Result<crate::linalg::tensor::TensorTrainResult<T::Native>, ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: crate::linalg::tensor::TtSvdScalar + NdarrowElement,
{
    let tensor_view = fixed_shape_tensor_viewd::<T>(field, array)?;
    Ok(crate::linalg::tensor::tt_svd_view(&tensor_view, config)?)
}

/// Left-orthogonalize a Tensor-Train result.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible.
pub fn tt_orthogonalize_left<T: crate::linalg::tensor::TtSvdScalar>(
    result: &crate::linalg::tensor::TensorTrainResult<T>,
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_orthogonalize_left(result)?)
}

/// Left-orthogonalize borrowed TT cores.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible.
pub fn tt_orthogonalize_left_from_cores_view<T: crate::linalg::tensor::TtSvdScalar>(
    cores: &[ArrayView3<'_, T>],
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_orthogonalize_left_from_cores_view(cores)?)
}

/// Right-orthogonalize a Tensor-Train result.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible.
pub fn tt_orthogonalize_right<T: crate::linalg::tensor::TtSvdScalar>(
    result: &crate::linalg::tensor::TensorTrainResult<T>,
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_orthogonalize_right(result)?)
}

/// Right-orthogonalize borrowed TT cores.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible.
pub fn tt_orthogonalize_right_from_cores_view<T: crate::linalg::tensor::TtSvdScalar>(
    cores: &[ArrayView3<'_, T>],
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_orthogonalize_right_from_cores_view(cores)?)
}

/// Round/compress a Tensor-Train result.
///
/// # Errors
/// Returns an error when TT core dimensions or configuration are invalid.
pub fn tt_round<T: crate::linalg::tensor::TtSvdScalar>(
    result: &crate::linalg::tensor::TensorTrainResult<T>,
    config: &crate::linalg::tensor::TtRoundConfig<T>,
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_round(result, config)?)
}

/// Round/compress borrowed TT cores.
///
/// # Errors
/// Returns an error when TT core dimensions or configuration are invalid.
pub fn tt_round_from_cores_view<T: crate::linalg::tensor::TtSvdScalar>(
    cores: &[ArrayView3<'_, T>],
    config: &crate::linalg::tensor::TtRoundConfig<T>,
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_round_from_cores_view(cores, config)?)
}

/// Compute inner product of two Tensor-Train tensors.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible or shapes mismatch.
pub fn tt_inner<T: NabledReal>(
    left: &crate::linalg::tensor::TensorTrainResult<T>,
    right: &crate::linalg::tensor::TensorTrainResult<T>,
) -> Result<T, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_inner(left, right)?)
}

/// Compute inner product of two borrowed TT tensors.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible or shapes mismatch.
pub fn tt_inner_from_cores_view<T: NabledReal>(
    left: &[ArrayView3<'_, T>],
    right: &[ArrayView3<'_, T>],
) -> Result<T, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_inner_from_cores_view(left, right)?)
}

/// Compute Frobenius norm of a Tensor-Train tensor.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible.
pub fn tt_norm<T: NabledReal>(
    result: &crate::linalg::tensor::TensorTrainResult<T>,
) -> Result<T, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_norm(result)?)
}

/// Compute Frobenius norm of borrowed TT cores.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible.
pub fn tt_norm_from_cores_view<T: NabledReal>(
    cores: &[ArrayView3<'_, T>],
) -> Result<T, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_norm_from_cores_view(cores)?)
}

/// Add two Tensor-Train tensors.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible or shapes mismatch.
pub fn tt_add<T: NabledReal>(
    left: &crate::linalg::tensor::TensorTrainResult<T>,
    right: &crate::linalg::tensor::TensorTrainResult<T>,
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_add(left, right)?)
}

/// Add two borrowed TT tensors.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible or shapes mismatch.
pub fn tt_add_from_cores_view<T: NabledReal>(
    left: &[ArrayView3<'_, T>],
    right: &[ArrayView3<'_, T>],
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_add_from_cores_view(left, right)?)
}

/// Compute elementwise Hadamard product of two Tensor-Train tensors.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible or shapes mismatch.
pub fn tt_hadamard<T: NabledReal>(
    left: &crate::linalg::tensor::TensorTrainResult<T>,
    right: &crate::linalg::tensor::TensorTrainResult<T>,
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_hadamard(left, right)?)
}

/// Compute elementwise Hadamard product of two borrowed TT tensors.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible or shapes mismatch.
pub fn tt_hadamard_from_cores_view<T: NabledReal>(
    left: &[ArrayView3<'_, T>],
    right: &[ArrayView3<'_, T>],
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_hadamard_from_cores_view(left, right)?)
}

/// Compute Hadamard product followed by TT rank-rounding.
///
/// # Errors
/// Returns an error when TT core dimensions/configuration are invalid.
pub fn tt_hadamard_round<T: crate::linalg::tensor::TtSvdScalar>(
    left: &crate::linalg::tensor::TensorTrainResult<T>,
    right: &crate::linalg::tensor::TensorTrainResult<T>,
    config: &crate::linalg::tensor::TtRoundConfig<T>,
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_hadamard_round(left, right, config)?)
}

/// Compute Hadamard product of borrowed TT cores followed by TT rounding.
///
/// # Errors
/// Returns an error when TT core dimensions/configuration are invalid.
pub fn tt_hadamard_round_from_cores_view<T: crate::linalg::tensor::TtSvdScalar>(
    left: &[ArrayView3<'_, T>],
    right: &[ArrayView3<'_, T>],
    config: &crate::linalg::tensor::TtRoundConfig<T>,
) -> Result<crate::linalg::tensor::TensorTrainResult<T>, ArrowInteropError> {
    Ok(crate::linalg::tensor::tt_hadamard_round_from_cores_view(left, right, config)?)
}

/// Reconstruct an `N`-D tensor from Tensor-Train cores into Arrow fixed-shape tensor form.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible.
pub fn tt_svd_reconstruct<T>(
    field_name: &str,
    result: &crate::linalg::tensor::TensorTrainResult<T::Native>,
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let output = crate::linalg::tensor::tt_svd_reconstruct(result)?;
    fixed_shape_tensor_from_owned::<T>(field_name, output)
}

/// Reconstruct an `N`-D tensor from borrowed TT cores into Arrow fixed-shape tensor form.
///
/// # Errors
/// Returns an error when TT core dimensions are incompatible.
pub fn tt_svd_reconstruct_from_cores_view<T>(
    field_name: &str,
    cores: &[ArrayView3<'_, T::Native>],
) -> Result<(Field, FixedSizeListArray), ArrowInteropError>
where
    T: ArrowPrimitiveType,
    T::Native: NabledReal + NdarrowElement,
{
    let output = crate::linalg::tensor::tt_svd_reconstruct_from_cores_view(cores)?;
    fixed_shape_tensor_from_owned::<T>(field_name, output)
}