Add rewrite to lift SpecifyShape through Elemwise Operations

pytensor/tensor/rewriting/shape.py

@@ -1026,6 +1026,52 @@ def local_Shape_of_SpecifyShape(fgraph, node):
     return [stack(shape).astype(np.int64)]
 
 
+@register_canonicalize
+@register_specialize
+@node_rewriter([SpecifyShape])
+def local_specify_shape_lift(fgraph, node):
+    """Lift SpecifyShape of Elemwise towards the inputs."""
+    inp, *shape = node.inputs
+    if inp.owner and isinstance(inp.owner.op, Elemwise):
+        if len(inp.owner.outputs) != 1:
+            return None
+
+        elem_inps = inp.owner.inputs
+        if len(elem_inps) == 1:
+            new_elem_inps = [specify_shape(elem_inps[0], shape)]
+        else:
+            # Rewrite does not support case where specify_shape provides new broadcastable information,
+            # As that may require a specify_shape for each input
+            out_broadcastable = node.outputs[0].type.broadcastable
+            if out_broadcastable != inp.type.broadcastable:
+                return None
+
+            # All non-broadcastable dimensions of inputs must match the non-broadcastbale specify_shape dims
+            # We look for a sufficient input to assign all the specify_shape dims
+            # We could consider distributing the SpecifyShape across multiple inputs, when none is sufficient
+
+            nonbcast_dims = {
+                i
+                for i, (dim, bcast) in enumerate(zip(shape, out_broadcastable))
+                if (not bcast and not NoneConst.equals(dim))
+            }
+            new_elem_inps = elem_inps.copy()
+            for i, elem_inp in enumerate(elem_inps):
+                if all(
+                    bcast_dim is False
+                    for dim, bcast_dim in enumerate(elem_inp.type.broadcastable)
+                    if dim in nonbcast_dims
+                ):
+                    new_elem_inps[i] = specify_shape(elem_inp, shape)
+                    break
+            else:  # no-break, no sufficient candidate found
+                return None
+
+        new_out = inp.owner.op.make_node(*new_elem_inps).outputs
+        copy_stack_trace(node.outputs, new_out)
+        return new_out
+
+
 @register_useless
 @register_canonicalize
 @node_rewriter([Shape_i])

tests/tensor/rewriting/test_shape.py

@@ -491,6 +491,14 @@ def test_local_Shape_of_SpecifyShape_partial(s1):
     assert not any(isinstance(apply.op, SpecifyShape) for apply in fgraph.apply_nodes)
 
 
+def test_local_specify_shape_lift():
+    x = vector("x")
+    out = specify_shape([1.0] + x, shape=(5,))
+
+    new_out = rewrite_graph(out)
+    assert equal_computations([new_out], [[1.0] + specify_shape(x, shape=(5,))])
+
+
 def test_local_Shape_i_ground():
     x = tensor(dtype=np.float64, shape=(None, 2))
     s = Shape_i(1)(x)