[Big Tensor] Fix big tensor problem for paddle.nn.functional.class_center_sample

Author: HeyDavid633

tester/api_config/8_big_tensor/big_tensor_1_8.txt

@@ -30332,6 +30332,11 @@ paddle.nn.functional.channel_shuffle(Tensor([29826162, 9, 4, 4],"float16"), 3, "
 paddle.nn.functional.channel_shuffle(Tensor([29826162, 9, 4, 4],"float16"), 3, "NCHW", None, )
 paddle.nn.functional.class_center_sample(Tensor([356493278],"int32"), 10, 8, )
 paddle.nn.functional.class_center_sample(Tensor([356493280],"int32"), 10, 8, )
+paddle.nn.functional.class_center_sample(Tensor([2294967295],"int32"), 10, 8, )
+paddle.nn.functional.class_center_sample(Tensor([4294967295],"int32"), 10, 8, )
+paddle.nn.functional.class_center_sample(Tensor([4294967295],"int32"), 20, 6, )
+paddle.nn.functional.class_center_sample(Tensor([4294967295],"int32"), 20, 8, )
+paddle.nn.functional.class_center_sample(Tensor([4294967295],"int32"), num_classes=10, num_samples=6, group=None, )
 paddle.nn.functional.conv1d(Tensor([1, 1024, 2228225],"float32"), Tensor([1024, 1024, 3],"float32"), bias=Tensor([1024],"float32"), padding=1, stride=list[2,], dilation=list[1,], groups=1, data_format="NCL", )
 paddle.nn.functional.conv1d(Tensor([1, 128, 17825793],"float32"), Tensor([128, 128, 3],"float32"), bias=Tensor([128],"float32"), padding=1, stride=list[1,], dilation=list[1,], groups=1, data_format="NCL", )
 paddle.nn.functional.conv1d(Tensor([1, 128, 17825793],"float32"), Tensor([128, 128, 3],"float32"), bias=Tensor([128],"float32"), padding=3, stride=list[1,], dilation=list[3,], groups=1, data_format="NCL", )

tester/api_config/8_big_tensor/big_tensor_error_0319_paddleonly.txt

@@ -1742,9 +1742,6 @@ paddle.nn.functional.batch_norm(x=Tensor([715827883, 1, 2, 3],"float32"), runnin
 paddle.nn.functional.batch_norm(x=Tensor([715827883, 1, 3],"float64"), running_mean=Tensor([1],"float64"), running_var=Tensor([1],"float64"), weight=Tensor([1],"float64"), bias=Tensor([1],"float64"), )
 paddle.nn.functional.batch_norm(x=Tensor([715827883, 1, 3],"float64"), running_mean=Tensor([1],"float64"), running_var=Tensor([1],"float64"), weight=Tensor([1],"float64"), bias=Tensor([1],"float64"), epsilon=1e-05, )
 paddle.nn.functional.batch_norm(x=Tensor([715827883, 1, 3],"float64"), running_mean=Tensor([1],"float64"), running_var=Tensor([1],"float64"), weight=Tensor([1],"float64"), bias=Tensor([1],"float64"), epsilon=1e-05, data_format="NCL", )
-paddle.nn.functional.class_center_sample(Tensor([356493278],"int32"), 10, 8, )
-paddle.nn.functional.class_center_sample(Tensor([356493280],"int32"), 10, 8, )
-paddle.nn.functional.class_center_sample(Tensor([2294967295],"int32"), 10, 8, )
 paddle.nn.functional.class_center_sample(Tensor([4294967295],"int32"), 10, 8, )
 paddle.nn.functional.class_center_sample(Tensor([4294967295],"int32"), 20, 6, )
 paddle.nn.functional.class_center_sample(Tensor([4294967295],"int32"), 20, 8, )