API(fluid.gridents) error message enhancement (#23450)

* API(fluid.gridents) error message enhancement test=develop

* fix unitest failed test=develop

python/paddle/fluid/backward.py

@@ -24,6 +24,7 @@ from .. import compat as cpt
 from . import unique_name
 from . import log_helper
 import paddle.fluid
+from .data_feeder import check_type
 __all__ = [
     'append_backward',
     'gradients',
@@ -1709,5 +1710,14 @@ def gradients(targets, inputs, target_gradients=None, no_grad_set=None):
             z = fluid.gradients([y], x)
             print(z)
     """
+    check_type(targets, 'targets', (framework.Variable, list),
+               'fluid.backward.gradients')
+    check_type(inputs, 'inputs', (framework.Variable, list),
+               'fluid.backward.gradients')
+    check_type(target_gradients, 'target_gradients', (
+        framework.Variable, list, type(None)), 'fluid.backward.gradients')
+    check_type(no_grad_set, 'no_grad_set', (set, type(None)),
+               'fluid.backward.gradients')
+
     outs = calc_gradient(targets, inputs, target_gradients, no_grad_set)
     return _as_list(outs)

python/paddle/fluid/tests/unittests/test_backward.py

@@ -241,6 +241,26 @@ class TestSimpleNet(TestBackward):
         self._check_all(self.net)
 
 
+class TestGradientsError(unittest.TestCase):
+    def test_error(self):
+        x = fluid.data(name='x', shape=[None, 2, 8, 8], dtype='float32')
+        x.stop_gradient = False
+        conv = fluid.layers.conv2d(x, 4, 1, bias_attr=False)
+        y = fluid.layers.relu(conv)
+
+        with self.assertRaises(TypeError):
+            x_grad = fluid.gradients(y.name, x)
+
+        with self.assertRaises(TypeError):
+            x_grad = fluid.gradients(y, x.name)
+
+        with self.assertRaises(TypeError):
+            x_grad = fluid.gradients([y], [x], target_gradients=x.name)
+
+        with self.assertRaises(TypeError):
+            x_grad = fluid.gradients([y], x, no_grad_set=conv)
+
+
 class TestSimpleNetWithErrorParamList(TestBackward):
     def test_parameter_list_type_error(self):
         self.global_block_idx = 0

python/paddle/fluid/tests/unittests/test_imperative_star_gan_with_gradient_penalty.py

@@ -441,7 +441,7 @@ def get_discriminator_loss(image_real, label_org, label_trg, generator,
     d_loss = d_loss_real + d_loss_fake + d_loss_cls
 
     d_loss_gp = gradient_penalty(discriminator, image_real, fake_img,
-                                 discriminator.parameters(), cfg)
+                                 set(discriminator.parameters()), cfg)
     if d_loss_gp is not None:
         d_loss += cfg.lambda_gp * d_loss_gp