reverse device.py all list;

fix some flake8 errors

Author: zhiboniu

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
@@ -280,7 +277,7 @@
 from .tensor.random import check_shape  # noqa: F401
 disable_static()
 
-__all__ = [     #noqa
+__all__ = [  # noqa
            'dtype',
            'uint8',
            'int8',
@@ -322,7 +319,6 @@
            'cos',
            'tan',
            'mean',
-           'XPUPlace',
            'mv',
            'in_dynamic_mode',
            'min',
@@ -359,7 +355,6 @@
            'to_tensor',
            'gather_nd',
            'isinf',
-           'set_device',
            'uniform',
            'floor_divide',
            'remainder',
@@ -383,8 +378,6 @@
            'rand',
            'less_equal',
            'triu',
-           'is_compiled_with_cuda',
-           'is_compiled_with_rocm',
            'sin',
            'dist',
            'unbind',
@@ -413,8 +406,6 @@
            'bernoulli',
            'summary',
            'sinh',
-           'is_compiled_with_xpu',
-           'is_compiled_with_npu',
            'round',
            'DataParallel',
            'argmin',
@@ -436,7 +427,6 @@
            'not_equal',
            'sum',
            'tile',
-           'get_device',
            'greater_equal',
            'isfinite',
            'create_parameter',
@@ -469,7 +459,6 @@
            'scatter_nd',
            'set_default_dtype',
            'expand_as',
-           'get_cudnn_version',
            'stack',
            'sqrt',
            'cholesky',

python/paddle/batch.py

@@ -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

@@ -19,7 +19,7 @@
 
 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

@@ -21,7 +21,17 @@
 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',
+    'is_compiled_with_cuda',
+    'is_compiled_with_rocm',
+    'is_compiled_with_npu'
+]
 
 _cudnn_version = None
 
@@ -113,15 +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)
@@ -135,7 +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]
@@ -144,7 +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

@@ -150,7 +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/optimizer/lookahead.py

@@ -282,9 +282,6 @@ def minimize(self,
         """
         assert isinstance(loss, Variable), "The loss should be an Tensor."
 
-        parameter_list = parameters if parameters \
-            else self._parameter_list
-
         # Apply inner optimizer to the main_program
         optimize_ops, params_grads = self.inner_optimizer.minimize(
             loss,

python/paddle/incubate/optimizer/modelaverage.py

@@ -415,7 +415,6 @@ def apply(self, executor=None, need_restore=True):
                                                         param)
                 old_num_accumulates = self._get_accumulator(
                     'old_num_accumulates', param)
-                num_updates = self._get_accumulator('num_updates', param)
                 sum_1 = self._get_accumulator('sum_1', param)
                 sum_2 = self._get_accumulator('sum_2', param)
                 sum_3 = self._get_accumulator('sum_3', param)
@@ -506,17 +505,15 @@ def _add_average_apply_op(self, block, param):
             self._get_accumulator('num_accumulates', param))
         old_num_accumulates = block._clone_variable(
             self._get_accumulator('old_num_accumulates', param))
-        num_updates = block._clone_variable(
-            self._get_accumulator('num_updates', param))
         # backup param value to grad
         layers.assign(input=param, output=grad)
         # param = (sum_1 + sum_2 + sum_3) / (num_accumulates + old_num_accumulates)
         tmp = layers.sum(x=[num_accumulates, old_num_accumulates])
         sum = layers.sum(x=[sum_1, sum_2, sum_3])
         tmp = layers.cast(
-            x=tmp, dtype='float32' if self._dtype == None else self._dtype)
+            x=tmp, dtype='float32' if self._dtype is None else self._dtype)
         sum = layers.cast(
-            x=sum, dtype='float32' if self._dtype == None else self._dtype)
+            x=sum, dtype='float32' if self._dtype is None else self._dtype)
         layers.ops._elementwise_div(x=sum, y=tmp, out=param)
 
     def _add_average_restore_op(self, block, param):

python/paddle/tensor/__init__.py

@@ -25,7 +25,6 @@
 from .creation import zeros  # noqa: F401
 from .creation import zeros_like  # noqa: F401
 from .creation import arange  # noqa: F401
-from .creation import eye  # noqa: F401
 from .creation import full  # noqa: F401
 from .creation import full_like  # noqa: F401
 from .creation import triu  # noqa: F401
@@ -82,7 +81,6 @@
 from .manipulation import squeeze_  # noqa: F401
 from .manipulation import stack  # noqa: F401
 from .manipulation import strided_slice  # noqa: F401
-from .manipulation import transpose  # noqa: F401
 from .manipulation import unique  # noqa: F401
 from .manipulation import unsqueeze  # noqa: F401
 from .manipulation import unsqueeze_  # noqa: F401
@@ -143,7 +141,6 @@
 from .math import add_  # noqa: F401
 from .math import subtract  # noqa: F401
 from .math import subtract_  # noqa: F401
-from .math import atan  # noqa: F401
 from .math import logsumexp  # noqa: F401
 from .math import inverse  # noqa: F401
 from .math import log2  # noqa: F401