Canonicalize subtensor slices

Author: Dhruvanshu-Joshi

pytensor/tensor/rewriting/subtensor.py

@@ -367,6 +367,7 @@ def local_useless_slice(fgraph, node):
     # check if we removed something
     if last_useless_slice < len(idxs):
         new_idxs = idxs[:last_useless_slice]
+
         if new_idxs:
             new_subtensor = Subtensor(new_idxs)
             new_subtensor_inputs = get_slice_elements(
@@ -381,6 +382,58 @@ def local_useless_slice(fgraph, node):
             return [node.inputs[0]]
 
 
+@register_useless
+@register_canonicalize
+@register_stabilize
+@register_specialize
+@node_rewriter([Subtensor])
+def local_replace_slice(fgraph, node):
+    """
+    Rewrite Subtensor of the form:
+        X[0:7:1] -> X[None:None:None]
+    where X is a vector of length 7
+
+    """
+    idxs = get_idx_list(node.inputs, node.op.idx_list)
+    x = node.inputs[0]
+
+    if not idxs:
+        return
+
+    new_idxs = list(idxs)
+    idx_flag = False
+    for dim, s in enumerate(new_idxs):
+        if not isinstance(s, slice):
+            continue
+
+        start = s.start
+        stop = s.stop
+        step = s.step
+        if extract_constant(start, only_process_constants=True) == 0:
+            idx_flag = True
+            start = None
+
+        if (
+            x.type.shape[dim] is not None
+            and extract_constant(stop, only_process_constants=True) == x.type.shape[dim]
+        ):
+            idx_flag = True
+            stop = None
+
+        if extract_constant(step, only_process_constants=True) == 1:
+            idx_flag = True
+            step = None
+
+        new_idxs[dim] = slice(start, stop, step)
+
+    if idx_flag is True:
+        out = x[tuple(new_idxs)]
+        # Copy over previous output stacktrace
+        copy_stack_trace(node.outputs, out)
+
+        return [out]
+
+
 # fast_compile to allow opt subtensor(cast{float32}(make_vector))
 @register_canonicalize("fast_compile")
 @node_rewriter([Subtensor])

tests/tensor/rewriting/test_subtensor.py

@@ -10,7 +10,7 @@
 from pytensor.compile.ops import DeepCopyOp
 from pytensor.configdefaults import config
 from pytensor.graph import FunctionGraph, vectorize_graph
-from pytensor.graph.basic import Constant, Variable, ancestors
+from pytensor.graph.basic import Constant, Variable, ancestors, equal_computations
 from pytensor.graph.rewriting.basic import check_stack_trace
 from pytensor.graph.rewriting.db import RewriteDatabaseQuery
 from pytensor.graph.rewriting.utils import rewrite_graph
@@ -2402,3 +2402,24 @@ def test_local_blockwise_advanced_inc_subtensor(set_instead_of_inc):
     else:
         expected_out[:, :, core_idxs] += test_y
     np.testing.assert_allclose(fn(test_x, test_y), expected_out)
+
+
+@pytest.mark.parametrize("fstop, lstop, lstep", [(None, 9, 1), (-1, -1, -1)])
+def test_slice_canonicalize(fstop, lstop, lstep):
+    x = tensor(shape=(3, 5, None, 9))
+    y = x[0:fstop, 0:5, 0:7, 0:lstop:lstep]
+    f = pytensor.function([x], y)
+    test_y = f.maker.fgraph.toposort()
+
+    y1 = x[None:None:None, None:None:None, None:7:None, None:None:None]
+
+    if fstop == -1 and lstop == -1 and lstep == -1:
+        y1 = x[None:-1:None, None:None:None, None:7:None, None:-1:-1]
+
+    f1 = pytensor.function([x], y1)
+    expected_y = f1.maker.fgraph.toposort()
+
+    assert all(
+        equal_computations([x1], [y1])
+        for x1, y1 in zip(test_y[0].inputs, expected_y[0].inputs)
+    )