[CodeStyle][task 35-37] enable Flake8 E712, E266, E714 rule in `pytho…

…n/paddle/base` (#58319)

* [CodeStyle] fix E712

* [CodeStyle] fix E266

* [CodeStyle] fix E714

.flake8

@@ -28,9 +28,3 @@ per-file-ignores =
 
     # Ignore compare with True in sot unittest
     test/sot/test_dup_top.py:E712
-
-    # temp ignore base directory
-    python/paddle/base/*:
-        E712,
-        E266,
-        E714

python/paddle/base/backward.py

@@ -2348,7 +2348,7 @@ def _find_op_path_(
         # If block is while block, dealing with op specifically again.
         # TODO(liym27): Consider special types of ops.
         for i, op in reversed(list(enumerate(block.ops))):
-            if relevant_op_flags[i] == False and _some_in_set_(
+            if relevant_op_flags[i] is False and _some_in_set_(
                 op.desc.output_arg_names(), output_names
             ):
                 relevant_op_flags[i] = True

python/paddle/base/device_worker.py

@@ -450,7 +450,7 @@ def _gen_worker_desc(self, trainer_desc):
             if (
                 opt_info["use_cvm"]
                 or "no_cvm" in opt_info
-                and opt_info["no_cvm"] == True
+                and opt_info["no_cvm"] is True
             ):
                 sparse_table.emb_dim = self._fleet_desc.server_param.downpour_server_param.downpour_table_param[
                     i
@@ -560,7 +560,7 @@ def _gen_worker_desc(self, trainer_desc):
             if (
                 opt_info["use_cvm"]
                 or "no_cvm" in opt_info
-                and opt_info["no_cvm"] == True
+                and opt_info["no_cvm"] is True
             ):
                 sparse_table.emb_dim = self._fleet_desc.server_param.downpour_server_param.downpour_table_param[
                     i

python/paddle/base/dygraph/base.py

@@ -928,7 +928,7 @@ def to_variable(value, name=None, zero_copy=None, dtype=None):
             # (2): when used in flask framework, it may result in hang.
             # Details: https://github.com/PaddlePaddle/Paddle/issues/26635
             # So, we temporally diable the zero_copy strategy.
-            if zero_copy == True:
+            if zero_copy is True:
                 warnings.warn(
                     "Currently, zero_copy is not supported, and it will be discarded."
                 )

python/paddle/base/executor.py

@@ -1711,7 +1711,7 @@ def _run_impl(
         if isinstance(program, Program) and program._heter_pipeline_opt:
             # print("program._heter_pipeline_opt: {}".format(
             #    program._heter_pipeline_opt))
-            ## change default executor
+            # change default executor
             heter_place = program._heter_pipeline_opt["heter_place"]
             heter_place = framework._get_paddle_place(heter_place)
             p = core.Place()
@@ -1868,12 +1868,12 @@ def _run_impl(
                 varobj = global_block.vars[varname]
 
                 if (
-                    vardesc.persistable() == False
+                    vardesc.persistable() is False
                     and vardesc.type() == core.VarDesc.VarType.LOD_TENSOR
-                    and vardesc.need_check_feed() == True
-                    and varobj.stop_gradient == True
-                    and varobj.is_data == True
-                    and varobj.belong_to_optimizer == False
+                    and vardesc.need_check_feed() is True
+                    and varobj.stop_gradient is True
+                    and varobj.is_data is True
+                    and varobj.belong_to_optimizer is False
                     and varname not in feed
                 ):
                     raise ValueError('Need feed data for variable %s' % varname)
@@ -2161,7 +2161,7 @@ def _prepare_trainer(
     ):
         is_heter = 0
         use_ps_gpu = 0
-        if not program._fleet_opt is None:
+        if program._fleet_opt is not None:
             if program._fleet_opt.get("worker_class", "") == "HeterCpuWorker":
                 is_heter = 1
             if program._fleet_opt.get("trainer", "") == "HeterXpuTrainer":
@@ -2287,7 +2287,7 @@ def _run_from_dataset(
                     raise RuntimeError(
                         "dataset is need and should be initialized"
                     )
-            ## change default executor
+            # change default executor
             heter_place = framework._get_paddle_place(heter_place)
             p = core.Place()
             p.set_place(heter_place)

python/paddle/base/framework.py

@@ -2993,7 +2993,7 @@ def __init__(
                     if (
                         type == 'less_than'
                         and op_attrs['force_cpu'] is not None
-                    ) or op_attrs['force_cpu'] != False:
+                    ) or op_attrs['force_cpu'] is not False:
                         warnings.warn(
                             "The Attr(force_cpu) of Op(%s) will be deprecated in the future, "
                             "please use 'device_guard' instead. 'device_guard' has higher priority when they are "
@@ -4264,7 +4264,7 @@ def _rename_var(self, name, new_name):
         return var
 
     def _remove_var(self, name, sync=True):
-        if sync == True:
+        if sync is True:
             self._sync_with_cpp()
         self.desc._remove_var(name.encode())
         del self.vars[name]
@@ -4453,7 +4453,7 @@ def _remove_op(self, index, sync=True):
         Returns:
             None
         """
-        if sync == True:
+        if sync is True:
             self._sync_with_cpp()
         self.desc._remove_op(index, index + 1)
         del self.ops[index]

python/paddle/base/trainer_desc.py

@@ -112,7 +112,7 @@ def _set_infer(self, infer):
 
     def _set_fleet_desc(self, fleet_desc):
         self._fleet_desc = fleet_desc
-        ## serialize fleet_desc
+        # serialize fleet_desc
         from google.protobuf import text_format
 
         fleet_desc_str = text_format.MessageToString(fleet_desc)

python/paddle/base/trainer_factory.py

@@ -186,7 +186,7 @@ def handler_launch_func(self, scope, handler):
         elapsed_secs = 0
         while True:
             self.running_lock.acquire()
-            if self.running == False:
+            if self.running is False:
                 break
             if elapsed_secs < period_secs:
                 # TODO(guru4elephant): needs customized condition