[xdoctest][task 60-64] reformat example code with google style in...

[xdoctest][task 60-64] reformat example code with google style in `geometric/*` ,`hapi/callbacks.py` (#55919)

* [Doctest]fix No.21, test=docs_preview

* Revert "[Doctest]fix No.21, test=docs_preview"

This reverts commit 76bcdb280e254d682be6fc6f85588f1940bb1ade.

* [Doctest]fix No.60-64, test=docs_preview

python/paddle/geometric/math.py

@@ -43,11 +43,13 @@ def segment_sum(data, segment_ids, name=None):
     Examples:
         .. code-block:: python
 
-            import paddle
-            data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
-            segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
-            out = paddle.geometric.segment_sum(data, segment_ids)
-            #Outputs: [[4., 4., 4.], [4., 5., 6.]]
+            >>> import paddle
+            >>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
+            >>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
+            >>> out = paddle.geometric.segment_sum(data, segment_ids)
+            >>> print(out.numpy())
+            [[4. 4. 4.]
+             [4. 5. 6.]]
 
     """
     if in_dynamic_mode():
@@ -99,11 +101,13 @@ def segment_mean(data, segment_ids, name=None):
     Examples:
         .. code-block:: python
 
-            import paddle
-            data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
-            segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
-            out = paddle.geometric.segment_mean(data, segment_ids)
-            #Outputs: [[2., 2., 2.], [4., 5., 6.]]
+            >>> import paddle
+            >>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
+            >>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
+            >>> out = paddle.geometric.segment_mean(data, segment_ids)
+            >>> print(out.numpy())
+            [[2. 2. 2.]
+             [4. 5. 6.]]
 
     """
 
@@ -155,11 +159,13 @@ def segment_min(data, segment_ids, name=None):
     Examples:
         .. code-block:: python
 
-            import paddle
-            data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
-            segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
-            out = paddle.geometric.segment_min(data, segment_ids)
-            #Outputs:  [[1., 2., 1.], [4., 5., 6.]]
+            >>> import paddle
+            >>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
+            >>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
+            >>> out = paddle.geometric.segment_min(data, segment_ids)
+            >>> print(out.numpy())
+            [[1. 2. 1.]
+             [4. 5. 6.]]
 
     """
 
@@ -211,11 +217,13 @@ def segment_max(data, segment_ids, name=None):
     Examples:
         .. code-block:: python
 
-            import paddle
-            data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
-            segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
-            out = paddle.geometric.segment_max(data, segment_ids)
-            #Outputs: [[3., 2., 3.], [4., 5., 6.]]
+            >>> import paddle
+            >>> data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
+            >>> segment_ids = paddle.to_tensor([0, 0, 1], dtype='int32')
+            >>> out = paddle.geometric.segment_max(data, segment_ids)
+            >>> print(out.numpy())
+            [[3. 2. 3.]
+             [4. 5. 6.]]
 
     """
 

python/paddle/geometric/message_passing/send_recv.py

@@ -88,26 +88,34 @@ def send_u_recv(
     Examples:
         .. code-block:: python
 
-            import paddle
-
-            x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
-            indexes = paddle.to_tensor([[0, 1], [1, 2], [2, 1], [0, 0]], dtype="int32")
-            src_index, dst_index = indexes[:, 0], indexes[:, 1]
-            out = paddle.geometric.send_u_recv(x, src_index, dst_index, reduce_op="sum")
-            # Outputs: [[0., 2., 3.], [2., 8., 10.], [1., 4., 5.]]
-
-            x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
-            indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
-            src_index, dst_index = indexes[:, 0], indexes[:, 1]
-            out_size = paddle.max(dst_index) + 1
-            out = paddle.geometric.send_u_recv(x, src_index, dst_index, reduce_op="sum", out_size=out_size)
-            # Outputs: [[0., 2., 3.], [[2., 8., 10.]]]
-
-            x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
-            indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
-            src_index, dst_index = indexes[:, 0], indexes[:, 1]
-            out = paddle.geometric.send_u_recv(x, src_index, dst_index, reduce_op="sum")
-            # Outputs: [[0., 2., 3.], [2., 8., 10.], [0., 0., 0.]]
+            >>> import paddle
+
+            >>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
+            >>> indexes = paddle.to_tensor([[0, 1], [1, 2], [2, 1], [0, 0]], dtype="int32")
+            >>> src_index, dst_index = indexes[:, 0], indexes[:, 1]
+            >>> out = paddle.geometric.send_u_recv(x, src_index, dst_index, reduce_op="sum")
+            >>> print(out.numpy())
+            [[ 0. 2. 3.]
+             [ 2. 8. 10.]
+             [ 1. 4. 5.]]
+
+            >>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
+            >>> indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
+            >>> src_index, dst_index = indexes[:, 0], indexes[:, 1]
+            >>> out_size = paddle.max(dst_index) + 1
+            >>> out = paddle.geometric.send_u_recv(x, src_index, dst_index, reduce_op="sum", out_size=out_size)
+            >>> print(out.numpy())
+            [[ 0. 2. 3.]
+             [ 2. 8. 10.]]
+
+            >>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
+            >>> indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
+            >>> src_index, dst_index = indexes[:, 0], indexes[:, 1]
+            >>> out = paddle.geometric.send_u_recv(x, src_index, dst_index, reduce_op="sum")
+            >>> print(out.numpy())
+            [[ 0. 2. 3.]
+             [ 2. 8. 10.]
+             [ 0. 0. 0.]]
 
     """
 
@@ -247,29 +255,37 @@ def send_ue_recv(
     Examples:
         .. code-block:: python
 
-            import paddle
-
-            x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
-            y = paddle.to_tensor([1, 1, 1, 1], dtype="float32")
-            indexes = paddle.to_tensor([[0, 1], [1, 2], [2, 1], [0, 0]], dtype="int32")
-            src_index, dst_index = indexes[:, 0], indexes[:, 1]
-            out = paddle.geometric.send_ue_recv(x, y, src_index, dst_index, message_op="add", reduce_op="sum")
-            # Outputs: [[1., 3., 4.], [4., 10., 12.], [2., 5., 6.]]
-
-            x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
-            y = paddle.to_tensor([1, 1, 1], dtype="float32")
-            indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
-            src_index, dst_index = indexes[:, 0], indexes[:, 1]
-            out_size = paddle.max(dst_index) + 1
-            out = paddle.geometric.send_ue_recv(x, y, src_index, dst_index, message_op="add", reduce_op="sum", out_size=out_size)
-            # Outputs: [[1., 3., 4.], [[4., 10., 12.]]]
-
-            x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
-            y = paddle.to_tensor([1, 1, 1], dtype="float32")
-            indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
-            src_index, dst_index = indexes[:, 0], indexes[:, 1]
-            out = paddle.geometric.send_ue_recv(x, y, src_index, dst_index, message_op="add", reduce_op="sum")
-            # Outputs: [[1., 3., 4.], [4., 10., 12.], [0., 0., 0.]]
+            >>> import paddle
+
+            >>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
+            >>> y = paddle.to_tensor([1, 1, 1, 1], dtype="float32")
+            >>> indexes = paddle.to_tensor([[0, 1], [1, 2], [2, 1], [0, 0]], dtype="int32")
+            >>> src_index, dst_index = indexes[:, 0], indexes[:, 1]
+            >>> out = paddle.geometric.send_ue_recv(x, y, src_index, dst_index, message_op="add", reduce_op="sum")
+            >>> print(out.numpy())
+            [[ 1. 3. 4.]
+             [ 4. 10. 12.]
+             [ 2. 5. 6.]]
+
+            >>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
+            >>> y = paddle.to_tensor([1, 1, 1], dtype="float32")
+            >>> indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
+            >>> src_index, dst_index = indexes[:, 0], indexes[:, 1]
+            >>> out_size = paddle.max(dst_index) + 1
+            >>> out = paddle.geometric.send_ue_recv(x, y, src_index, dst_index, message_op="add", reduce_op="sum", out_size=out_size)
+            >>> print(out.numpy())
+            [[ 1. 3. 4.]
+             [ 4. 10. 12.]]
+
+            >>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
+            >>> y = paddle.to_tensor([1, 1, 1], dtype="float32")
+            >>> indexes = paddle.to_tensor([[0, 1], [2, 1], [0, 0]], dtype="int32")
+            >>> src_index, dst_index = indexes[:, 0], indexes[:, 1]
+            >>> out = paddle.geometric.send_ue_recv(x, y, src_index, dst_index, message_op="add", reduce_op="sum")
+            >>> print(out.numpy())
+            [[ 1. 3. 4.]
+             [ 4. 10. 12.]
+             [ 0. 0. 0.]]
 
     """
 
@@ -425,15 +441,19 @@ def send_uv(x, y, src_index, dst_index, message_op="add", name=None):
 
         .. code-block:: python
 
-            import paddle
-
-            x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
-            y = paddle.to_tensor([[0, 1, 2], [2, 3, 4], [4, 5, 6]], dtype="float32")
-            indexes = paddle.to_tensor([[0, 1], [1, 2], [2, 1], [0, 0]], dtype="int32")
-            src_index = indexes[:, 0]
-            dst_index = indexes[:, 1]
-            out = paddle.geometric.send_uv(x, y, src_index, dst_index, message_op="add")
-            # Outputs: [[2., 5., 7.], [5., 9., 11.], [4., 9., 11.], [0., 3., 5.]]
+            >>> import paddle
+
+            >>> x = paddle.to_tensor([[0, 2, 3], [1, 4, 5], [2, 6, 7]], dtype="float32")
+            >>> y = paddle.to_tensor([[0, 1, 2], [2, 3, 4], [4, 5, 6]], dtype="float32")
+            >>> indexes = paddle.to_tensor([[0, 1], [1, 2], [2, 1], [0, 0]], dtype="int32")
+            >>> src_index = indexes[:, 0]
+            >>> dst_index = indexes[:, 1]
+            >>> out = paddle.geometric.send_uv(x, y, src_index, dst_index, message_op="add")
+            >>> print(out.numpy())
+            [[ 2. 5. 7.]
+             [ 5. 9. 11.]
+             [ 4. 9. 11.]
+             [ 0. 3. 5.]]
 
     """
 

python/paddle/geometric/reindex.py

@@ -69,18 +69,21 @@ def reindex_graph(
     Examples:
         .. code-block:: python
 
-            import paddle
-
-            x = [0, 1, 2]
-            neighbors = [8, 9, 0, 4, 7, 6, 7]
-            count = [2, 3, 2]
-            x = paddle.to_tensor(x, dtype="int64")
-            neighbors = paddle.to_tensor(neighbors, dtype="int64")
-            count = paddle.to_tensor(count, dtype="int32")
-            reindex_src, reindex_dst, out_nodes = paddle.geometric.reindex_graph(x, neighbors, count)
-            # reindex_src: [3, 4, 0, 5, 6, 7, 6]
-            # reindex_dst: [0, 0, 1, 1, 1, 2, 2]
-            # out_nodes: [0, 1, 2, 8, 9, 4, 7, 6]
+            >>> import paddle
+
+            >>> x = [0, 1, 2]
+            >>> neighbors = [8, 9, 0, 4, 7, 6, 7]
+            >>> count = [2, 3, 2]
+            >>> x = paddle.to_tensor(x, dtype="int64")
+            >>> neighbors = paddle.to_tensor(neighbors, dtype="int64")
+            >>> count = paddle.to_tensor(count, dtype="int32")
+            >>> reindex_src, reindex_dst, out_nodes = paddle.geometric.reindex_graph(x, neighbors, count)
+            >>> print(reindex_src.numpy())
+            [3 4 0 5 6 7 6]
+            >>> print(reindex_dst.numpy())
+            [0 0 1 1 1 2 2]
+            >>> print(out_nodes.numpy())
+            [0 1 2 8 9 4 7 6]
 
     """
     use_buffer_hashtable = (
@@ -182,24 +185,27 @@ def reindex_heter_graph(
     Examples:
         .. code-block:: python
 
-            import paddle
-
-            x = [0, 1, 2]
-            neighbors_a = [8, 9, 0, 4, 7, 6, 7]
-            count_a = [2, 3, 2]
-            x = paddle.to_tensor(x, dtype="int64")
-            neighbors_a = paddle.to_tensor(neighbors_a, dtype="int64")
-            count_a = paddle.to_tensor(count_a, dtype="int32")
-            neighbors_b = [0, 2, 3, 5, 1]
-            count_b = [1, 3, 1]
-            neighbors_b = paddle.to_tensor(neighbors_b, dtype="int64")
-            count_b = paddle.to_tensor(count_b, dtype="int32")
-            neighbors = [neighbors_a, neighbors_b]
-            count = [count_a, count_b]
-            reindex_src, reindex_dst, out_nodes = paddle.geometric.reindex_heter_graph(x, neighbors, count)
-            # reindex_src: [3, 4, 0, 5, 6, 7, 6, 0, 2, 8, 9, 1]
-            # reindex_dst: [0, 0, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2]
-            # out_nodes: [0, 1, 2, 8, 9, 4, 7, 6, 3, 5]
+            >>> import paddle
+
+            >>> x = [0, 1, 2]
+            >>> neighbors_a = [8, 9, 0, 4, 7, 6, 7]
+            >>> count_a = [2, 3, 2]
+            >>> x = paddle.to_tensor(x, dtype="int64")
+            >>> neighbors_a = paddle.to_tensor(neighbors_a, dtype="int64")
+            >>> count_a = paddle.to_tensor(count_a, dtype="int32")
+            >>> neighbors_b = [0, 2, 3, 5, 1]
+            >>> count_b = [1, 3, 1]
+            >>> neighbors_b = paddle.to_tensor(neighbors_b, dtype="int64")
+            >>> count_b = paddle.to_tensor(count_b, dtype="int32")
+            >>> neighbors = [neighbors_a, neighbors_b]
+            >>> count = [count_a, count_b]
+            >>> reindex_src, reindex_dst, out_nodes = paddle.geometric.reindex_heter_graph(x, neighbors, count)
+            >>> print(reindex_src.numpy())
+            [3 4 0 5 6 7 6 0 2 8 9 1]
+            >>> print(reindex_dst.numpy())
+            [0 0 1 1 1 2 2 0 1 1 1 2]
+            >>> print(out_nodes.numpy())
+            [0 1 2 8 9 4 7 6 3 5]
 
     """
     use_buffer_hashtable = (

python/paddle/geometric/sampling/neighbors.py

@@ -77,18 +77,18 @@ def sample_neighbors(
     Examples:
         .. code-block:: python
 
-            import paddle
-
-            # edges: (3, 0), (7, 0), (0, 1), (9, 1), (1, 2), (4, 3), (2, 4),
-            #        (9, 5), (3, 5), (9, 6), (1, 6), (9, 8), (7, 8)
-            row = [3, 7, 0, 9, 1, 4, 2, 9, 3, 9, 1, 9, 7]
-            colptr = [0, 2, 4, 5, 6, 7, 9, 11, 11, 13, 13]
-            nodes = [0, 8, 1, 2]
-            sample_size = 2
-            row = paddle.to_tensor(row, dtype="int64")
-            colptr = paddle.to_tensor(colptr, dtype="int64")
-            nodes = paddle.to_tensor(nodes, dtype="int64")
-            out_neighbors, out_count = paddle.geometric.sample_neighbors(row, colptr, nodes, sample_size=sample_size)
+            >>> import paddle
+
+            >>> # edges: (3, 0), (7, 0), (0, 1), (9, 1), (1, 2), (4, 3), (2, 4),
+            >>> #        (9, 5), (3, 5), (9, 6), (1, 6), (9, 8), (7, 8)
+            >>> row = [3, 7, 0, 9, 1, 4, 2, 9, 3, 9, 1, 9, 7]
+            >>> colptr = [0, 2, 4, 5, 6, 7, 9, 11, 11, 13, 13]
+            >>> nodes = [0, 8, 1, 2]
+            >>> sample_size = 2
+            >>> row = paddle.to_tensor(row, dtype="int64")
+            >>> colptr = paddle.to_tensor(colptr, dtype="int64")
+            >>> nodes = paddle.to_tensor(nodes, dtype="int64")
+            >>> out_neighbors, out_count = paddle.geometric.sample_neighbors(row, colptr, nodes, sample_size=sample_size)
 
     """
 
@@ -228,20 +228,20 @@ def weighted_sample_neighbors(
     Examples:
         .. code-block:: python
 
-            import paddle
-
-            # edges: (3, 0), (7, 0), (0, 1), (9, 1), (1, 2), (4, 3), (2, 4),
-            #        (9, 5), (3, 5), (9, 6), (1, 6), (9, 8), (7, 8)
-            row = [3, 7, 0, 9, 1, 4, 2, 9, 3, 9, 1, 9, 7]
-            colptr = [0, 2, 4, 5, 6, 7, 9, 11, 11, 13, 13]
-            weight = [0.1, 0.5, 0.2, 0.5, 0.9, 1.9, 2.0, 2.1, 0.01, 0.9, 0,12, 0.59, 0.67]
-            nodes = [0, 8, 1, 2]
-            sample_size = 2
-            row = paddle.to_tensor(row, dtype="int64")
-            colptr = paddle.to_tensor(colptr, dtype="int64")
-            weight = paddle.to_tensor(weight, dtype="float32")
-            nodes = paddle.to_tensor(nodes, dtype="int64")
-            out_neighbors, out_count = paddle.geometric.weighted_sample_neighbors(row, colptr, weight, nodes, sample_size=sample_size)
+            >>> import paddle
+
+            >>> # edges: (3, 0), (7, 0), (0, 1), (9, 1), (1, 2), (4, 3), (2, 4),
+            >>> #        (9, 5), (3, 5), (9, 6), (1, 6), (9, 8), (7, 8)
+            >>> row = [3, 7, 0, 9, 1, 4, 2, 9, 3, 9, 1, 9, 7]
+            >>> colptr = [0, 2, 4, 5, 6, 7, 9, 11, 11, 13, 13]
+            >>> weight = [0.1, 0.5, 0.2, 0.5, 0.9, 1.9, 2.0, 2.1, 0.01, 0.9, 0,12, 0.59, 0.67]
+            >>> nodes = [0, 8, 1, 2]
+            >>> sample_size = 2
+            >>> row = paddle.to_tensor(row, dtype="int64")
+            >>> colptr = paddle.to_tensor(colptr, dtype="int64")
+            >>> weight = paddle.to_tensor(weight, dtype="float32")
+            >>> nodes = paddle.to_tensor(nodes, dtype="int64")
+            >>> out_neighbors, out_count = paddle.geometric.weighted_sample_neighbors(row, colptr, weight, nodes, sample_size=sample_size)
 
     """