fix pylint

This commit is contained in:
panyifeng 2020-05-14 11:32:12 +08:00
parent 4bb5c7b39a
commit 755ba75deb
24 changed files with 66 additions and 91 deletions

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@ -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

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@ -6,4 +6,3 @@
"""
from .ad_test import *

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@ -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)
@ -117,20 +117,17 @@ def test_if(a, b):
# if statement, so I prefer to name the test 'test_if'
if a > b:
return a
else:
return b
def test_if2(a, b):
if a > b:
return a * a
else:
return b + b
def test_fact(x):
def fact(n):
if n <= 1:
return 1
else:
return n * fact(n - 1)
return fact(x)

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@ -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)

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@ -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

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@ -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):
@ -63,7 +63,7 @@ conv2d = P.Conv2D(64,
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

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@ -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"]

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@ -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

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@ -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

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@ -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

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@ -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)

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@ -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)

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@ -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'

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@ -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)

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@ -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

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@ -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))

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@ -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
@ -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)

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@ -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

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@ -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)

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@ -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()

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@ -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") == "."

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@ -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
@ -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):