update 2.0 public api in all left files

python/paddle/__init__.py

@@ -21,8 +21,7 @@
      import paddle from the source directory; please install paddlepaddle*.whl firstly.'''
                      )
 
-import paddle.batch
-batch = batch.batch
+from .batch import batch  # noqa: F401
 from .fluid import monkey_patch_variable
 from .fluid.dygraph import monkey_patch_math_varbase
 monkey_patch_variable()
@@ -135,7 +134,6 @@
 from .tensor.manipulation import squeeze_  # noqa: F401
 from .tensor.manipulation import stack  # noqa: F401
 from .tensor.manipulation import strided_slice  # noqa: F401
-from .tensor.manipulation import transpose  # noqa: F401
 from .tensor.manipulation import unique  # noqa: F401
 from .tensor.manipulation import unsqueeze  # noqa: F401
 from .tensor.manipulation import unsqueeze_  # noqa: F401
@@ -191,7 +189,6 @@
 from .tensor.math import multiply  # noqa: F401
 from .tensor.math import add  # noqa: F401
 from .tensor.math import subtract  # noqa: F401
-from .tensor.math import atan  # noqa: F401
 from .tensor.math import logsumexp  # noqa: F401
 from .tensor.math import inverse  # noqa: F401
 from .tensor.math import log1p  # noqa: F401
@@ -244,9 +241,8 @@
 from .framework import load  # noqa: F401
 from .framework import DataParallel  # noqa: F401
 
-from .framework import set_default_dtype  #DEFINE_ALIAS
-from .framework import get_default_dtype  #DEFINE_ALIAS
-from .framework import set_grad_enabled  #DEFINE_ALIAS
+from .framework import set_default_dtype  # noqa: F401
+from .framework import get_default_dtype  # noqa: F401
 
 from .tensor.search import index_sample  # noqa: F401
 from .tensor.stat import mean  # noqa: F401
@@ -281,7 +277,7 @@
 from .tensor.random import check_shape  # noqa: F401
 disable_static()
 
-__all__ = [     #noqa
+__all__ = [  # noqa
            'dtype',
            'uint8',
            'int8',
@@ -323,7 +319,6 @@
            'cos',
            'tan',
            'mean',
-           'XPUPlace',
            'mv',
            'in_dynamic_mode',
            'min',
@@ -360,7 +355,6 @@
            'to_tensor',
            'gather_nd',
            'isinf',
-           'set_device',
            'uniform',
            'floor_divide',
            'remainder',
@@ -384,8 +378,6 @@
            'rand',
            'less_equal',
            'triu',
-           'is_compiled_with_cuda',
-           'is_compiled_with_rocm',
            'sin',
            'dist',
            'unbind',
@@ -414,8 +406,6 @@
            'bernoulli',
            'summary',
            'sinh',
-           'is_compiled_with_xpu',
-           'is_compiled_with_npu',
            'round',
            'DataParallel',
            'argmin',
@@ -437,7 +427,6 @@
            'not_equal',
            'sum',
            'tile',
-           'get_device',
            'greater_equal',
            'isfinite',
            'create_parameter',
@@ -470,7 +459,6 @@
            'scatter_nd',
            'set_default_dtype',
            'expand_as',
-           'get_cudnn_version',
            'stack',
            'sqrt',
            'cholesky',
@@ -484,7 +472,6 @@
            'logical_not',
            'add_n',
            'minimum',
-           'ComplexTensor',
            'scatter',
            'scatter_',
            'floor',
@@ -493,5 +480,6 @@
            'log2',
            'log10',
            'concat',
-           'check_shape'
+           'check_shape',
+           'standard_normal'
 ]

python/paddle/amp/__init__.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .auto_cast import auto_cast
-from .grad_scaler import GradScaler
+from .auto_cast import auto_cast  # noqa: F401
+from .grad_scaler import GradScaler  # noqa: F401
 
 __all__ = ['auto_cast', 'GradScaler']

python/paddle/amp/auto_cast.py

@@ -14,7 +14,7 @@
 
 from paddle.fluid.dygraph.amp import amp_guard
 
-__all__ = ['auto_cast']
+__all__ = []
 
 
 def auto_cast(enable=True, custom_white_list=None, custom_black_list=None):

python/paddle/amp/grad_scaler.py

@@ -14,7 +14,7 @@
 
 from paddle.fluid.dygraph.amp import AmpScaler
 
-__all__ = ['GradScaler']
+__all__ = []
 
 
 class GradScaler(AmpScaler):

python/paddle/autograd/__init__.py

@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from ..fluid.dygraph.base import grad  #DEFINE_ALIAS
-
-from . import backward_mode
-from .backward_mode import backward
-from .py_layer import PyLayer, PyLayerContext
+from ..fluid.dygraph.base import grad  # noqa: F401
+from . import backward_mode  # noqa: F401
+from .backward_mode import backward  # noqa: F401
+from .py_layer import PyLayer, PyLayerContext  # noqa: F401
 
 __all__ = ['grad', 'backward', 'PyLayer', 'PyLayerContext']

python/paddle/autograd/backward_mode.py

@@ -15,7 +15,7 @@
 from paddle.fluid import core
 from paddle.fluid import framework
 import paddle
-__all__ = ['backward']
+__all__ = []
 
 
 @framework.dygraph_only

python/paddle/autograd/py_layer.py

@@ -15,7 +15,7 @@
 import paddle
 from paddle.fluid.framework import dygraph_only
 from paddle.fluid import core
-__all__ = ['PyLayer', 'PyLayerContext']
+__all__ = []
 
 
 class PyLayerContext(object):

python/paddle/batch.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__all__ = ['batch']
+__all__ = []
 
 
 def batch(reader, batch_size, drop_last=False):
@@ -35,11 +35,11 @@ def batch(reader, batch_size, drop_last=False):
     Examples:
         .. code-block:: python
 
-            import paddle.fluid as fluid
+            import paddle
             def reader():
                 for i in range(10):
                     yield i
-            batch_reader = fluid.io.batch(reader, batch_size=2)
+            batch_reader = paddle.batch(reader, batch_size=2)
 
             for data in batch_reader():
                 print(data)
@@ -60,7 +60,7 @@ def batch_reader():
             if len(b) == batch_size:
                 yield b
                 b = []
-        if drop_last == False and len(b) != 0:
+        if drop_last is False and len(b) != 0:
             yield b
 
     # Batch size check

python/paddle/compat.py

@@ -15,18 +15,11 @@
 import six
 import math
 
-__all__ = [
-    'long_type',
-    'to_text',
-    'to_bytes',
-    'round',
-    'floor_division',
-    'get_exception_message',
-]
+__all__ = []
 
 if six.PY2:
     int_type = int
-    long_type = long
+    long_type = long  # noqa: F821
 else:
     int_type = int
     long_type = int

python/paddle/device.py

@@ -18,21 +18,16 @@
 from paddle.fluid import core
 from paddle.fluid import framework
 from paddle.fluid.dygraph.parallel import ParallelEnv
-from paddle.fluid.framework import is_compiled_with_cuda  #DEFINE_ALIAS
-from paddle.fluid.framework import is_compiled_with_rocm  #DEFINE_ALIAS
+from paddle.fluid.framework import is_compiled_with_cuda  # noqa: F401
+from paddle.fluid.framework import is_compiled_with_rocm  # noqa: F401
 
-__all__ = [
+
+__all__ = [  # npqa
     'get_cudnn_version',
     'set_device',
     'get_device',
     'XPUPlace',
     'is_compiled_with_xpu',
-    #            'cpu_places',
-    #            'CPUPlace',
-    #            'cuda_pinned_places',
-    #            'cuda_places',
-    #            'CUDAPinnedPlace',
-    #            'CUDAPlace',
     'is_compiled_with_cuda',
     'is_compiled_with_rocm',
     'is_compiled_with_npu'
@@ -68,7 +63,7 @@ def is_compiled_with_xpu():
         .. code-block:: python
 
             import paddle
-            support_xpu = paddle.device.is_compiled_with_xpu()
+            support_xpu = paddle.is_compiled_with_xpu()
     """
     return core.is_compiled_with_xpu()
 
@@ -82,9 +77,10 @@ def XPUPlace(dev_id):
 
     Examples:
         .. code-block:: python
-
+            # required: xpu
+
             import paddle
-            place = paddle.device.XPUPlace(0)
+            place = paddle.XPUPlace(0)
     """
     return core.XPUPlace(dev_id)
 
@@ -127,15 +123,13 @@ def _convert_to_place(device):
         place = core.CPUPlace()
     elif lower_device == 'gpu':
         if not core.is_compiled_with_cuda():
-            raise ValueError(
-                "The device should not be 'gpu', " \
-                "since PaddlePaddle is not compiled with CUDA")
+            raise ValueError("The device should not be 'gpu', "
+                             "since PaddlePaddle is not compiled with CUDA")
         place = core.CUDAPlace(ParallelEnv().dev_id)
     elif lower_device == 'xpu':
         if not core.is_compiled_with_xpu():
-            raise ValueError(
-                "The device should not be 'xpu', " \
-                "since PaddlePaddle is not compiled with XPU")
+            raise ValueError("The device should not be 'xpu', "
+                             "since PaddlePaddle is not compiled with XPU")
         selected_xpus = os.getenv("FLAGS_selected_xpus", "0").split(",")
         device_id = int(selected_xpus[0])
         place = core.XPUPlace(device_id)
@@ -149,7 +143,7 @@ def _convert_to_place(device):
         if avaliable_gpu_device:
             if not core.is_compiled_with_cuda():
                 raise ValueError(
-                    "The device should not be {}, since PaddlePaddle is " \
+                    "The device should not be {}, since PaddlePaddle is "
                     "not compiled with CUDA".format(avaliable_gpu_device))
             device_info_list = device.split(':', 1)
             device_id = device_info_list[1]
@@ -158,7 +152,7 @@ def _convert_to_place(device):
         if avaliable_xpu_device:
             if not core.is_compiled_with_xpu():
                 raise ValueError(
-                    "The device should not be {}, since PaddlePaddle is " \
+                    "The device should not be {}, since PaddlePaddle is "
                     "not compiled with XPU".format(avaliable_xpu_device))
             device_info_list = device.split(':', 1)
             device_id = device_info_list[1]

python/paddle/distributed/parallel.py

@@ -29,9 +29,7 @@
 from paddle.fluid.dygraph.parallel import ParallelEnv
 from paddle.distributed.fleet.base.private_helper_function import wait_server_ready  # noqa: F401
 
-__all__ = [  #noqa
-    "init_parallel_env"
-]
+__all__ = []
 
 ParallelStrategy = core.ParallelStrategy
 
@@ -152,7 +150,6 @@ def _check_var_exists(var_name):
     init_gloo = int(os.getenv("PADDLE_WITH_GLOO", "0"))
     if init_gloo:
         ep_rank_0 = parallel_env.trainer_endpoints[0].split(":")
-        ep_rank = parallel_env.trainer_endpoints[parallel_env.rank].split(":")
         manager = Manager()
         # glboal dict to store status
         http_server_d = manager.dict()

python/paddle/incubate/__init__.py

@@ -12,10 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from . import optimizer
-from . import checkpoint
-from ..fluid.layer_helper import LayerHelper
+from .optimizer import LookAhead  # noqa: F401
+from .optimizer import ModelAverage  # noqa: F401
+from .checkpoint import auto_checkpoint  # noqa: F401
+from ..fluid.layer_helper import LayerHelper  # noqa: F401
 
-__all__ = []
-__all__ += optimizer.__all__
-__all__ += checkpoint.__all__
+__all__ = [  # noqa
+    'LookAhead', 'ModelAverage'
+]

python/paddle/incubate/checkpoint/__init__.py

@@ -12,6 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from ...fluid.incubate.checkpoint import auto_checkpoint
+from ...fluid.incubate.checkpoint import auto_checkpoint  # noqa: F401
 
-__all__ = ["auto_checkpoint"]
+__all__ = []

python/paddle/incubate/optimizer/__init__.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .lookahead import LookAhead
-from .modelaverage import ModelAverage
+from .lookahead import LookAhead  # noqa: F401
+from .modelaverage import ModelAverage  # noqa: F401
 
-__all__ = ['LookAhead', 'ModelAverage']
+__all__ = []