Add unit tests for cases that `mul_op` takes tensors as inputs

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

@@ -2,6 +2,7 @@ import unittest
 import numpy as np
 from gradient_checker import GradientChecker, create_op
 from op_test_util import OpTestMeta
+from paddle.v2.framework.op import Operator
 
 
 class TestMulOp(unittest.TestCase):
@@ -16,6 +17,22 @@ class TestMulOp(unittest.TestCase):
         self.outputs = {'Out': np.dot(self.inputs['X'], self.inputs['Y'])}
 
 
+class TestMulOp2(unittest.TestCase):
+    __metaclass__ = OpTestMeta
+
+    def setUp(self):
+        self.type = "mul"
+        self.inputs = {
+            'X': np.random.random((15, 4, 12, 10)).astype("float32"),
+            'Y': np.random.random((4, 30, 8, 2, 9)).astype("float32")
+        }
+        self.attrs = {'x_num_row_dims': 2, 'y_num_row_dims': 3}
+        self.outputs = {
+            'Out': np.dot(self.inputs['X'].reshape(15 * 4, 12 * 10),
+                          self.inputs['Y'].reshape(4 * 30, 8 * 2 * 9))
+        }
+
+
 class TestMulGradOp(GradientChecker):
     def setUp(self):
         self.op = create_op("mul")
@@ -49,6 +66,39 @@ class TestMulGradOp(GradientChecker):
             no_grad_set={"Y"})
 
 
+class TestMulGradTest2(GradientChecker):
+    def setUp(self):
+        self.op = Operator(
+            "mul", X="X", Y="Y", Out="Out", x_num_row_dims=2, y_num_row_dims=3)
+        self.inputs = {
+            "X": np.random.random((15, 4, 12, 10)).astype("float32"),
+            "Y": np.random.random((4, 30, 8, 2, 9)).astype("float32")
+        }
+
+    def test_cpu_gpu_compare(self):
+        self.compare_grad(self.op, self.inputs)
+
+    def test_normal(self):
+        self.check_grad(
+            self.op, self.inputs, ["X", "Y"], "Out", max_relative_error=0.5)
+
+    def test_ignore_x(self):
+        self.check_grad(
+            self.op,
+            self.inputs, ["Y"],
+            "Out",
+            max_relative_error=0.5,
+            no_grad_set={"X"})
+
+    def test_ignore_y(self):
+        self.check_grad(
+            self.op,
+            self.inputs, ["X"],
+            "Out",
+            max_relative_error=0.5,
+            no_grad_set={"Y"})
+
+
 # TODO(dzh,qijun) : mulgrad test case need transpose feature of blas library
 
 if __name__ == '__main__':