Fix pylint warning for test cases of optimizer, infer, parse and

pynative.

tests/ut/cpp/python_input/gtest_input/optimizer/ad/ad_test.py

@@ -12,8 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
-import numpy as np
 from dataclasses import dataclass
+import numpy as np
 
 import mindspore as ms
 from mindspore.common.tensor import Tensor

tests/ut/cpp/python_input/gtest_input/optimizer/opt_test.py

@@ -16,7 +16,7 @@
 import numpy as np
 
 from mindspore import Tensor
-from mindspore.ops import Primitive, PrimitiveWithInfer
+from mindspore.ops import Primitive
 from mindspore.ops import operations as P
 from mindspore.ops.operations import _grad_ops as G
 

tests/ut/cpp/python_input/gtest_input/pipeline/parse/parser_integrate.py

@@ -136,8 +136,8 @@ class Net(nn.Cell):
         super(Net, self).__init__()
         self.conv = nn.Conv2d(3, 64, 3, bias_init='zeros')
 
-    def construct(self, input):
+    def construct(self, inputs):
-        return self.conv(input)
+        return self.conv(inputs)
 
 
 class TestNet(nn.Cell):

tests/ut/cpp/python_input/gtest_input/session/session_test.py

@@ -25,7 +25,7 @@ max_pool = P.MaxPoolWithArgmax(padding="same", ksize=3, strides=2)
 
 
 def test_addn_cast(x, y, z):
-    mysum = addn((x, y))
+    mysum = addn((x, y, z))
     res = cast(mysum, ms.float16)
     return res
 

tests/ut/python/pipeline/infer/infer.py

@@ -13,8 +13,8 @@
 # limitations under the License.
 # ============================================================================
 """ infer """
-import numpy as np
 from argparse import ArgumentParser
+import numpy as np
 
 from mindspore import Tensor
 from ....dataset_mock import MindData

tests/ut/python/pipeline/infer/test_hypermap_specialize.py

@@ -53,4 +53,4 @@ def test_hypermap_specialize_param():
 
     expected_ret = (Tensor(np.full(1, 5).astype(np.int32)), Tensor(np.full(2, 5).astype(np.int32)))
     ret = hypermap_specialize_param()
-    assert (ret == (expected_ret, expected_ret))
+    assert ret == (expected_ret, expected_ret)

tests/ut/python/pipeline/parse/test_for_stmt.py

@@ -13,8 +13,8 @@
 # limitations under the License.
 # ============================================================================
 """ test_for_stmt """
-import numpy as np
 from dataclasses import dataclass
+import numpy as np
 
 from mindspore import Tensor, Model, context
 from mindspore.nn import Cell

tests/ut/python/pipeline/parse/test_operator.py

@@ -163,7 +163,7 @@ def test_ops():
             ret_floor = p // q + q // p
             ret = ret_pow + ret_mod + ret_floor
             if self.int > self.float:
-                if [1, 2, 3] != None:
+                if [1, 2, 3] is not None:
                     if self.str_a + self.str_b == "helloworld":
                         if q == 86:
                             print("hello world")

tests/ut/python/pipeline/parse/test_parse.py

@@ -25,7 +25,6 @@ import mindspore as ms
 import mindspore.nn as nn
 from mindspore import Tensor
 from mindspore.common.api import ms_function, _executor
-from mindspore.ops.composite import core
 from mindspore.ops.functional import tensor_add
 from ...ut_filter import non_graph_engine
 

tests/ut/python/pynative_mode/nn/test_activation.py

@@ -14,7 +14,6 @@
 # ============================================================================
 """ test Activations """
 import numpy as np
-import pytest
 
 import mindspore.nn as nn
 from mindspore import Tensor

tests/ut/python/pynative_mode/nn/test_cell.py

@@ -305,4 +305,4 @@ def test_net_call():
         net = ConvNet()
         input_x = Tensor(
             np.random.randint(0, 255, [1, 3, net.image_h, net.image_w]).astype(np.float32))
-        output = net.construct(input_x)
+        net.construct(input_x)

tests/ut/python/pynative_mode/nn/test_container.py

@@ -13,9 +13,9 @@
 # limitations under the License.
 # ============================================================================
 """ test_container """
+from collections import OrderedDict
 import numpy as np
 import pytest
-from collections import OrderedDict
 
 import mindspore.nn as nn
 from mindspore import Tensor