Add missing test for OpDef Signature functionality

Author: brandonwillard

symbolic_pymc/tensorflow/meta.py

@@ -86,25 +86,26 @@ def make_opdef_sig(cls, opdef):
                 params[name] = new_param
 
         else:
-            params = []
-            for i_name, i_type in input_args:
+            for i_name, i_type in input_args.items():
                 p = Parameter(i_name, Parameter.POSITIONAL_OR_KEYWORD, annotation=i_type)
                 params[i_name] = p
 
             # These are the ambiguities we're attempting to overcome
             # with the `tf.raw_ops` functions above.
-            for a_name, a_type in attrs:
+            for a_name, a_type in attrs.items():
+
                 if a_name == "T":
                     # This is a type value that will most likely be inferred
                     # from/by the inputs.
                     # TODO: We could check for an `allowed_values` attribute.
                     continue
+
                 p = Parameter(
                     a_name,
                     Parameter.POSITIONAL_OR_KEYWORD,
                     # TODO: We could use the `default_value`
                     # attribute.
-                    default=None,
+                    default=Parameter.empty,
                     annotation=a_type,
                 )
                 params[a_name] = p

tests/tensorflow/test_meta.py

@@ -16,6 +16,7 @@
                                            TFlowMetaOpDef,
                                            TFlowMetaNodeDef,
                                            TFlowOpName,
+                                           MetaOpDefLibrary,
                                            mt)
 
 from tests.tensorflow import run_in_graph_mode
@@ -321,6 +322,47 @@ def test_inputs_remapping():
     assert z_mt.inputs[1].obj == z.op.inputs[2]
 
 
+@pytest.mark.usefixtures("run_with_tensorflow")
+def test_opdef_sig():
+    """Make sure we can construct an `inspect.Signature` object for a protobuf OpDef when its corresponding function isn't present in `tf.raw_ops`."""
+    from tensorflow.core.framework import op_def_pb2
+
+    custom_opdef_tf = op_def_pb2.OpDef()
+    custom_opdef_tf.name = "MyOpDef"
+
+    arg1_tf = op_def_pb2.OpDef.ArgDef()
+    arg1_tf.name = "arg1"
+    arg1_tf.type_attr = "T"
+
+    arg2_tf = op_def_pb2.OpDef.ArgDef()
+    arg2_tf.name = "arg2"
+    arg2_tf.type_attr = "T"
+
+    custom_opdef_tf.input_arg.extend([arg1_tf, arg2_tf])
+
+    attr1_tf = op_def_pb2.OpDef.AttrDef()
+    attr1_tf.name = "T"
+    attr1_tf.type = "type"
+
+    attr2_tf = op_def_pb2.OpDef.AttrDef()
+    attr2_tf.name = "axis"
+    attr2_tf.type = "int"
+    attr2_tf.default_value.i = 1
+
+    custom_opdef_tf.attr.extend([attr1_tf, attr2_tf])
+
+    opdef_sig = MetaOpDefLibrary.make_opdef_sig(custom_opdef_tf)
+
+    import inspect
+    # These are standard inputs
+    assert opdef_sig.parameters['arg1'].default == inspect._empty
+    assert opdef_sig.parameters['arg2'].default == inspect._empty
+    # These are attributes that are sometimes required by the OpDef
+    assert opdef_sig.parameters['axis'].default == inspect._empty
+    # The obligatory tensor name parameter
+    assert opdef_sig.parameters['name'].default is None
+
+
 @pytest.mark.usefixtures("run_with_tensorflow")
 @run_in_graph_mode
 def test_nodedef():