!1149 fix pylint in tests

Merge pull request !1149 from panyifeng/fix_pylint

tests/ut/cpp/python_input/gtest_input/ir/manager_test.py

@@ -44,7 +44,7 @@ def test_calls(x):
 # pylint: disable=unused-argument
 def test_unused_param(x, y):
     return x * x
-    
+
 
 def test_cannot_replace_return(x):
     return x * x

tests/ut/cpp/python_input/gtest_input/mem_reuse/mem_reuse_test.py

@@ -13,8 +13,6 @@
 # limitations under the License.
 # ============================================================================
 from mindspore.ops import operations as P
-from mindspore.ops import Primitive
-import mindspore as ms
 
 add = P.TensorAdd()
 reshape = P.Reshape()
@@ -26,6 +24,6 @@ def test_shape_add(x1, x2, y1, y2, z1, z2):
     reshape_sum1 = reshape(sum1, (2, 2, 3, 1))
     reshape_sum2 = reshape(sum2, (2, 2, 3, 1))
     reshape_sum3 = reshape(sum3, (2, 2, 3, 1))
-    sum = add(reshape_sum1, reshape_sum2)
-    sum = add(sum, reshape_sum3)
-    return sum
+    result = add(reshape_sum1, reshape_sum2)
+    result = add(result, reshape_sum3)
+    return result

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

@@ -1,9 +1,8 @@
 """
 @File  : __init__.py
 @Author:
-@Date  : 2019-01-23 16:36 
-@Desc  : 
+@Date  : 2019-01-23 16:36
+@Desc  :
 """
 
 from .ad_test import *
-

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

@@ -12,10 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
+from dataclasses import dataclass
 import numpy as np
 
 import mindspore as ms
-from dataclasses import dataclass
 from mindspore.common.tensor import Tensor
 from mindspore.ops import Primitive
 from mindspore.model_zoo.resnet import resnet50
@@ -106,7 +106,7 @@ def test_closure(a):
     def x1(b):
 
         def x4(c):
-            return b
+            return c * b
         return x4
     x2 = x1(a)
     x3 = x2(1.0)
@@ -117,21 +117,18 @@ def test_if(a, b):
     # if statement, so I prefer to name the test 'test_if'
     if a > b:
         return a
-    else:
-        return b
+    return b
 
 def test_if2(a, b):
     if a > b:
         return a * a
-    else:
-        return b + b
+    return b + b
 
 def test_fact(x):
     def fact(n):
         if n <= 1:
             return 1
-        else:
-            return n * fact(n - 1)
+        return n * fact(n - 1)
     return fact(x)
 
 def test_while(x):

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

@@ -13,11 +13,11 @@
 # limitations under the License.
 # ============================================================================
 """ opt_test """
+import numpy as np
 from mindspore.ops import Primitive, PrimitiveWithInfer
 from mindspore.ops import operations as P
 from mindspore.ops.operations import _grad_ops as G
 from mindspore import Tensor
-import numpy as np
 
 # pylint: disable=unused-variable
 
@@ -790,9 +790,9 @@ def test_convert_switch_ops(tag):
         return z
     @fns
     def after(cond, x, y):
-        sw1 =ge_switch(x, cond)
-        sw2 =ge_switch(y, cond)
-        sw3 =ge_switch(y, cond)
+        sw1 = ge_switch(x, cond)
+        sw2 = ge_switch(y, cond)
+        sw3 = ge_switch(y, cond)
         sw1_t = tuple_getitem(sw1, 1)
         sw2_t = tuple_getitem(sw2, 1)
         sw3_f = tuple_getitem(sw3, 0)

tests/ut/cpp/python_input/gtest_input/pipeline/infer/__init__.py

@@ -13,4 +13,4 @@
 # limitations under the License.
 # ============================================================================
 from .primitive_test import *
-from .infer_test import *
+from .infer_test import *

tests/ut/cpp/python_input/gtest_input/pipeline/infer/infer_test.py

@@ -12,8 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
-import mindspore.nn as nn
 from dataclasses import dataclass
+import mindspore.nn as nn
 from mindspore.ops import Primitive
 from mindspore.ops import functional as F
 from mindspore.ops import operations as P

tests/ut/cpp/python_input/gtest_input/pipeline/infer/primitive_test.py

@@ -14,7 +14,7 @@
 # ============================================================================
 import mindspore.nn as nn
 from mindspore.common import dtype
-from mindspore.ops import Primitive, prim_attr_register, PrimitiveWithInfer
+from mindspore.ops import prim_attr_register, PrimitiveWithInfer
 from mindspore.ops import operations as P
 
 def get_add(a, b):
@@ -55,15 +55,15 @@ def get_tensor_to_scalar(logits, labels):
 
 
 conv2d = P.Conv2D(64,
-                (3, 3),
-                pad_mode="pad",
-                pad=1,
-                stride=2)
+                  (3, 3),
+                  pad_mode="pad",
+                  pad=1,
+                  stride=2)
 
 def get_conv2d(x, w):
     return conv2d(x, w)
 
-conv2dNative = P.DepthwiseConv2dNative(3, (3,3), pad_mode="pad", pad=1, stride=2)
+conv2dNative = P.DepthwiseConv2dNative(3, (3, 3), pad_mode="pad", pad=1, stride=2)
 
 def get_conv2d_native(x, w):
     return conv2dNative(x, w)
@@ -74,8 +74,8 @@ def get_bias_add(x, b):
 
 
 def test_conv2d(out_channel, kernel_size, pad, stride, dilation):
-    conv = P.Conv2D(out_channel=out_channel, kernel_size=kernel_size, pad_mode= "pad", pad=pad,
-                  stride=stride, dilation= dilation)
+    conv = P.Conv2D(out_channel=out_channel, kernel_size=kernel_size, pad_mode="pad", pad=pad,
+                    stride=stride, dilation=dilation)
     def get_conv(x, w):
         return conv(x, w)
     return get_conv
@@ -83,7 +83,7 @@ def test_conv2d(out_channel, kernel_size, pad, stride, dilation):
 
 def test_dropout():
     dropOutGenMask = P.DropoutGenMask()
-    dropoutDoMask  = P.DropoutDoMask()
+    dropoutDoMask = P.DropoutDoMask()
     shape = P.Shape()
     def get_dropout(x, prob):
         mask = dropOutGenMask(shape(x), prob)

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

@@ -154,12 +154,12 @@ def test_lambda(x, y):
     return t
 
 def test_funcdef(x, y):
-    def max(a, b):
+    def mymax(a, b):
         if a > b:
             return a
         else:
             return b
-    t = max(x, y)
+    t = mymax(x, y)
     return t
 
 def test_tuple_fn(x, y):
@@ -225,7 +225,7 @@ def test_simple_closure(a, b):
         return b + 2.0
     return f() * g()
 
-def test_assign_tuple(x,y):
+def test_assign_tuple(x, y):
     a = 1
     b = 2
     t = a, b
@@ -282,8 +282,8 @@ def test_subscript_setitem():
     return t
 
 def test_dict():
-    dict = {"a": 1, "b": 2}
-    return dict
+    ret = {"a": 1, "b": 2}
+    return ret
 
 def func_call(x, y, *var, a=0, b=1, **kwargs):
     return x + y + var[0] + a + b + kwargs["z"]

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

@@ -25,13 +25,13 @@ tuple_getitem = Primitive('tuple_getitem')
 max_pool = P.MaxPoolWithArgmax(padding="same", ksize=3, strides=2)
 
 def test_addn_cast(x, y, z):
-    sum = addn((x, y))
-    res = cast(sum, ms.float16)
+    mysum = addn((x, y))
+    res = cast(mysum, ms.float16)
     return res
 
 def test_addn_with_max_pool(x, y):
-    sum = addn((x, y))
-    output = max_pool(sum)
+    mysum = addn((x, y))
+    output = max_pool(mysum)
     res = tuple_getitem(output, 0)
     return res
 
@@ -43,6 +43,6 @@ def test_shape_add(x1, x2, y1, y2, z1, z2):
     reshape_sum1 = reshape(sum1, (2, 2, 3, 1))
     reshape_sum2 = reshape(sum2, (2, 2, 3, 1))
     reshape_sum3 = reshape(sum3, (2, 2, 3, 1))
-    sum = add(reshape_sum1, reshape_sum2)
-    sum = add(sum, reshape_sum3)
-    return sum
+    mysum = add(reshape_sum1, reshape_sum2)
+    mysum = add(mysum, reshape_sum3)
+    return mysum

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

@@ -12,9 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
-from mindspore.common.api import ms_function
 import numpy as np
 from mindspore import Tensor
+from mindspore.common.api import ms_function
 from mindspore.ops import operations as P
 
 

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

@@ -13,7 +13,6 @@
 # limitations under the License.
 # ============================================================================
 """ test_dtype """
-import pytest
 from mindspore._c_expression import typing
 from mindspore.common.api import ms_function
 

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

@@ -19,8 +19,6 @@ import mindspore.nn as nn
 from mindspore import context
 import mindspore.common.dtype as mstype
 from mindspore.common.tensor import Tensor
-from mindspore.common.parameter import Parameter
-from mindspore.common.api import ms_function
 context.set_context(mode=context.GRAPH_MODE)
 
 

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

@@ -200,6 +200,3 @@ def test_in_dict():
     z = Tensor(np.random.randint(low=20, high=30, size=(2, 3, 4), dtype=np.int32))
     context.set_context(mode=context.GRAPH_MODE)
     net(x, y, z)
-
-
-

tests/ut/python/pynative_mode/ge/ops/test_tensor_add.py

@@ -38,5 +38,5 @@ def test_tensor_orign_ops():
     assert np.all(z.asnumpy() - (x.asnumpy() + y.asnumpy()) < 0.0001)
     z = x * y
     assert np.all(z.asnumpy() - (x.asnumpy() * y.asnumpy()) < 0.0001)
-    assert (x == y)
-    assert (x != 'zero')
+    assert x == y
+    assert x != 'zero'

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

@@ -297,4 +297,3 @@ def test_net_call():
         input_x = Tensor(
             np.random.randint(0, 255, [1, 3, net.image_h, net.image_w]).astype(np.float32))
         output = net.construct(input_x)
-

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

@@ -14,7 +14,6 @@
 # ============================================================================
 """ test_dropout """
 import numpy as np
-import pytest
 from mindspore.common.api import _executor
 import mindspore.nn as nn
 from mindspore import Tensor

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

@@ -57,6 +57,3 @@ def test_maxpool2d():
     output = max_pool(input_data)
     output_np = output.asnumpy()
     assert isinstance(output_np[0][0][0][0], (np.float32, np.float64))
-
-
-

tests/ut/python/pynative_mode/ops/test_grad.py

@@ -20,7 +20,6 @@ from mindspore import Tensor
 from mindspore.ops import composite as C
 from mindspore.ops.composite import grad_all_with_sens
 from mindspore.common.dtype import get_py_obj_dtype
-import mindspore.nn as nn
 import mindspore.ops.operations as P
 from mindspore.ops import functional as F
 from ...ut_filter import non_graph_engine
@@ -174,7 +173,7 @@ def test_select_grad():
     assert np.all(gout[0].asnumpy() == expect_cond)
     assert np.all(gout[1].asnumpy() == expect_x)
     assert np.all(gout[2].asnumpy() == expect_y)
-    
+
 
 def test_SubGrad():
     """ test_SubGrad """
@@ -201,10 +200,10 @@ def test_MulGrad():
     """ test_MulGrad """
     input_x = Tensor(np.array([[2, 2], [2, 2]], np.float32))
     input_y = Tensor(np.array([[3, 3], [3, 3]], np.float32))
-    mul = P.Mul()
+    mymul = P.Mul()
 
     def fn(x, y):
-        output = mul(x, y)
+        output = mymul(x, y)
         return output
 
     out = fn(input_x, input_y)

tests/ut/python/pynative_mode/ops/test_hypermap.py

@@ -17,7 +17,6 @@ import numpy as np
 
 from mindspore.common.api import ms_function
 from mindspore import Tensor
-from mindspore import context
 from mindspore.ops import Primitive
 from mindspore.ops import composite as C
 from mindspore.ops import operations as P

tests/ut/python/pynative_mode/test_bprop.py

@@ -19,8 +19,8 @@ from mindspore import context
 from mindspore.ops import operations as P
 from mindspore.common.parameter import Parameter
 from mindspore.common import Tensor
-from ....mindspore_test_framework.utils.bprop_util import bprop
 from mindspore.common.api import ms_function
+from ....mindspore_test_framework.utils.bprop_util import bprop
 
 def setup_module(module):
     context.set_context(mode=context.PYNATIVE_MODE)

tests/ut/python/pynative_mode/test_cell_bprop.py

@@ -88,7 +88,7 @@ class WithNoBprop(nn.Cell):
 
 def test_with_no_bprop():
     with_no_bprop = WithNoBprop()
-    C.grad_all(with_no_bprop)(1, 2) == (2, 1)
+    assert C.grad_all(with_no_bprop)(1, 2) == (2, 1)
 
 def test_grad_in_bprop_1():
     class GradInBprop_1(nn.Cell):
@@ -189,8 +189,8 @@ class OneInputBprop(nn.Cell):
 
 def test_grad_one_input_bprop():
     net = OneInputBprop()
-    input = Tensor(np.ones([2, 2]).astype(np.float32))
-    grad = C.grad_all(net)(input)
+    input1 = Tensor(np.ones([2, 2]).astype(np.float32))
+    grad = C.grad_all(net)(input1)
     assert (grad[0].asnumpy() == np.array([5, 5]).astype(np.float32)).all()
 
 

tests/ut/python/pynative_mode/test_context.py

@@ -68,9 +68,9 @@ def test_dump_target():
     with pytest.raises(TypeError):
         context.set_context(save_dump_path=1)
     context.set_context(enable_dump=False)
-    assert context.get_context("enable_dump") == False
+    assert not context.get_context("enable_dump")
     context.set_context(enable_dump=True)
-    assert context.get_context("enable_dump") == True
+    assert context.get_context("enable_dump")
     assert context.get_context("save_dump_path") == "."
 
 

tests/ut/python/pynative_mode/test_framstruct.py

@@ -15,23 +15,17 @@
 """ test_framstruct """
 import pytest
 import numpy as np
-import mindspore as ms
 import mindspore.nn as nn
 from mindspore import context
 from mindspore.ops import composite as C
 from mindspore.ops import operations as P
 from mindspore.common.tensor import Tensor
 from mindspore.common.parameter import Parameter, ParameterTuple
-from mindspore.common.initializer import initializer
 from mindspore.common import dtype as mstype
-import mindspore.nn as nn
-from mindspore.nn.wrap.cell_wrapper import WithGradCell, WithLossCell
 from ..ut_filter import non_graph_engine
 from ....mindspore_test_framework.utils.check_gradient import (
     ms_function, check_jacobian, Tensor, NNGradChecker,
     OperationGradChecker, check_gradient, ScalarGradChecker)
-from ....mindspore_test_framework.utils.bprop_util import bprop
-import mindspore.context as context
 from mindspore.ops._grad.grad_base import bprop_getters
 from mindspore.ops.primitive import prim_attr_register, PrimitiveWithInfer
 
@@ -299,22 +293,22 @@ def test_dont_unroll_while():
     assert res == 3
 
 class ConvNet(nn.Cell):
-  def __init__(self):
-    super(ConvNet, self).__init__()
-    out_channel = 16
-    kernel_size = 3
-    self.conv = P.Conv2D(out_channel,
-                 kernel_size,
-                 mode=1,
-                 pad_mode="pad",
-                 pad=0,
-                 stride=1,
-                 dilation=2,
-                 group=1)
-    self.w = Parameter(Tensor(np.ones([16, 16, 3, 3]).astype(np.float32)), name='w')
+    def __init__(self):
+        super(ConvNet, self).__init__()
+        out_channel = 16
+        kernel_size = 3
+        self.conv = P.Conv2D(out_channel,
+                    kernel_size,
+                    mode=1,
+                    pad_mode="pad",
+                    pad=0,
+                    stride=1,
+                    dilation=2,
+                    group=1)
+        self.w = Parameter(Tensor(np.ones([16, 16, 3, 3]).astype(np.float32)), name='w')
 
-  def construct(self, x):
-    return self.conv(x, self.w)
+    def construct(self, x):
+        return self.conv(x, self.w)
 
 conv = ConvNet()
 c1 = Tensor([2], mstype.float32)
@@ -674,7 +668,7 @@ def grad_refactor_6(a, b):
 
 
 def test_grad_refactor_6():
-    C.grad_all(grad_refactor_6)(3, 2) == (3, 1)
+    assert C.grad_all(grad_refactor_6)(3, 2) == (3, 1)
 
 
 def grad_refactor_while(x):