Merge branch 'feature/change_op_creation' into feature/uniform_random_op

python/paddle/v2/framework/network.py

-import paddle.v2.framework.core as core
-from paddle.v2.framework.create_op_creation_methods import op_creations
-from default_scope_funcs import new_var, find_var, get_cur_scope
-
-__all__ = ['Network']  # Only expose Network
-
-
-class NetworkFunctor(object):
-    """
-    Network Op Creation Function. Used internally in this module.
-    It convert string input to Variable. If it is not created before, just 
-    create in scope.
-    
-    It is a functor object. means the instances are callable.
-    
-    :param func: The op creation function which generated in Python.
-    :param net: The Network instance.
-    """
-
-    def __init__(self, func, net):
-        self.func = func
-        self.net = net
-
-    def __call__(self, *args, **kwargs):
-        if len(args) != 0:
-            raise ValueError("Paddle must use keyword argument")
-        inputs = self.func.all_input_args
-        for ipt in inputs:
-            if ipt in kwargs:
-                var = kwargs[ipt]
-                if isinstance(var, basestring):
-                    tmp = new_var(var)
-                    self.net.var_names[tmp] = var
-                    var = tmp
-
-                if not isinstance(var, core.Variable):
-                    raise TypeError(
-                        "Input of op creation must be string or variable")
-
-                kwargs[ipt] = self.net.var_names[var]
-
-        notemp_outputs = self.func.all_not_temp_output_args
-
-        for name in notemp_outputs:
-            if name not in kwargs:
-                kwargs[
-                    name] = self.func.__name__ + "@OUT@%d" % core.unique_integer(
-                    )
-
-        outputs = self.func.all_output_args
-        for opt in outputs:
-            if opt in kwargs:
-                var = kwargs[opt]
-                if isinstance(var, basestring):
-                    tmp = new_var(var)
-                    self.net.var_names[tmp] = var
-                    var = tmp
-
-                if not isinstance(var, core.Variable):
-                    raise TypeError(
-                        "Output of op creation must be string or variable")
-                kwargs[opt] = self.net.var_names[var]
-
-        op = self.func(**kwargs)
-
-        self.net.net.add_op(op)
-
-        lst = [find_var(kwargs[opt]) for opt in notemp_outputs]
-        if len(lst) == 1:
-            return lst[0]
-        elif len(lst) == 0:
-            return None
-        else:
-            return lst
-
-
-class Network(object):
-    """
-    The network concept. It avoid user to manually create operator, create 
-    variable, and combine them into a Net. Just use Network.xxx can create the
-    operator, create variables in default scope, and add them into `self.net`.
-    
-    For example:
-    
-    ..  code-block: python
-    
-        net = Network()
-        out = net.add_two(X="a", Y="b")
-        fc_out = net.fc(X="out", W="fc.w")
-        
-        net.run(...)
-    """
-
-    def __init__(self):
-        self.net = core.Net.create()
-        funcs = (func_name for func_name in dir(op_creations)
-                 if not func_name.startswith("__"))
-        self.var_names = dict()
-
-        # TODO(yuyang18): This code can work, but do not generate a good
-        # docstring, try to give a better way generate function in runtime
-        # later.
-        for func_name in funcs:
-            func = getattr(op_creations, func_name)
-            impl = NetworkFunctor(func, self)
-            setattr(self, func_name, impl.__call__)
-        self.__complete_add_op__ = False
-
-    def infer_shape(self):
-        self.complete_add_op()
-        self.net.infer_shape(get_cur_scope())
-
-    def run(self, device_context):
-        self.complete_add_op()
-        self.net.run(get_cur_scope(), device_context)
-
-    def __str__(self):
-        return str(self.net)
-
-    def complete_add_op(self):
-        if not self.__complete_add_op__:
-            self.net.complete_add_op()
-            self.__complete_add_op__ = True
-
-
-if __name__ == '__main__':
-    net = Network()
-    out = net.add_two(X="a", Y="b")
-    fc_out = net.fc(X=out, W="fc.w", b="fc.b", activation="softmax")
-    net.complete_add_op()
-    print net

python/paddle/v2/framework/create_op_creation_methods.py → python/paddle/v2/framework/op.py

@@ -2,7 +2,6 @@ import paddle.v2.framework.core as core
 import paddle.v2.framework.proto.op_proto_pb2 as op_proto_pb2
 import paddle.v2.framework.proto.op_desc_pb2 as op_desc_pb2
 import paddle.v2.framework.proto.attribute_pb2 as attribute_pb2
-import cStringIO
 
 
 def get_all_op_protos():
@@ -146,66 +145,6 @@ class OpDescCreationMethod(object):
         return False
 
 
-def get_docstring_from_op_proto(op_proto):
-    """
-    Generate docstring from a OpProto
-    :param op_proto: a OpProto instance.
-    :type op_proto: op_proto_pb2.OpProto
-    :return: docstring
-    """
-    if not isinstance(op_proto, op_proto_pb2.OpProto):
-        raise TypeError("Input must be OpProto")
-    f = cStringIO.StringIO()
-    f.write(op_proto.comment)
-    f.write("\n")
-
-    def __append_param__(name, comment, type):
-        # Maybe replace the following line with template engine is better.
-        f.write(":param ")
-        f.write(name)
-        f.write(": ")
-        f.write(comment)
-        f.write("\n")
-        f.write(":type ")
-        f.write(name)
-        f.write(": ")
-        f.write(type)
-        f.write("\n")
-
-    for ipt in op_proto.inputs:
-        __append_param__(ipt.name, ipt.comment, "list | basestr"
-                         if ipt.multiple else "basestr")
-
-    temp_var_prefix = \
-        "This is a temporary variable. It does not have to set by user. "
-    for opt in op_proto.outputs:
-        __append_param__(opt.name, opt.comment if not opt.temporary else
-                         temp_var_prefix + opt.comment, "list | basestr"
-                         if opt.multiple else "basestr")
-
-    for attr in op_proto.attrs:
-        attr_type = None
-        if attr.type == attribute_pb2.INT:
-            attr_type = "int"
-        elif attr.type == attribute_pb2.FLOAT:
-            attr_type = "float"
-        elif attr.type == attribute_pb2.STRING:
-            attr_type = "basestr"
-        elif attr.type == attribute_pb2.INTS:
-            attr_type = "list of int"
-        elif attr.type == attribute_pb2.FLOATS:
-            attr_type = "list of float"
-        elif attr.type == attribute_pb2.STRINGS:
-            attr_type = "list of basestr"
-
-        if attr_type is None:
-            raise RuntimeError("Not supported attribute type " + attr.type)
-
-        __append_param__(attr.name, attr.comment, attr_type)
-
-    return f.getvalue()
-
-
 def create_op_creation_method(op_proto):
     """
     Generate op creation method for an OpProto
@@ -216,38 +155,57 @@ def create_op_creation_method(op_proto):
         opdesc = method(*args, **kwargs)
         return core.Operator.create(opdesc.SerializeToString())
 
-    __impl__.__doc__ = get_docstring_from_op_proto(op_proto)
-    __impl__.all_input_args = [var.name for var in op_proto.inputs]
-    __impl__.all_output_args = [var.name for var in op_proto.outputs]
-    __impl__.all_attr_args = [attr.name for attr in op_proto.attrs]
-    __impl__.all_not_temp_output_args = [
-        var.name for var in op_proto.outputs if not var.temporary
-    ]
+    return {
+        'method': __impl__,
+        'name': op_proto.type,
+        'all_inputs': [var.name for var in op_proto.inputs],
+        'all_outputs': [var.name for var in op_proto.outputs],
+        'all_attrs': [attr.name for attr in op_proto.attrs],
+        'all_no_temp_outputs':
+        [var.name for var in op_proto.outputs if not var.temporary]
+    }
 
-    return __impl__
 
+class OperatorFactory(object):
+    def __init__(self):
+        self.op_methods = dict()
+        for op_proto in get_all_op_protos():
+            method = create_op_creation_method(op_proto)
+            self.op_methods[method['name']] = method
 
-class OpCreationsHolder(object):
-    """
-    A object will holds all op creation methods.
+    def __call__(self, *args, **kwargs):
+        if 'type' in kwargs:
+            if len(args) != 0:
+                raise ValueError("All Paddle argument should be key-word "
+                                 "argument except type")
+            t = kwargs.pop('type')
+        else:
+            if len(args) != 1:
+                raise ValueError("All Paddle argument should be key-word "
+                                 "argument except type")
+            t = args[0]
 
-    Use `op_creations.xxx_op` to access them.
-    """
-    pass
+        return self.get_op_creation_info(t)['method'](**kwargs)
 
+    def types(self):
+        return self.op_methods.keys()
 
-op_creations = OpCreationsHolder()
+    def get_op_creation_info(self, t):
+        if t not in self.op_methods:
+            raise ValueError("operator %s is not registered", t)
+        return self.op_methods.get(t)
 
+    def get_op_input_names(self, type):
+        return self.get_op_creation_info(type)['all_inputs']
 
-def __bootstrap__():
-    """
-    Bootstrap function for this module. It will dynamic create all op creation
-    methods in runtime.
-    """
-    for op_proto in get_all_op_protos():
-        func = create_op_creation_method(op_proto)
-        func.__name__ = str(op_proto.type)
-        setattr(op_creations, func.__name__, func)
+    def get_op_output_names(self, type):
+        return self.get_op_creation_info(type)['all_outputs']
+
+    def get_op_attr_names(self, type):
+        return self.get_op_creation_info(type)['all_attrs']
+
+    def get_op_no_temp_output_names(self, type):
+        return self.get_op_creation_info(type)['all_no_temp_outputs']
 
 
-__bootstrap__()
+Operator = OperatorFactory()  # Default global factory

python/paddle/v2/framework/tests/CMakeLists.txt

 add_python_test(test_framework
     test_protobuf.py
     test_scope.py
+    test_operator.py
     test_default_scope_funcs.py
-    test_op_creation_methods.py
     test_net.py
     test_tensor.py
     test_fc_op.py
@@ -13,6 +13,5 @@ add_python_test(test_framework
     test_sigmoid_op.py
     test_softmax_op.py
     test_rowwise_add_op.py
-    test_network.py
     gradient_checker.py
     test_uniform_random_op.py)

python/paddle/v2/framework/tests/gradient_checker.py

 import paddle.v2.framework.core as core
-from paddle.v2.framework.create_op_creation_methods import op_creations
+from paddle.v2.framework.op import Operator
 import numpy
 import unittest
 
@@ -80,7 +80,7 @@ if __name__ == '__main__':
 
     class GetNumericGradientTest(unittest.TestCase):
         def test_add_op(self):
-            add_op = op_creations.add_two(X="X", Y="Y", Out="Z")
+            add_op = Operator('add_two', X="X", Y="Y", Out="Z")
             x = numpy.random.random((10, 1)).astype("float32")
             y = numpy.random.random((10, 1)).astype("float32")
 

python/paddle/v2/framework/tests/op_test_util.py

 import paddle.v2.framework.core as core
 import unittest
 import numpy
-import paddle.v2.framework.create_op_creation_methods as creation
+from paddle.v2.framework.op import Operator
 
 
 class OpTestMeta(type):
@@ -21,18 +21,14 @@ class OpTestMeta(type):
         obj = super(OpTestMeta, cls).__new__(cls, name, bases, attrs)
 
         def test_all(self):
-            func = getattr(creation.op_creations, self.type, None)
-            self.assertIsNotNone(func)
-
             scope = core.Scope()
             kwargs = dict()
-            places = []
-            places.append(core.CPUPlace())
+            places = [core.CPUPlace()]
             if core.is_compile_gpu():
                 places.append(core.GPUPlace(0))
 
             for place in places:
-                for in_name in func.all_input_args:
+                for in_name in Operator.get_op_input_names(self.type):
                     if hasattr(self, in_name):
                         kwargs[in_name] = in_name
                         var = scope.new_var(in_name).get_tensor()
@@ -42,23 +38,23 @@ class OpTestMeta(type):
                     else:
                         kwargs[in_name] = "@EMPTY@"
 
-                for out_name in func.all_output_args:
+                for out_name in Operator.get_op_output_names(self.type):
                     if hasattr(self, out_name):
                         kwargs[out_name] = out_name
                         scope.new_var(out_name).get_tensor()
 
-                for attr_name in func.all_attr_args:
+                for attr_name in Operator.get_op_attr_names(self.type):
                     if hasattr(self, attr_name):
                         kwargs[attr_name] = getattr(self, attr_name)
 
-                op = func(**kwargs)
+                op = Operator(self.type, **kwargs)
 
                 op.infer_shape(scope)
 
                 ctx = core.DeviceContext.create(place)
                 op.run(scope, ctx)
 
-                for out_name in func.all_output_args:
+                for out_name in Operator.get_op_output_names(self.type):
                     actual = numpy.array(scope.find_var(out_name).get_tensor())
                     expect = getattr(self, out_name)
                     numpy.isclose(actual, expect)

python/paddle/v2/framework/tests/test_add_two_op.py

@@ -2,7 +2,7 @@ import unittest
 
 import numpy
 import paddle.v2.framework.core as core
-import paddle.v2.framework.create_op_creation_methods as creation
+from paddle.v2.framework.op import Operator
 
 from op_test_util import OpTestMeta
 
@@ -19,7 +19,7 @@ class TestAddOp(unittest.TestCase):
 
 class TestAddGradOp(unittest.TestCase):
     def test_add_grad(self):
-        op = creation.op_creations.add_two(X="X", Y="Y", Out="Out")
+        op = Operator('add_two', X="X", Y="Y", Out="Out")
         backward_op = core.Operator.backward(op, set())
         self.assertEqual(backward_op.type(), "add_two_grad")
         expected = '''Op(add_two_grad), inputs:(X, Y, Out, Out@GRAD), outputs:(X@GRAD, Y@GRAD).'''

python/paddle/v2/framework/tests/test_fc_op.py

 import paddle.v2.framework.core as core
 import unittest
 import numpy
-import paddle.v2.framework.create_op_creation_methods as creation
+from paddle.v2.framework.op import Operator
 
 
 class TestFc(unittest.TestCase):
@@ -24,7 +24,7 @@ class TestFc(unittest.TestCase):
         # Set a real numpy array here.
         # x_tensor.set(numpy.array([]))
 
-        op = creation.op_creations.fc(X="X", Y="Y", W="W")
+        op = Operator("fc", X="X", Y="Y", W="W")
 
         for out in op.outputs():
             if scope.find_var(out) is None:

python/paddle/v2/framework/tests/test_net.py

 import paddle.v2.framework.core as core
-from paddle.v2.framework.create_op_creation_methods import op_creations
+from paddle.v2.framework.op import Operator
 import unittest
 
 
 class TestNet(unittest.TestCase):
     def test_net_all(self):
         net = core.Net.create()
-        op1 = op_creations.add_two(X="X", Y="Y", Out="Out")
+        op1 = Operator("add_two", X="X", Y="Y", Out="Out")
         net.add_op(op1)
 
         net2 = core.Net.create()
-        net2.add_op(op_creations.fc(X="X", W="w", Y="fc.out"))
+        net2.add_op(Operator("fc", X="X", W="w", Y="fc.out"))
         net2.complete_add_op(True)
         net.add_op(net2)
         net.complete_add_op(True)

python/paddle/v2/framework/tests/test_network.py

-from paddle.v2.framework.network import Network
-import paddle.v2.framework.core as core
-import unittest
-
-
-class TestNet(unittest.TestCase):
-    def test_net_all(self):
-        net = Network()
-        out = net.add_two(X="X", Y="Y")
-        fc_out = net.fc(X=out, W="w")
-        net.complete_add_op()
-        self.assertTrue(isinstance(fc_out, core.Variable))
-        self.assertEqual(
-            '''Op(plain_net), inputs:(@EMPTY@, X, Y, w), outputs:(@TEMP@fc@0, add_two@OUT@0, fc@OUT@1).
-    Op(add_two), inputs:(X, Y), outputs:(add_two@OUT@0).
-    Op(fc), inputs:(add_two@OUT@0, w, @EMPTY@), outputs:(fc@OUT@1, @TEMP@fc@0).
-        Op(mul), inputs:(add_two@OUT@0, w), outputs:(@TEMP@fc@0).
-        Op(sigmoid), inputs:(@TEMP@fc@0), outputs:(fc@OUT@1).
-''', str(net))
-
-        net2 = Network()
-        tmp = net2.add_two(X="X", Y="Y")
-        self.assertTrue(isinstance(tmp, core.Variable))
-        net2.complete_add_op()
-        self.assertEqual(
-            '''Op(plain_net), inputs:(X, Y), outputs:(add_two@OUT@2).
-    Op(add_two), inputs:(X, Y), outputs:(add_two@OUT@2).
-''', str(net2))
-
-
-if __name__ == '__main__':
-    unittest.main()

python/paddle/v2/framework/tests/test_op_creation_methods.py → python/paddle/v2/framework/tests/test_operator.py

 import unittest
-import paddle.v2.framework.create_op_creation_methods as creation
+import paddle.v2.framework.op as op
 import paddle.v2.framework.core as core
 import paddle.v2.framework.proto.op_proto_pb2 as op_proto_pb2
 import paddle.v2.framework.proto.op_desc_pb2 as op_desc_pb2
@@ -8,7 +8,7 @@ import paddle.v2.framework.proto.attribute_pb2 as attribute_pb2
 
 class TestGetAllProtos(unittest.TestCase):
     def test_all(self):
-        all_protos = creation.get_all_op_protos()
+        all_protos = op.get_all_op_protos()
         self.assertNotEqual(0, len(all_protos))
 
         for each in all_protos:
@@ -17,25 +17,25 @@ class TestGetAllProtos(unittest.TestCase):
 
 class TestOpDescCreationMethod(unittest.TestCase):
     def test_plain_input_output(self):
-        op = op_proto_pb2.OpProto()
-        op.type = "test"
-        ipt = op.inputs.add()
+        op_proto = op_proto_pb2.OpProto()
+        op_proto.type = "test"
+        ipt = op_proto.inputs.add()
         ipt.name = "X"
         ipt.comment = "not matter"
 
-        ipt = op.inputs.add()
+        ipt = op_proto.inputs.add()
         ipt.name = "Y"
         ipt.comment = "not matter"
 
-        opt = op.outputs.add()
+        opt = op_proto.outputs.add()
         opt.name = "Z"
         opt.comment = "not matter"
 
-        op.comment = "not matter"
+        op_proto.comment = "not matter"
 
-        self.assertTrue(op.IsInitialized())
+        self.assertTrue(op_proto.IsInitialized())
 
-        method = creation.OpDescCreationMethod(op)
+        method = op.OpDescCreationMethod(op_proto)
         output = method(X="a", Y="b", Z="c")
 
         expected = op_desc_pb2.OpDesc()
@@ -45,29 +45,29 @@ class TestOpDescCreationMethod(unittest.TestCase):
         self.assertEqual(expected, output)
 
     def test_multiple_input_plain_output(self):
-        op = op_proto_pb2.OpProto()
-        op.type = "fc"
-        ipt = op.inputs.add()
+        op_proto = op_proto_pb2.OpProto()
+        op_proto.type = "fc"
+        ipt = op_proto.inputs.add()
         ipt.name = "X"
         ipt.comment = ""
         ipt.multiple = True
 
-        ipt = op.inputs.add()
+        ipt = op_proto.inputs.add()
         ipt.name = "W"
         ipt.comment = ""
         ipt.multiple = True
 
-        ipt = op.inputs.add()
+        ipt = op_proto.inputs.add()
         ipt.name = "b"
         ipt.comment = ""
 
-        out = op.outputs.add()
+        out = op_proto.outputs.add()
         out.name = "Y"
         out.comment = ""
 
-        op.comment = ""
-        self.assertTrue(op.IsInitialized())
-        method = creation.OpDescCreationMethod(op)
+        op_proto.comment = ""
+        self.assertTrue(op_proto.IsInitialized())
+        method = op.OpDescCreationMethod(op_proto)
 
         generated1 = method(X="x", W="w", b="b", Y="y")
         expected1 = op_desc_pb2.OpDesc()
@@ -93,14 +93,14 @@ class TestOpDescCreationMethod(unittest.TestCase):
         self.assertEqual(expected2, generated2)
 
     def test_attrs(self):
-        op = op_proto_pb2.OpProto()
-        op.type = "test"
-        ipt = op.inputs.add()
+        op_proto = op_proto_pb2.OpProto()
+        op_proto.type = "test"
+        ipt = op_proto.inputs.add()
         ipt.name = 'X'
         ipt.comment = ""
 
         def __add_attr__(name, type):
-            attr = op.attrs.add()
+            attr = op_proto.attrs.add()
             attr.name = name
             attr.comment = ""
             attr.type = type
@@ -112,10 +112,10 @@ class TestOpDescCreationMethod(unittest.TestCase):
         __add_attr__("floats_attr", attribute_pb2.FLOATS)
         __add_attr__("strings_attr", attribute_pb2.STRINGS)
 
-        op.comment = ""
-        self.assertTrue(op.IsInitialized())
+        op_proto.comment = ""
+        self.assertTrue(op_proto.IsInitialized())
 
-        method = creation.OpDescCreationMethod(op)
+        method = op.OpDescCreationMethod(op_proto)
 
         generated = method(
             X="a",
@@ -162,23 +162,23 @@ class TestOpDescCreationMethod(unittest.TestCase):
         self.assertEqual(expected, generated)
 
     def test_input_temporary_output(self):
-        op = op_proto_pb2.OpProto()
-        op.type = "test"
-        out = op.outputs.add()
+        op_proto = op_proto_pb2.OpProto()
+        op_proto.type = "test"
+        out = op_proto.outputs.add()
         out.name = "OUT"
         out.comment = ""
 
-        out = op.outputs.add()
+        out = op_proto.outputs.add()
         out.name = "TMP"
         out.comment = ""
         out.temporary = True
 
-        out = op.outputs.add()
+        out = op_proto.outputs.add()
         out.name = "OUT2"
         out.comment = ""
-        op.comment = ""
+        op_proto.comment = ""
 
-        method = creation.OpDescCreationMethod(op)
+        method = op.OpDescCreationMethod(op_proto)
         generated = method(OUT="a", OUT2="b")
         desc = op_desc_pb2.OpDesc()
         desc.outputs.extend(["a", core.var_names.temp(), "b"])
@@ -190,60 +190,9 @@ class TestOpDescCreationMethod(unittest.TestCase):
         self.assertEqual(generated, desc)
 
 
-class TestOpCreationDocStr(unittest.TestCase):
-    def test_all(self):
-        op = op_proto_pb2.OpProto()
-        op.type = "test"
-        op.comment = """Test Op.
-
-This op is used for unit test, not a real op.
-"""
-        a = op.inputs.add()
-        a.name = "a"
-        a.comment = "Input a for test op"
-        a.multiple = True
-
-        b = op.inputs.add()
-        b.name = "b"
-        b.comment = "Input b for test op"
-        self.assertTrue(op.IsInitialized())
-
-        o1 = op.outputs.add()
-        o1.name = "output"
-        o1.comment = "The output of test op"
-
-        o2 = op.outputs.add()
-        o2.name = "temp output"
-        o2.comment = "The temporary output of test op"
-        o2.temporary = True
-
-        test_str = op.attrs.add()
-        test_str.name = "str_attr"
-        test_str.type = attribute_pb2.STRING
-        test_str.comment = "A string attribute for test op"
-
-        actual = creation.get_docstring_from_op_proto(op)
-        expected_docstring = '''Test Op.
-
-This op is used for unit test, not a real op.
-
-:param a: Input a for test op
-:type a: list | basestr
-:param b: Input b for test op
-:type b: basestr
-:param output: The output of test op
-:type output: basestr
-:param temp output: This is a temporary variable. It does not have to set by user. The temporary output of test op
-:type temp output: basestr
-:param str_attr: A string attribute for test op
-:type str_attr: basestr
-'''
-        self.assertEqual(expected_docstring, actual)
-
-
 class TestOpCreations(unittest.TestCase):
     def test_all(self):
-        add_op = creation.op_creations.add_two(X="a", Y="b", Out="z")
+        add_op = op.Operator("add_two", X="a", Y="b", Out="z")
         self.assertIsNotNone(add_op)
         # Invoke C++ DebugString()
         self.assertEqual('Op(add_two), inputs:(a, b), outputs:(z).',

python/paddle/v2/framework/tests/test_softmax_op.py

@@ -2,7 +2,7 @@ import unittest
 
 import numpy as np
 import paddle.v2.framework.core as core
-import paddle.v2.framework.create_op_creation_methods as creation
+from paddle.v2.framework.op import Operator
 
 from op_test_util import OpTestMeta
 
@@ -25,7 +25,7 @@ class TestSoftmaxOp(unittest.TestCase):
 
 class TestSoftmaxGradOp(unittest.TestCase):
     def test_softmax_grad(self):
-        op = creation.op_creations.softmax(X="X", Y="Y")
+        op = Operator('softmax', X="X", Y="Y")
         backward_op = core.Operator.backward(op, set())
         self.assertEqual(backward_op.type(), "softmax_grad")
         expected = '''Op(softmax_grad), inputs:(X, Y, Y@GRAD), outputs:(X@GRAD).'''