Remove unsquash_pdim

* It was unused and I think it will be replaced by functions that find divisors of the basis

Author: ValerianRey

src/torchjd/sparse/_aten_function_overrides/shape.py

@@ -69,61 +69,6 @@ def infer_shape(shape: list[int], numel: int) -> list[int]:
     return [inferred if s == -1 else s for s in shape]
 
 
-def unsquash_pdim(
-    physical: Tensor, basis: Tensor, pdim: int, new_pdim_shape: list[int]
-) -> tuple[Tensor, Tensor]:
-    """
-    EXAMPLE:
-
-    physical = [
-        [1, 2, 3, 4, 5, 6],
-        [7, 8, 9, 10, 11, 12],
-        [13, 14, 15, 16, 17, 18],
-    ]
-    basis = [
-        [1, 1],
-        [0, 2],
-    ]
-
-    dim = 1
-    shape = [2, 3]
-
-    new_physical = [[
-        [1, 2, 3],
-        [4, 5, 6],
-    ], [
-        [7, 8, 9],
-        [10, 11, 12],
-    ], [
-        [13, 14, 15],
-        [16, 17, 18],
-    ]]
-
-    new_basis = [
-        [1, 3, 1],
-        [0, 6, 2]
-    """
-
-    # TODO: handle working with multiple dimensions at once
-
-    old_shape = list(physical.shape)
-    new_shape = old_shape[:pdim] + new_pdim_shape + old_shape[pdim + 1 :]
-    new_physical = physical.reshape(new_shape)
-
-    multipliers = tensor([prod(new_pdim_shape[i + 1 :]) for i in range(len(new_pdim_shape))])
-
-    new_basis = torch.concat(
-        [
-            basis[:, :pdim],
-            torch.outer(basis[:, pdim], multipliers),
-            basis[:, pdim + 1 :],
-        ],
-        dim=1,
-    )
-
-    return new_physical, new_basis
-
-
 @impl(aten._unsafe_view.default)
 def _unsafe_view_default(t: SparseLatticedTensor, shape: list[int]) -> Tensor:
     return view_default(

tests/unit/sparse/test_sparse_latticed_tensor.py

@@ -10,7 +10,6 @@
     _IN_PLACE_POINTWISE_FUNCTIONS,
     _POINTWISE_FUNCTIONS,
 )
-from torchjd.sparse._aten_function_overrides.shape import unsquash_pdim
 from torchjd.sparse._coalesce import fix_zero_basis_vectors
 from torchjd.sparse._sparse_latticed_tensor import (
     SparseLatticedTensor,
@@ -312,43 +311,6 @@ def test_fix_ungrouped_dims(
     assert torch.equal(fixed_basis, expected_basis)
 
 
-@mark.parametrize(
-    [
-        "physical_shape",
-        "basis",
-        "pdim",
-        "new_pdim_shape",
-        "expected_physical_shape",
-        "expected_basis",
-    ],
-    [
-        ([4], tensor([[1], [2]]), 0, [4], [4], tensor([[1], [2]])),  # trivial
-        ([4], tensor([[1], [2]]), 0, [2, 2], [2, 2], tensor([[2, 1], [4, 2]])),
-        (
-            [3, 4, 5],
-            tensor([[1, 2, 0], [1, 0, 1], [0, 1, 1]]),
-            1,
-            [2, 1, 1, 2],
-            [3, 2, 1, 1, 2, 5],
-            tensor([[1, 4, 4, 4, 2, 0], [1, 0, 0, 0, 0, 1], [0, 2, 2, 2, 1, 1]]),
-        ),
-    ],
-)
-def test_unsquash_pdim(
-    physical_shape: list[int],
-    basis: Tensor,
-    pdim: int,
-    new_pdim_shape: list[int],
-    expected_physical_shape: list[int],
-    expected_basis: Tensor,
-):
-    physical = randn_(physical_shape)
-    new_physical, new_basis = unsquash_pdim(physical, basis, pdim, new_pdim_shape)
-
-    assert list(new_physical.shape) == expected_physical_shape
-    assert torch.equal(new_basis, expected_basis)
-
-
 @mark.parametrize(
     [
         "source",