Fix TF logic variable name and NodeDef handling

Author: brandonwillard

symbolic_pymc/tensorflow/meta.py

@@ -235,7 +235,7 @@ def out_meta_types(self, inputs=None, node_def=None):
         """Return a list of tuples containing object types and corresponding dtypes for the outputs of this OpDef."""
 
         def _convert_outputs(o):
-            if o.type_attr == "T" and hasattr(node_def, "attr"):
+            if o.type_attr == "T" and isinstance(getattr(node_def, "attr", None), dict):
                 return (TFlowMetaTensor, node_def.attr.get("T", var()))
             elif o.type_attr == "dtype" and inputs:
                 return (TFlowMetaTensor, inputs.get("dtype", var()))
@@ -323,9 +323,10 @@ def __call__(self, *args, **kwargs):
             else:
                 node_attr = var()
 
-            op_name = op_kwargs.get(
-                "name", self.obj.name if "names" not in meta._lvar_defaults_enabled else var()
-            )
+            if "names" not in meta._lvar_defaults_enabled:
+                op_name = op_kwargs.get("name", self.obj.name)
+            else:
+                op_name = var()
 
             node_def = TFlowMetaNodeDef(self.obj.name, op_name, node_attr)
 
@@ -561,7 +562,7 @@ def outputs(self):
             self._outputs = var()
         else:
 
-            if isvar(self.node_def) or isvar(getattr(self.node_def, "attr")):
+            if isvar(self.node_def) or not isinstance(getattr(self.node_def, "attr", None), dict):
                 node_attr = {}
             else:
                 node_attr = self.node_def.attr
@@ -613,24 +614,23 @@ def reify(self):
         if self.obj and not isinstance(self.obj, Var):
             return self.obj
 
-        # tt_op = self.op.reify()
-        # if not self.is_meta(tt_op):
+        if isvar(self.inputs):
+            return self
+
         op_inputs, op_inputs_unreified = meta_reify_iter(self.inputs)
 
-        if isvar(self.node_def):
+        node_attr = getattr(self.node_def, "attr", None)
+
+        if node_attr is None or isvar(node_attr):
             return self
 
         op_attrs, op_attrs_unreified = meta_reify_iter(
             # Only use NodeDef attrs that appear in the OpDef's call signature.
             # Other NodeDef attrs, like dtype and shape, can be computed.
-            {
-                k: v
-                for k, v in self.node_def.attr.items()
-                if k in self.op_def._apply_func_sig.parameters
-            }
+            {k: v for k, v in node_attr.items() if k in self.op_def._apply_func_sig.parameters}
         )
 
-        if not (op_inputs_unreified or op_attrs_unreified or MetaSymbol.is_meta(self.name)):
+        if not (op_inputs_unreified or op_attrs_unreified or isvar(self.name)):
 
             # We have to use a primitive string or TF will complain.
             name = self.name

tests/tensorflow/test_meta.py

@@ -224,6 +224,8 @@ def test_meta_lvars():
 
     nd_mt = TFlowMetaNodeDef(var(), var(), var())
     assert all(isvar(getattr(nd_mt, s)) for s in nd_mt.__all_props__)
+    # TODO: Figure out how we want this to work.
+    # assert isinstance(nd_mt.reify(), TFlowMetaNodeDef)
 
     mo_mt = TFlowMetaOp(var(), var(), var(), var())
     assert all(isvar(getattr(mo_mt, s)) for s in mo_mt.__all_props__)
@@ -234,14 +236,21 @@ def test_meta_lvars():
 
     mo_mt = TFlowMetaOp(mt.Add, var(), var())
     assert len(mo_mt.outputs) == 1
+    assert isinstance(mo_mt.reify(), TFlowMetaOp)
 
     ts_mt = TFlowMetaTensorShape(var())
     assert all(isvar(getattr(ts_mt, s)) for s in ts_mt.__all_props__)
+    assert isinstance(ts_mt.reify(), TFlowMetaTensorShape)
 
     assert isvar(ts_mt.as_list())
 
     tn_mt = TFlowMetaTensor(var(), var(), var())
     assert all(isvar(getattr(tn_mt, s)) for s in tn_mt.__all_props__)
+    assert isinstance(tn_mt.reify(), TFlowMetaTensor)
+
+    mo_mt = TFlowMetaOp(mt.Add, [tn_mt, tn_mt], var())
+    assert len(mo_mt.outputs) == 1
+    assert isinstance(mo_mt.reify(), TFlowMetaOp)
 
 
 @pytest.mark.usefixtures("run_with_tensorflow")
@@ -554,10 +563,19 @@ def test_global_options():
         assert isvar(z_mt.name)
         assert isvar(z_mt.op.node_def.attr)
 
-    with tf.Graph().as_default(), disable_auto_reification(), enable_lvar_defaults('names', 'node_attrs'):
+    with disable_auto_reification(), enable_lvar_defaults('names', 'node_attrs'):
         # This will *not* auto-reify and simply create the object from scratch with meta types
         # and the appropriate/desired logic variables.
         z_mt = mt.Placeholder('float')
         assert z_mt.obj is None
         assert isvar(z_mt.name)
         assert isvar(z_mt.op.node_def.attr)
+
+    with tf.Graph().as_default(), enable_lvar_defaults('names', 'node_attrs'):
+        y_mt = mt.Placeholder('float') + mt.Placeholder('float')
+        assert isvar(y_mt.name)
+        assert isvar(y_mt.op.inputs[0].name)
+        assert isvar(y_mt.op.inputs[1].name)
+        assert isvar(y_mt.op.node_def.attr)
+        assert isvar(y_mt.op.inputs[0].op.node_def.attr)
+        assert isvar(y_mt.op.inputs[1].op.node_def.attr)