Fix Python IndexError of case13: paddle.static.nn.batch_norm (#50011)

* add channel_num check for paddle.static.nn.batch_norm

* fix bugs

* fix bugs

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

@@ -768,6 +768,10 @@ class TestBatchNormOpError(unittest.TestCase):
             )
             self.assertRaises(TypeError, paddle.static.nn.batch_norm, x2)
 
+            # the first dimension of input for batch_norm must between [2d, 5d].
+            x3 = paddle.static.data("", shape=[0], dtype="float32")
+            self.assertRaises(ValueError, paddle.static.nn.batch_norm, x3)
+
 
 class TestDygraphBatchNormAPIError(unittest.TestCase):
     def test_errors(self):

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

@@ -179,7 +179,7 @@ class TestFoldOpError(unittest.TestCase):
         with program_guard(Program(), Program()):
 
             def test_input_shape():
-                # input_shpae must be 3-D
+                # input_shape must be 3-D
                 x = paddle.randn(shape=[2, 3, 6, 7], dtype="float32")
                 out = fold(x, output_sizes=[2, 3], kernel_sizes=[2, 2])
 

python/paddle/static/nn/common.py

@@ -2731,6 +2731,12 @@ def batch_norm(
         dtype = core.VarDesc.VarType.FP32
 
     input_shape = input.shape
+    if len(input.shape) < 2 or len(input.shape) > 5:
+        raise ValueError(
+            'expected 2D or 3D or 4D or 5D input (got {}D input, input shape is: {})'.format(
+                len(input.shape), input_shape
+            )
+        )
     if data_layout == 'NCHW':
         channel_num = input_shape[1]
     else: