Render inner-graphs of Composite Ops in debugprint

Author: ricardoV94

pytensor/printing.py

@@ -302,7 +302,11 @@ def debugprint(
     ):
 
         if hasattr(var.owner, "op"):
-            if isinstance(var.owner.op, HasInnerGraph) and var not in inner_graph_vars:
+            if (
+                isinstance(var.owner.op, HasInnerGraph)
+                or hasattr(var.owner.op, "scalar_op")
+                and isinstance(var.owner.op.scalar_op, HasInnerGraph)
+            ) and var not in inner_graph_vars:
                 inner_graph_vars.append(var)
             if print_op_info:
                 op_information.update(op_debug_information(var.owner.op, var.owner))
@@ -345,8 +349,12 @@ def debugprint(
                 inner_inputs = inner_fn.maker.fgraph.inputs
                 inner_outputs = inner_fn.maker.fgraph.outputs
             else:
-                inner_inputs = ig_var.owner.op.inner_inputs
-                inner_outputs = ig_var.owner.op.inner_outputs
+                if hasattr(ig_var.owner.op, "scalar_op"):
+                    inner_inputs = ig_var.owner.op.scalar_op.inner_inputs
+                    inner_outputs = ig_var.owner.op.scalar_op.inner_outputs
+                else:
+                    inner_inputs = ig_var.owner.op.inner_inputs
+                    inner_outputs = ig_var.owner.op.inner_outputs
 
             outer_inputs = ig_var.owner.inputs
 
@@ -412,8 +420,9 @@ def debugprint(
 
                 if (
                     isinstance(getattr(out.owner, "op", None), HasInnerGraph)
-                    and out not in inner_graph_vars
-                ):
+                    or hasattr(getattr(out.owner, "op", None), "scalar_op")
+                    and isinstance(out.owner.op.scalar_op, HasInnerGraph)
+                ) and out not in inner_graph_vars:
                     inner_graph_vars.append(out)
 
                 _debugprint(
@@ -654,8 +663,9 @@ def get_id_str(
                 if hasattr(in_var, "owner") and hasattr(in_var.owner, "op"):
                     if (
                         isinstance(in_var.owner.op, HasInnerGraph)
-                        and in_var not in inner_graph_ops
-                    ):
+                        or hasattr(in_var.owner.op, "scalar_op")
+                        and isinstance(in_var.owner.op.scalar_op, HasInnerGraph)
+                    ) and in_var not in inner_graph_ops:
                         inner_graph_ops.append(in_var)
 
                 _debugprint(

pytensor/scalar/basic.py

@@ -4000,7 +4000,8 @@ class Composite(ScalarOp, HasInnerGraph):
 
     init_param: Tuple[str, ...] = ("inputs", "outputs")
 
-    def __init__(self, inputs, outputs):
+    def __init__(self, inputs, outputs, name="Composite"):
+        self.name = name
         # We need to clone the graph as sometimes its nodes already
         # contain a reference to an fgraph. As we want the Composite
         # to be pickable, we can't have reference to fgraph.
@@ -4106,30 +4107,6 @@ def _perform(*inputs, outputs=[[None]]):
         self._py_perform_fn = fgraph_to_python(self.fgraph, python_convert)
         return self._py_perform_fn
 
-    @property
-    def name(self):
-        if hasattr(self, "_name"):
-            return self._name
-
-        # TODO FIXME: Just implement pretty printing for the `Op`; don't do
-        # this redundant, outside work in the `Op` itself.
-        for i, r in enumerate(self.fgraph.inputs):
-            r.name = f"i{int(i)}"
-        for i, r in enumerate(self.fgraph.outputs):
-            r.name = f"o{int(i)}"
-        io = set(self.fgraph.inputs + self.fgraph.outputs)
-        for i, r in enumerate(self.fgraph.variables):
-            if r not in io and len(self.fgraph.clients[r]) > 1:
-                r.name = f"t{int(i)}"
-        outputs_str = ", ".join([pprint(output) for output in self.fgraph.outputs])
-        rval = f"Composite{{{outputs_str}}}"
-        self._name = rval
-        return self._name
-
-    @name.setter
-    def name(self, name):
-        self._name = name
-
     @property
     def fgraph(self):
         if hasattr(self, "_fgraph"):

tests/scalar/test_basic.py

@@ -183,12 +183,7 @@ def test_composite_printing(self):
         make_function(DualLinker().accept(g))
 
         assert str(g) == (
-            "FunctionGraph(*1 -> Composite{((i0 + i1) + i2),"
-            " (i0 + (i1 * i2)), (i0 / i1), "
-            "(i0 // 5), "
-            "(-i0), (i0 - i1), ((i0 ** i1) + (-i2)),"
-            " (i0 % 3)}(x, y, z), "
-            "*1::1, *1::2, *1::3, *1::4, *1::5, *1::6, *1::7)"
+            "FunctionGraph(*1 -> Composite(x, y, z), *1::1, *1::2, *1::3, *1::4, *1::5, *1::6, *1::7)"
         )
 
     def test_non_scalar_error(self):

tests/scan/test_printing.py

@@ -604,31 +604,40 @@ def no_shared_fn(n, x_tm1, M):
     out = pytensor.function([M], out, updates=updates, mode="FAST_RUN")
 
     expected_output = """forall_inplace,cpu,scan_fn} [id A] 2 (outer_out_sit_sot-0)
-    |TensorConstant{20000} [id B] (n_steps)
-    |TensorConstant{[    0    ..998 19999]} [id C] (outer_in_seqs-0)
-    |IncSubtensor{InplaceSet;:int64:} [id D] 1 (outer_in_sit_sot-0)
-    | |AllocEmpty{dtype='int64'} [id E] 0
-    | | |TensorConstant{20000} [id B]
-    | |TensorConstant{(1,) of 0} [id F]
-    | |ScalarConstant{1} [id G]
-    |<TensorType(float64, (20000, 2, 2))> [id H] (outer_in_non_seqs-0)
+     |TensorConstant{20000} [id B] (n_steps)
+     |TensorConstant{[    0    ..998 19999]} [id C] (outer_in_seqs-0)
+     |IncSubtensor{InplaceSet;:int64:} [id D] 1 (outer_in_sit_sot-0)
+     | |AllocEmpty{dtype='int64'} [id E] 0
+     | | |TensorConstant{20000} [id B]
+     | |TensorConstant{(1,) of 0} [id F]
+     | |ScalarConstant{1} [id G]
+     |<TensorType(float64, (20000, 2, 2))> [id H] (outer_in_non_seqs-0)
 
     Inner graphs:
 
     forall_inplace,cpu,scan_fn} [id A] (outer_out_sit_sot-0)
-    >Elemwise{Composite{Switch(LT(i0, i1), i2, i0)}} [id I] (inner_out_sit_sot-0)
-    > |TensorConstant{0} [id J]
-    > |Subtensor{int64, int64, uint8} [id K]
-    > | |*2-<TensorType(float64, (20000, 2, 2))> [id L] -> [id H] (inner_in_non_seqs-0)
-    > | |ScalarFromTensor [id M]
-    > | | |*0-<TensorType(int64, ())> [id N] -> [id C] (inner_in_seqs-0)
-    > | |ScalarFromTensor [id O]
-    > | | |*1-<TensorType(int64, ())> [id P] -> [id D] (inner_in_sit_sot-0)
-    > | |ScalarConstant{0} [id Q]
-    > |TensorConstant{1} [id R]
+     >Elemwise{Composite} [id I] (inner_out_sit_sot-0)
+     > |TensorConstant{0} [id J]
+     > |Subtensor{int64, int64, uint8} [id K]
+     > | |*2-<TensorType(float64, (20000, 2, 2))> [id L] -> [id H] (inner_in_non_seqs-0)
+     > | |ScalarFromTensor [id M]
+     > | | |*0-<TensorType(int64, ())> [id N] -> [id C] (inner_in_seqs-0)
+     > | |ScalarFromTensor [id O]
+     > | | |*1-<TensorType(int64, ())> [id P] -> [id D] (inner_in_sit_sot-0)
+     > | |ScalarConstant{0} [id Q]
+     > |TensorConstant{1} [id R]
+
+    Elemwise{Composite} [id I]
+     >Switch [id S]
+     > |LT [id T]
+     > | |<int64> [id U]
+     > | |<float64> [id V]
+     > |<int64> [id W]
+     > |<int64> [id U]
     """
 
     output_str = debugprint(out, file="str", print_op_info=True)
+    print(output_str)
     lines = output_str.split("\n")
 
     for truth, out in zip(expected_output.split("\n"), lines):

tests/tensor/rewriting/test_basic.py

@@ -16,7 +16,7 @@
 from pytensor.graph.rewriting.basic import check_stack_trace, out2in
 from pytensor.graph.rewriting.db import RewriteDatabaseQuery
 from pytensor.graph.rewriting.utils import rewrite_graph
-from pytensor.printing import pprint
+from pytensor.printing import debugprint, pprint
 from pytensor.raise_op import Assert, CheckAndRaise
 from pytensor.tensor.basic import (
     Alloc,
@@ -1105,7 +1105,7 @@ def test_elemwise_float_ops(self, op):
         s2 = at.switch(c, x, y)
 
         g = rewrite(FunctionGraph(mats, [op(s1, s2)]))
-        assert str(g).count("Switch") == 1
+        assert debugprint(g, file="str").count("Switch") == 1
 
     @pytest.mark.parametrize(
         "op",
@@ -1122,7 +1122,7 @@ def test_elemwise_int_ops(self, op):
         s1 = at.switch(c, a, b)
         s2 = at.switch(c, x, y)
         g = rewrite(FunctionGraph(mats, [op(s1, s2)]))
-        assert str(g).count("Switch") == 1
+        assert debugprint(g, file="str").count("Switch") == 1
 
     @pytest.mark.parametrize("op", [add, mul])
     def test_elemwise_multi_inputs(self, op):
@@ -1134,7 +1134,7 @@ def test_elemwise_multi_inputs(self, op):
         u, v = matrices("uv")
         s3 = at.switch(c, u, v)
         g = rewrite(FunctionGraph(mats + [u, v], [op(s1, s2, s3)]))
-        assert str(g).count("Switch") == 1
+        assert debugprint(g, file="str").count("Switch") == 1
 
 
 class TestLocalOptAlloc:

tests/tensor/rewriting/test_math.py

@@ -28,6 +28,7 @@
 from pytensor.graph.rewriting.db import RewriteDatabaseQuery
 from pytensor.graph.rewriting.utils import is_same_graph, rewrite_graph
 from pytensor.misc.safe_asarray import _asarray
+from pytensor.printing import debugprint
 from pytensor.tensor import inplace
 from pytensor.tensor.basic import Alloc, join, switch
 from pytensor.tensor.blas import Dot22, Gemv
@@ -2416,7 +2417,7 @@ def test_elemwise(self):
             at_pow,
         ):
             g = rewrite(FunctionGraph(mats, [op(s1, s2)]))
-            assert str(g).count("Switch") == 1
+            assert debugprint(g, file="str").count("Switch") == 1
         # integer Ops
         mats = imatrices("cabxy")
         c, a, b, x, y = mats
@@ -2428,13 +2429,13 @@ def test_elemwise(self):
             bitwise_xor,
         ):
             g = rewrite(FunctionGraph(mats, [op(s1, s2)]))
-            assert str(g).count("Switch") == 1
+            assert debugprint(g, file="str").count("Switch") == 1
         # add/mul with more than two inputs
         u, v = matrices("uv")
         s3 = at.switch(c, u, v)
         for op in (add, mul):
             g = rewrite(FunctionGraph(mats + [u, v], [op(s1, s2, s3)]))
-            assert str(g).count("Switch") == 1
+            assert debugprint(g, file="str").count("Switch") == 1
 
 
 class TestLocalSumProd:

tests/test_printing.py

@@ -273,7 +273,7 @@ def test_debugprint():
     s = s.getvalue()
     exp_res = dedent(
         r"""
-        Elemwise{Composite{(i2 + (i0 - i1))}} 4
+        Elemwise{Composite} 4
          |InplaceDimShuffle{x,0} v={0: [0]} 3
          | |CGemv{inplace} d={0: [0]} 2
          |   |AllocEmpty{dtype='float64'} 1
@@ -285,6 +285,15 @@ def test_debugprint():
          |   |TensorConstant{0.0}
          |D
          |A
+
+        Inner graphs:
+
+        Elemwise{Composite}
+         >add
+         > |<float64>
+         > |sub
+         >   |<float64>
+         >   |<float64>
         """
     ).lstrip()