[xdoctest] reformat example code with google style in No. 270 275-280 (#56476)

python/paddle/distributed/communication/group.py

@@ -144,15 +144,15 @@ def is_initialized():
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
 
-            print(paddle.distributed.is_initialized())
-            # False
+            >>> print(paddle.distributed.is_initialized())
+            False
 
-            paddle.distributed.init_parallel_env()
-            print(paddle.distributed.is_initialized())
-            # True
+            >>> paddle.distributed.init_parallel_env()
+            >>> print(paddle.distributed.is_initialized())
+            True
 
     """
     return _GroupManager.global_group_id in _GroupManager.group_map_by_id
@@ -175,19 +175,19 @@ def destroy_process_group(group=None):
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
 
-            dist.init_parallel_env()
-            group = dist.new_group([0, 1])
+            >>> dist.init_parallel_env()
+            >>> group = dist.new_group([0, 1])
 
-            dist.destroy_process_group(group)
-            print(dist.is_initialized())
-            # True
-            dist.destroy_process_group()
-            print(dist.is_initialized())
-            # False
+            >>> dist.destroy_process_group(group)
+            >>> print(dist.is_initialized())
+            True
+            >>> dist.destroy_process_group()
+            >>> print(dist.is_initialized())
+            False
 
     """
     group = _get_global_group() if group is None else group
@@ -214,13 +214,13 @@ def get_group(id=0):
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
 
-            dist.init_parallel_env()
-            gid = paddle.distributed.new_group([2,4,6])
-            paddle.distributed.get_group(gid.id)
+            >>> dist.init_parallel_env()
+            >>> gid = paddle.distributed.new_group([2,4,6])
+            >>> paddle.distributed.get_group(gid.id)
 
     """
 
@@ -276,12 +276,13 @@ def wait(tensor, group=None, use_calc_stream=True):
     Examples:
         .. code-block:: python
 
-            import paddle
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
 
-            paddle.distributed.init_parallel_env()
-            tindata = paddle.randn(shape=[2, 3])
-            paddle.distributed.all_reduce(tindata, sync_op=True)
-            paddle.distributed.wait(tindata)
+            >>> paddle.distributed.init_parallel_env()
+            >>> tindata = paddle.randn(shape=[2, 3])
+            >>> paddle.distributed.all_reduce(tindata, sync_op=True)
+            >>> paddle.distributed.wait(tindata)
 
     """
     if group is not None and not group.is_member():
@@ -308,12 +309,13 @@ def barrier(group=None):
     Examples:
         .. code-block:: python
 
-            import paddle
-            from paddle.distributed import init_parallel_env
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> from paddle.distributed import init_parallel_env
 
-            paddle.set_device('gpu:%d'%paddle.distributed.ParallelEnv().dev_id)
-            init_parallel_env()
-            paddle.distributed.barrier()
+            >>> paddle.set_device('gpu:%d'%paddle.distributed.ParallelEnv().dev_id)
+            >>> init_parallel_env()
+            >>> paddle.distributed.barrier()
     """
     if group is not None and not group.is_member():
         return
@@ -362,11 +364,12 @@ def get_backend(group=None):
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
 
-            paddle.distributed.init_parallel_env()
-            paddle.distributed.get_backend() # NCCL
+            >>> paddle.distributed.init_parallel_env()
+            >>> paddle.distributed.get_backend()
+            NCCL
     """
     if _warn_cur_rank_not_in_group(group):
         raise RuntimeError("Invalid group specified")

python/paddle/distributed/communication/recv.py

@@ -32,19 +32,19 @@ def recv(tensor, src=0, group=None, sync_op=True):
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            if dist.get_rank() == 0:
-                data = paddle.to_tensor([7, 8, 9])
-                dist.send(data, dst=1)
-            else:
-                data = paddle.to_tensor([1, 2, 3])
-                dist.recv(data, src=0)
-            print(data)
-            # [7, 8, 9] (2 GPUs)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> if dist.get_rank() == 0:
+            ...     data = paddle.to_tensor([7, 8, 9])
+            ...     dist.send(data, dst=1)
+            >>> else:
+            ...     data = paddle.to_tensor([1, 2, 3])
+            ...     dist.recv(data, src=0)
+            >>> print(data)
+            >>> # [7, 8, 9] (2 GPUs)
     """
     return stream.recv(
         tensor, src=src, group=group, sync_op=sync_op, use_calc_stream=False
@@ -70,19 +70,19 @@ def irecv(tensor, src=None, group=None):
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            if dist.get_rank() == 0:
-                data = paddle.to_tensor([7, 8, 9])
-                task = dist.isend(data, dst=1)
-            else:
-                data = paddle.to_tensor([1, 2, 3])
-                task = dist.irecv(data, src=0)
-            task.wait()
-            print(data)
-            # [7, 8, 9] (2 GPUs)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> if dist.get_rank() == 0:
+            ...     data = paddle.to_tensor([7, 8, 9])
+            ...     task = dist.isend(data, dst=1)
+            >>> else:
+            ...     data = paddle.to_tensor([1, 2, 3])
+            ...     task = dist.irecv(data, src=0)
+            >>> task.wait()
+            >>> print(data)
+            >>> # [7, 8, 9] (2 GPUs)
     """
     return recv(tensor, src, group, sync_op=False)

python/paddle/distributed/communication/reduce.py

@@ -34,18 +34,18 @@ class ReduceOp:
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            if dist.get_rank() == 0:
-                data = paddle.to_tensor([[4, 5, 6], [4, 5, 6]])
-            else:
-                data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
-            dist.all_reduce(data, op=dist.ReduceOp.SUM)
-            print(data)
-            # [[5, 7, 9], [5, 7, 9]] (2 GPUs)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> if dist.get_rank() == 0:
+            ...     data = paddle.to_tensor([[4, 5, 6], [4, 5, 6]])
+            >>> else:
+            ...     data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
+            >>> dist.all_reduce(data, op=dist.ReduceOp.SUM)
+            >>> print(data)
+            >>> # [[5, 7, 9], [5, 7, 9]] (2 GPUs)
     """
 
     SUM = 0
@@ -106,19 +106,19 @@ def reduce(tensor, dst, op=ReduceOp.SUM, group=None, sync_op=True):
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            if dist.get_rank() == 0:
-                data = paddle.to_tensor([[4, 5, 6], [4, 5, 6]])
-            else:
-                data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
-            dist.reduce(data, dst=0)
-            print(data)
-            # [[5, 7, 9], [5, 7, 9]] (2 GPUs, out for rank 0)
-            # [[1, 2, 3], [1, 2, 3]] (2 GPUs, out for rank 1)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> if dist.get_rank() == 0:
+            ...     data = paddle.to_tensor([[4, 5, 6], [4, 5, 6]])
+            >>> else:
+            ...     data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
+            >>> dist.reduce(data, dst=0)
+            >>> print(data)
+            >>> # [[5, 7, 9], [5, 7, 9]] (2 GPUs, out for rank 0)
+            >>> # [[1, 2, 3], [1, 2, 3]] (2 GPUs, out for rank 1)
     """
     return stream.reduce(
         tensor,

python/paddle/distributed/communication/reduce_scatter.py

@@ -44,21 +44,21 @@ def reduce_scatter(
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            if dist.get_rank() == 0:
-                data1 = paddle.to_tensor([0, 1])
-                data2 = paddle.to_tensor([2, 3])
-            else:
-                data1 = paddle.to_tensor([4, 5])
-                data2 = paddle.to_tensor([6, 7])
-            dist.reduce_scatter(data1, [data1, data2])
-            print(data1)
-            # [4, 6] (2 GPUs, out for rank 0)
-            # [8, 10] (2 GPUs, out for rank 1)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> if dist.get_rank() == 0:
+            ...     data1 = paddle.to_tensor([0, 1])
+            ...     data2 = paddle.to_tensor([2, 3])
+            >>> else:
+            ...     data1 = paddle.to_tensor([4, 5])
+            ...     data2 = paddle.to_tensor([6, 7])
+            >>> dist.reduce_scatter(data1, [data1, data2])
+            >>> print(data1)
+            >>> # [4, 6] (2 GPUs, out for rank 0)
+            >>> # [8, 10] (2 GPUs, out for rank 1)
 
     """
     return stream.reduce_scatter(
@@ -93,20 +93,20 @@ def _reduce_scatter_base(
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            rank = dist.get_rank()
-            data = paddle.arange(4) + rank
-            # [0, 1, 2, 3] (2 GPUs, for rank 0)
-            # [1, 2, 3, 4] (2 GPUs, for rank 1)
-            output = paddle.empty(shape=[2], dtype=data.dtype)
-            dist.collective._reduce_scatter_base(output, data)
-            print(output)
-            # [1, 3] (2 GPUs, out for rank 0)
-            # [5, 7] (2 GPUs, out for rank 1)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> rank = dist.get_rank()
+            >>> data = paddle.arange(4) + rank
+            >>> # [0, 1, 2, 3] (2 GPUs, for rank 0)
+            >>> # [1, 2, 3, 4] (2 GPUs, for rank 1)
+            >>> output = paddle.empty(shape=[2], dtype=data.dtype)
+            >>> dist.collective._reduce_scatter_base(output, data)
+            >>> print(output)
+            >>> # [1, 3] (2 GPUs, out for rank 0)
+            >>> # [5, 7] (2 GPUs, out for rank 1)
 
     """
     return _reduce_scatter_base_stream(

python/paddle/distributed/communication/scatter.py

@@ -51,22 +51,22 @@ def scatter(tensor, tensor_list=None, src=0, group=None, sync_op=True):
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            if dist.get_rank() == 0:
-                data1 = paddle.to_tensor([7, 8, 9])
-                data2 = paddle.to_tensor([10, 11, 12])
-                dist.scatter(data1, src=1)
-            else:
-                data1 = paddle.to_tensor([1, 2, 3])
-                data2 = paddle.to_tensor([4, 5, 6])
-                dist.scatter(data1, tensor_list=[data1, data2], src=1)
-            print(data1, data2)
-            # [1, 2, 3] [10, 11, 12] (2 GPUs, out for rank 0)
-            # [4, 5, 6] [4, 5, 6] (2 GPUs, out for rank 1)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> if dist.get_rank() == 0:
+            ...     data1 = paddle.to_tensor([7, 8, 9])
+            ...     data2 = paddle.to_tensor([10, 11, 12])
+            ...     dist.scatter(data1, src=1)
+            >>> else:
+            ...     data1 = paddle.to_tensor([1, 2, 3])
+            ...     data2 = paddle.to_tensor([4, 5, 6])
+            ...     dist.scatter(data1, tensor_list=[data1, data2], src=1)
+            >>> print(data1, data2)
+            >>> # [1, 2, 3] [10, 11, 12] (2 GPUs, out for rank 0)
+            >>> # [4, 5, 6] [4, 5, 6] (2 GPUs, out for rank 1)
     """
     return stream.scatter(tensor, tensor_list, src, group, sync_op)
 
@@ -93,19 +93,19 @@ def scatter_object_list(
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            out_object_list = []
-            if dist.get_rank() == 0:
-                in_object_list = [{'foo': [1, 2, 3]}, {'foo': [4, 5, 6]}]
-            else:
-                in_object_list = [{'bar': [1, 2, 3]}, {'bar': [4, 5, 6]}]
-            dist.scatter_object_list(out_object_list, in_object_list, src=1)
-            print(out_object_list)
-            # [{'bar': [1, 2, 3]}] (2 GPUs, out for rank 0)
-            # [{'bar': [4, 5, 6]}] (2 GPUs, out for rank 1)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> out_object_list = []
+            >>> if dist.get_rank() == 0:
+            ...     in_object_list = [{'foo': [1, 2, 3]}, {'foo': [4, 5, 6]}]
+            >>> else:
+            ...     in_object_list = [{'bar': [1, 2, 3]}, {'bar': [4, 5, 6]}]
+            >>> dist.scatter_object_list(out_object_list, in_object_list, src=1)
+            >>> print(out_object_list)
+            >>> # [{'bar': [1, 2, 3]}] (2 GPUs, out for rank 0)
+            >>> # [{'bar': [4, 5, 6]}] (2 GPUs, out for rank 1)
     """
     assert (
         framework.in_dynamic_mode()

python/paddle/distributed/communication/send.py

@@ -32,19 +32,19 @@ def send(tensor, dst=0, group=None, sync_op=True):
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            if dist.get_rank() == 0:
-                data = paddle.to_tensor([7, 8, 9])
-                dist.send(data, dst=1)
-            else:
-                data = paddle.to_tensor([1, 2, 3])
-                dist.recv(data, src=0)
-            print(data)
-            # [7, 8, 9] (2 GPUs)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> if dist.get_rank() == 0:
+            ...     data = paddle.to_tensor([7, 8, 9])
+            ...     dist.send(data, dst=1)
+            >>> else:
+            ...     data = paddle.to_tensor([1, 2, 3])
+            ...     dist.recv(data, src=0)
+            >>> print(data)
+            >>> # [7, 8, 9] (2 GPUs)
     """
     return stream.send(
         tensor, dst=dst, group=group, sync_op=sync_op, use_calc_stream=False
@@ -70,20 +70,20 @@ def isend(tensor, dst, group=None):
     Examples:
         .. code-block:: python
 
-            # required: distributed
-            import paddle
-            import paddle.distributed as dist
-
-            dist.init_parallel_env()
-            if dist.get_rank() == 0:
-                data = paddle.to_tensor([7, 8, 9])
-                task = dist.isend(data, dst=1)
-            else:
-                data = paddle.to_tensor([1, 2, 3])
-                task = dist.irecv(data, src=0)
-            task.wait()
-            print(data)
-            # [7, 8, 9] (2 GPUs)
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> if dist.get_rank() == 0:
+            ...     data = paddle.to_tensor([7, 8, 9])
+            ...     task = dist.isend(data, dst=1)
+            >>> else:
+            ...     data = paddle.to_tensor([1, 2, 3])
+            ...     task = dist.irecv(data, src=0)
+            >>> task.wait()
+            >>> print(data)
+            >>> # [7, 8, 9] (2 GPUs)
 
     """
     return send(tensor, dst, group, sync_op=False)

python/paddle/utils/cpp_extension/extension_utils.py

@@ -906,10 +906,10 @@ def get_build_directory(verbose=False):
 
     .. code-block:: python
 
-        from paddle.utils.cpp_extension import get_build_directory
+        >>> from paddle.utils.cpp_extension import get_build_directory
 
-        build_dir = get_build_directory()
-        print(build_dir)
+        >>> build_dir = get_build_directory()
+        >>> print(build_dir)
 
     """
     root_extensions_directory = os.environ.get('PADDLE_EXTENSION_DIR')