new_var to get_or_create

paddle/pybind/protobuf.cc

@@ -134,7 +134,7 @@ void BindBlockDesc(py::module &m) {
            py::return_value_policy::reference)
       .def("prepend_op", &BlockDescBind::PrependOp,
            py::return_value_policy::reference)
-      .def("new_var",
+      .def("get_or_create",
            [](BlockDescBind &self, py::bytes byte_name) {
              std::string name = byte_name;
              return self.GetOrCreateVar(name);

paddle/pybind/pybind.cc

@@ -163,7 +163,7 @@ All parameter, weight, gradient are variables in Paddle.
            py::return_value_policy::reference);
 
   py::class_<Scope>(m, "Scope", "")
-      .def("new_var",
+      .def("get_or_create",
            [](Scope &self, const std::string &name) -> Variable * {
              return self.GetOrCreateVar(name);
            },

python/paddle/v2/framework/default_scope_funcs.py

@@ -5,7 +5,7 @@ Default scope function.
 thread-local stack of Scope. Top of that stack is current scope, the bottom 
 of that stack is all scopes' parent. 
 
-Invoking `new_var/find_var`  can `new/find` variable in current scope. 
+Invoking `get_or_create/find_var`  can `new/find` variable in current scope. 
 Invoking `enter_local_scope/leave_local_scope` can create or destroy local 
 scope. 
 
@@ -19,7 +19,7 @@ import threading
 __tl_scope__ = threading.local()
 
 __all__ = [
-    'get_cur_scope', 'enter_local_scope', 'leave_local_scope', 'new_var',
+    'get_cur_scope', 'enter_local_scope', 'leave_local_scope', 'get_or_create',
     'find_var', 'scoped_function'
 ]
 
@@ -54,11 +54,11 @@ def leave_local_scope():
     get_cur_scope().drop_kids()
 
 
-def new_var(name):
+def get_or_create(name):
     """
     create variable in current scope.
     """
-    return get_cur_scope().new_var(name)
+    return get_cur_scope().get_or_create(name)
 
 
 def find_var(name):

python/paddle/v2/framework/graph.py

@@ -22,7 +22,7 @@ class Variable(object):
             self.desc = self.block.desc.var(name)
             is_new_var = False
         except core.EnforceNotMet:
-            self.desc = self.block.desc.new_var(name)
+            self.desc = self.block.desc.get_or_create(name)
             is_new_var = True
 
         if shape is not None:

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

@@ -14,7 +14,7 @@ def create_op(scope, op_type, inputs, outputs, attrs):
     kwargs = dict()
 
     def __create_var__(name, var_name):
-        scope.new_var(var_name)
+        scope.get_or_create(var_name)
         kwargs[name].append(var_name)
 
     for in_name, in_dup in Operator.get_op_inputs(op_type):
@@ -71,7 +71,7 @@ def set_input(scope, op, inputs, place):
 def set_output_grad(scope, op, outputs, place):
     def __set_tensor__(name):
         out_tensor = scope.find_var(name).get_tensor()
-        grad_tensor = scope.new_var(grad_var_name(name)).get_tensor()
+        grad_tensor = scope.get_or_create(grad_var_name(name)).get_tensor()
         out_dtype = out_tensor.dtype()
         if out_dtype == core.DataType.FP64:
             data = np.ones(out_tensor.shape(), dtype=np.float64)
@@ -169,10 +169,10 @@ def get_numeric_gradient(scope,
 def get_backward_op(scope, op, no_grad_set):
     backward_op = core.Operator.backward(op, no_grad_set)
     for input in backward_op.input_vars():
-        var = scope.new_var(input)
+        var = scope.get_or_create(input)
         var.get_tensor()
     for output in backward_op.output_vars():
-        var = scope.new_var(output)
+        var = scope.get_or_create(output)
         var.get_tensor()
     return backward_op
 

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

@@ -39,7 +39,7 @@ class PySimpleCondTest(unittest.TestCase):
 
 
 def create_tensor(scope, name, shape, np_data):
-    tensor = scope.new_var(name).get_tensor()
+    tensor = scope.get_or_create(name).get_tensor()
     tensor.set_dims(shape)
     tensor.set(np_data, core.CPUPlace())
     return tensor
@@ -74,9 +74,9 @@ class TestCondOp(unittest.TestCase):
         create_tensor(self.scope, "X", [10, 1], x_np_data)
         cond_np_data = self.py_cond.cond.astype("int32")
         create_tensor(self.scope, "cond", [10, 1], cond_np_data)
-        self.scope.new_var("SubScopes")
-        self.scope.new_var("IndexTensors")
-        self.scope.new_var("Out")
+        self.scope.get_or_create("SubScopes")
+        self.scope.get_or_create("IndexTensors")
+        self.scope.get_or_create("Out")
 
     def create_cond_op(self):
         self.condop = CondOp(

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

@@ -10,7 +10,7 @@ class TestDefaultScopeFuncs(unittest.TestCase):
         self.assertIsNone(find_var("test"))
 
     def test_create_var_get_var(self):
-        var_a = new_var("var_a")
+        var_a = get_or_create("var_a")
         self.assertIsNotNone(var_a)
         self.assertIsNotNone(get_cur_scope().find_var('var_a'))
         enter_local_scope()
@@ -19,7 +19,7 @@ class TestDefaultScopeFuncs(unittest.TestCase):
 
     def test_var_get_int(self):
         def __new_scope__():
-            i = new_var("var_i")
+            i = get_or_create("var_i")
             self.assertFalse(i.is_int())
             i.set_int(10)
             self.assertTrue(i.is_int())

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

@@ -14,7 +14,7 @@ class TestGaussianRandomOp(unittest.TestCase):
 
     def gaussian_random_test(self, place):
         scope = core.Scope()
-        scope.new_var('Out').get_tensor()
+        scope.get_or_create('Out').get_tensor()
 
         op = Operator(
             "gaussian_random",

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

@@ -13,12 +13,12 @@ class TestInferShape(unittest.TestCase):
         shape = [10, 20]
 
         # prepare input/output
-        x1 = block.new_var("x1")
+        x1 = block.get_or_create("x1")
         x1.set_shape(shape)
-        x2 = block.new_var("x2")
+        x2 = block.get_or_create("x2")
         x2.set_shape(shape)
 
-        out = block.new_var("out")
+        out = block.get_or_create("out")
 
         # prepare the operator
         sum_op_desc = block.append_op()
@@ -39,12 +39,12 @@ class TestInferShape(unittest.TestCase):
         y_shape = [20, 30]
 
         # prepare input/output
-        x1 = block.new_var("x")
+        x1 = block.get_or_create("x")
         x1.set_shape(x_shape)
-        x2 = block.new_var("y")
+        x2 = block.get_or_create("y")
         x2.set_shape(y_shape)
 
-        out = block.new_var("out")
+        out = block.get_or_create("out")
 
         # prepare the operator
         mul_op_desc = block.append_op()

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

@@ -31,7 +31,7 @@ uniq_id = atomic_id().next
 
 
 def data_layer(name, dims):
-    var = scope.new_var(name)
+    var = scope.get_or_create(name)
     tensor = var.get_tensor()
     tensor.set_dims(dims)  # 1 is batch size holder.
     return name
@@ -67,7 +67,7 @@ def sgd_optimizer(net, param_name, learning_rate=0.005):
 
 # should use operator and add these to the init_network
 def init_param(net, param_name, dims):
-    scope.new_var(param_name)
+    scope.get_or_create(param_name)
     op = Operator(
         "uniform_random", Out=param_name, dims=dims, min=-0.5, max=0.5, seed=10)
     op.infer_shape(scope)
@@ -104,7 +104,7 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None):
     sgd_optimizer(net=optimize_net, param_name=w_name, learning_rate=0.01)
 
     pre_activation = name + ".mul.out"
-    scope.new_var(pre_activation)
+    scope.get_or_create(pre_activation)
     mul_op = Operator("mul", X=input, Y=w_name, Out=pre_activation)
     net.append_op(mul_op)
 
@@ -115,7 +115,7 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None):
         sgd_optimizer(
             net=optimize_net, param_name=bias_name, learning_rate=0.001)
         bias_out = name + ".rowwise_add.out"
-        scope.new_var(bias_out)
+        scope.get_or_create(bias_out)
         rowwise_append_op = Operator(
             "rowwise_add", X=pre_activation, b=bias_name, Out=bias_out)
         net.append_op(rowwise_append_op)
@@ -123,7 +123,7 @@ def fc_layer(net, input, size, act="softmax", bias=True, param=None, name=None):
 
     activation_op = Operator(act, X=pre_activation, Y=name)
     net.append_op(activation_op)
-    scope.new_var(name)
+    scope.get_or_create(name)
     net.infer_shape(scope)
     return name
 
@@ -133,7 +133,7 @@ def cross_entropy_layer(net, input, label):
     cross_entropy_op = Operator(
         "cross_entropy", X=input, Label=label, Y=cost_name)
     net.append_op(cross_entropy_op)
-    scope.new_var(cost_name)
+    scope.get_or_create(cost_name)
     net.infer_shape(scope)
     return cost_name
 
@@ -141,10 +141,10 @@ def cross_entropy_layer(net, input, label):
 def create_backward_net(forward_net):
     net = core.Operator.backward(forward_net, set())
     for input in net.inputs()["all"]:
-        var = scope.new_var(input)
+        var = scope.get_or_create(input)
         var.get_tensor()
     for output in net.outputs()["all"]:
-        var = scope.new_var(output)
+        var = scope.get_or_create(output)
         var.get_tensor()
     return net
 

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

@@ -93,7 +93,7 @@ class TestVarDesc(unittest.TestCase):
     def test_shape(self):
         program_desc = core.ProgramDesc.__create_program_desc__()
         block = program_desc.block(0)
-        var = block.new_var('my_var')
+        var = block.get_or_create('my_var')
         src_shape = [3, 2, 10, 8]
         var.set_shape(src_shape)
         res_shape = var.shape()
@@ -102,7 +102,7 @@ class TestVarDesc(unittest.TestCase):
     def test_data_type(self):
         program_desc = core.ProgramDesc.__create_program_desc__()
         block = program_desc.block(0)
-        var = block.new_var('my_var')
+        var = block.get_or_create('my_var')
         var.set_data_type(core.DataType.INT32)
         self.assertEqual(core.DataType.INT32, var.data_type())
 
@@ -113,9 +113,9 @@ class TestBlockDesc(unittest.TestCase):
         self.assertIsNotNone(prog)
         block = prog.block(0)
         self.assertIsNotNone(block)
-        var1 = block.new_var("var1")
-        var2 = block.new_var("var2")
-        var3 = block.new_var("var3")
+        var1 = block.get_or_create("var1")
+        var2 = block.get_or_create("var2")
+        var3 = block.get_or_create("var3")
         all_vars = block.all_vars()
         self.assertEqual(set(all_vars), set([var1, var2, var3]))
         var2_re = block.var("var2")

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

@@ -66,7 +66,7 @@ class PySimpleRNNTest(unittest.TestCase):
 
 
 def create_tensor(scope, name, shape, np_data):
-    tensor = scope.new_var(name).get_tensor()
+    tensor = scope.get_or_create(name).get_tensor()
     tensor.set_dims(shape)
     tensor.set(np_data, core.CPUPlace())
     return tensor
@@ -125,8 +125,8 @@ class RecurrentOpTest(unittest.TestCase):
         h_boot_np_data = self.py_rnn.h_boot
         create_tensor(self.scope, "h_boot", [self.batch_size, self.input_dim],
                       h_boot_np_data)
-        self.scope.new_var("step_scopes")
-        self.scope.new_var("h@mem")
+        self.scope.get_or_create("step_scopes")
+        self.scope.get_or_create("h@mem")
 
     def create_rnn_op(self):
         # create RNNOp

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

@@ -18,7 +18,7 @@ class TestScope(unittest.TestCase):
     def test_create_var_get_var(self):
         paddle_c = paddle.v2.framework.core
         scope = paddle_c.Scope()
-        var_a = scope.new_var("var_a")
+        var_a = scope.get_or_create("var_a")
         self.assertIsNotNone(var_a)
         self.assertIsNotNone(scope.find_var('var_a'))
         scope2 = scope.new_scope()
@@ -27,7 +27,7 @@ class TestScope(unittest.TestCase):
     def test_var_get_int(self):
         paddle_c = paddle.v2.framework.core
         scope = paddle_c.Scope()
-        var = scope.new_var("test_int")
+        var = scope.get_or_create("test_int")
         var.set_int(10)
         self.assertTrue(var.is_int())
         self.assertEqual(10, var.get_int())

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

@@ -6,7 +6,7 @@ import numpy
 class TestTensor(unittest.TestCase):
     def test_int_tensor(self):
         scope = core.Scope()
-        var = scope.new_var("test_tensor")
+        var = scope.get_or_create("test_tensor")
         place = core.CPUPlace()
 
         tensor = var.get_tensor()
@@ -25,7 +25,7 @@ class TestTensor(unittest.TestCase):
 
     def test_float_tensor(self):
         scope = core.Scope()
-        var = scope.new_var("test_tensor")
+        var = scope.get_or_create("test_tensor")
         place = core.CPUPlace()
 
         tensor = var.get_tensor()
@@ -46,7 +46,7 @@ class TestTensor(unittest.TestCase):
     def test_int_lod_tensor(self):
         place = core.CPUPlace()
         scope = core.Scope()
-        var_lod = scope.new_var("test_lod_tensor")
+        var_lod = scope.get_or_create("test_lod_tensor")
         lod_tensor = var_lod.get_tensor()
 
         lod_tensor.set_dims([4, 4, 6])
@@ -68,7 +68,7 @@ class TestTensor(unittest.TestCase):
     def test_float_lod_tensor(self):
         place = core.CPUPlace()
         scope = core.Scope()
-        var_lod = scope.new_var("test_lod_tensor")
+        var_lod = scope.get_or_create("test_lod_tensor")
 
         lod_tensor = var_lod.get_tensor()
         lod_tensor.set_dims([5, 2, 3, 4])

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

@@ -13,7 +13,7 @@ class TestTensorArray(unittest.TestCase):
 
         # create a LoDTensor
         self.scope = core.Scope()
-        var = self.scope.new_var("test_tensor")
+        var = self.scope.get_or_create("test_tensor")
         self.place = core.CPUPlace()
         tensor = var.get_tensor()
         tensor.set_dims([self.batch_size, self.dim])
@@ -51,7 +51,7 @@ class TestTensorArray(unittest.TestCase):
         self.ta.unstack(self.tensor)
 
         # create a tensor with shape of [1, self.dim]
-        var = self.scope.new_var("hell")
+        var = self.scope.get_or_create("hell")
         tensor = var.get_tensor()
         tensor.set_dims([1, self.dim])
         tensor.alloc_float(self.place)
@@ -71,7 +71,7 @@ class TestTensorArray(unittest.TestCase):
         self.ta.unstack(self.tensor)
 
         # create a tensor with shape of [1, self.dim]
-        var = self.scope.new_var("hell")
+        var = self.scope.get_or_create("hell")
         tensor = var.get_tensor()
         tensor.set_dims([1, self.dim])
         tensor.alloc_float(self.place)

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

@@ -14,7 +14,7 @@ class TestUniformRandomOp(unittest.TestCase):
 
     def uniform_random_test(self, place):
         scope = core.Scope()
-        scope.new_var('X').get_tensor()
+        scope.get_or_create('X').get_tensor()
 
         op = Operator(
             "uniform_random",