Merge pull request #4012 from QiJune/refine_op_test

fix attr bug in op_test and ensure order in duplicate inputs/outputs

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

@@ -9,7 +9,7 @@ def grad_var_name(var_name):
     return var_name + "@GRAD"
 
 
-def create_op(scope, op_type, inputs, outputs, attrs=None):
+def create_op(scope, op_type, inputs, outputs, attrs):
     kwargs = dict()
 
     for in_name, in_dup in Operator.get_op_inputs(op_type):
@@ -17,7 +17,7 @@ def create_op(scope, op_type, inputs, outputs, attrs=None):
             kwargs[in_name] = []
             if in_dup:
                 sub_in = inputs[in_name]
-                for sub_in_name in sub_in:
+                for sub_in_name, _ in sub_in:
                     var = scope.new_var(sub_in_name)
                     kwargs[in_name].append(sub_in_name)
             else:
@@ -29,15 +29,16 @@ def create_op(scope, op_type, inputs, outputs, attrs=None):
             kwargs[out_name] = []
             if out_dup:
                 sub_in = outputs[out_name]
-                for sun_in_name in sub_in:
-                    var = scope.new_var(sun_in_name)
-                    kwargs[out_name].append(sun_in_name)
+                for sub_in_name, _ in sub_in:
+                    var = scope.new_var(sub_in_name)
+                    kwargs[out_name].append(sub_in_name)
             else:
                 var = scope.new_var(out_name)
                 kwargs[out_name].append(out_name)
 
     for attr_name in Operator.get_op_attr_names(op_type):
-        kwargs[attr_name] = attrs[attr_name]
+        if attr_name in attrs:
+            kwargs[attr_name] = attrs[attr_name]
     return Operator(op_type, **kwargs)
 
 
@@ -46,12 +47,11 @@ def set_input(scope, op, inputs, place):
         if in_name in inputs:
             if in_dup:
                 sub_in = inputs[in_name]
-                for sub_in_name in sub_in:
+                for sub_in_name, sub_in_array in sub_in:
                     var = scope.find_var(sub_in_name)
                     tensor = var.get_tensor()
-                    arr = sub_in[sub_in_name]
-                    tensor.set_dims(arr.shape)
-                    tensor.set(arr, place)
+                    tensor.set_dims(sub_in_array.shape)
+                    tensor.set(sub_in_array, place)
             else:
                 var = scope.find_var(in_name)
                 tensor = var.get_tensor()
@@ -65,7 +65,7 @@ def set_output_grad(scope, op, outputs, place):
         if out_name in outputs:
             if out_dup:
                 sub_out = outputs[out_name]
-                for sub_out_name in sub_out:
+                for sub_out_name, sub_out_grad in sub_out:
                     out_tensor = scope.find_var(sub_out_name).get_tensor()
                     grad_tensor = scope.new_var(grad_var_name(
                         sub_out_name)).get_tensor()
@@ -110,7 +110,7 @@ def get_numeric_gradient(scope,
     # we use a for loop to compute the gradient of every element.
     for i in xrange(tensor_size):
         if in_place:
-            set_input(op, inputs, core.CPUPlace())
+            set_input(scope, op, inputs, core.CPUPlace())
 
         # get one input element throw it's index i.
         origin = tensor_to_check.get_float_element(i)
@@ -120,7 +120,7 @@ def get_numeric_gradient(scope,
         y_pos = get_output()
 
         if in_place:
-            set_input(op, inputs, core.CPUPlace())
+            set_input(scope, op, inputs, core.CPUPlace())
 
         x_neg = origin - delta
         tensor_to_check.set_float_element(i, x_neg)
@@ -168,7 +168,10 @@ def get_gradient(scope, op, inputs, outputs, grad_name, place,
 class OpTest(unittest.TestCase):
     def check_output_with_place(self, place):
         self.scope = core.Scope()
-        self.op = create_op(self.scope, self.op_type, self.inputs, self.outputs)
+        op_inputs = self.inputs if hasattr(self, "inputs") else dict()
+        op_attrs = self.attrs if hasattr(self, "attrs") else dict()
+        self.op = create_op(self.scope, self.op_type, op_inputs, self.outputs,
+                            op_attrs)
         if isinstance(place, core.GPUPlace) and not self.op.support_gpu():
             return
         set_input(self.scope, self.op, self.inputs, place)
@@ -227,7 +230,10 @@ class OpTest(unittest.TestCase):
                    in_place=False,
                    max_relative_error=0.005):
         self.scope = core.Scope()
-        self.op = create_op(self.scope, self.op_type, self.inputs, self.outputs)
+        op_inputs = self.inputs if hasattr(self, "inputs") else dict()
+        op_attrs = self.attrs if hasattr(self, "attrs") else dict()
+        self.op = create_op(self.scope, self.op_type, op_inputs, self.outputs,
+                            op_attrs)
         if no_grad_set is None:
             no_grad_set = set()
 

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

@@ -9,7 +9,7 @@ class TestSumOp(OpTest):
         x0 = np.random.random((3, 4)).astype('float32')
         x1 = np.random.random((3, 4)).astype('float32')
         x2 = np.random.random((3, 4)).astype('float32')
-        self.inputs = {"X": {"x0": x0, "x1": x1, "x2": x2}}
+        self.inputs = {"X": [("x0", x0), ("x1", x1), ("x2", x2)]}
         y = x0 + x1 + x2
         self.outputs = {'Out': y}