use large input size in tree_conv and teacher_student_sigmoid_loss (#21896)

test=develop

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

@@ -28,7 +28,7 @@ class TestTeacherStudentSigmoidLossOp(OpTest):
 
     def setUp(self):
         self.op_type = "teacher_student_sigmoid_loss"
-        batch_size = 16
+        batch_size = 100
         num_classes = 1
         self.inputs = {
             'X': logit(

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

@@ -54,7 +54,7 @@ class TestTreeConvOp(OpTest):
         self.fea_size = 3
         self.output_size = 1
         self.max_depth = 2
-        self.batch_size = 1
+        self.batch_size = 2
         self.num_filters = 1
         adj_array = [
             1, 2, 1, 3, 1, 4, 1, 5, 2, 6, 2, 7, 2, 8, 4, 9, 4, 10, 5, 11, 6, 12,

python/paddle/fluid/tests/unittests/white_list/check_shape_white_list.py

@@ -20,6 +20,5 @@ NOT_CHECK_OP_LIST = [
 NEED_TO_FIX_OP_LIST = [
     'sequence_scatter', 'log_loss', 'sequence_topk_avg_pooling', 'matmul',
     'add_position_encoding', 'margin_rank_loss', 'elementwise_pow',
-    'fused_elemwise_activation', 'tree_conv', 'mul',
-    'teacher_student_sigmoid_loss'
+    'fused_elemwise_activation', 'mul'
 ]