fix Assign docstring sample shapes

Author: ShigureNyako

python/paddle/nn/initializer/assign.py

@@ -209,61 +209,64 @@ class Assign(NumpyArrayInitializer):
             >>> data_1 = paddle.ones(shape=[1, 2], dtype='float32')
             >>> weight_attr_1 = paddle.ParamAttr(
             ...     name="linear_weight_1",
-            ...     initializer=paddle.nn.initializer.Assign(np.array([2, 2])),
+            ...     initializer=paddle.nn.initializer.Assign(np.array([[2, 2], [2, 2]])),
             ... )
             >>> bias_attr_1 = paddle.ParamAttr(
             ...     name="linear_bias_1",
-            ...     initializer=paddle.nn.initializer.Assign(np.array([2])),
+            ...     initializer=paddle.nn.initializer.Assign(np.array([2, 2])),
             ... )
             >>> linear_1 = paddle.nn.Linear(2, 2, weight_attr=weight_attr_1, bias_attr=bias_attr_1)
             >>> print(linear_1.weight.numpy())
-            [2. 2.]
+            [[2. 2.]
+             [2. 2.]]
             >>> print(linear_1.bias.numpy())
-            [2.]
+            [2. 2.]
 
             >>> res_1 = linear_1(data_1)
             >>> print(res_1.numpy())
-            [6.]
+            [[6. 6.]]
 
             >>> # python list
             >>> data_2 = paddle.ones(shape=[1, 2], dtype='float32')
             >>> weight_attr_2 = paddle.ParamAttr(
             ...     name="linear_weight_2",
-            ...     initializer=paddle.nn.initializer.Assign([2, 2]),
+            ...     initializer=paddle.nn.initializer.Assign([[2, 2], [2, 2]]),
             ... )
             >>> bias_attr_2 = paddle.ParamAttr(
             ...     name="linear_bias_2",
-            ...     initializer=paddle.nn.initializer.Assign([2]),
+            ...     initializer=paddle.nn.initializer.Assign([2, 2]),
             ... )
             >>> linear_2 = paddle.nn.Linear(2, 2, weight_attr=weight_attr_2, bias_attr=bias_attr_2)
             >>> print(linear_2.weight.numpy())
-            [2. 2.]
+            [[2. 2.]
+             [2. 2.]]
             >>> print(linear_2.bias.numpy())
-            [2.]
+            [2. 2.]
 
             >>> res_2 = linear_2(data_2)
             >>> print(res_2.numpy())
-            [6.]
+            [[6. 6.]]
 
             >>> # tensor
             >>> data_3 = paddle.ones(shape=[1, 2], dtype='float32')
             >>> weight_attr_3 = paddle.ParamAttr(
             ...     name="linear_weight_3",
-            ...     initializer=paddle.nn.initializer.Assign(paddle.full([2], 2)),
+            ...     initializer=paddle.nn.initializer.Assign(paddle.full([2, 2], 2)),
             ... )
             >>> bias_attr_3 = paddle.ParamAttr(
             ...     name="linear_bias_3",
-            ...     initializer=paddle.nn.initializer.Assign(paddle.full([1], 2)),
+            ...     initializer=paddle.nn.initializer.Assign(paddle.full([2], 2)),
             ... )
             >>> linear_3 = paddle.nn.Linear(2, 2, weight_attr=weight_attr_3, bias_attr=bias_attr_3)
             >>> print(linear_3.weight.numpy())
-            [2. 2.]
+            [[2. 2.]
+             [2. 2.]]
             >>> print(linear_3.bias.numpy())
-            [2.]
+            [2. 2.]
 
             >>> res_3 = linear_3(data_3)
             >>> print(res_3.numpy())
-            [6.]
+            [[6. 6.]]
     """
 
     def __init__(