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new d599bc3 [MXNET-1411] solve pylint error issue#14851 (#15113)
d599bc3 is described below
commit d599bc3c1356b3471d27026711f67467122992f9
Author: Neo Chien <[email protected]>
AuthorDate: Sun Jul 21 16:07:39 2019 +0800
[MXNET-1411] solve pylint error issue#14851 (#15113)
* fix pylint error: no-else-raise in _export_helper.py
* fix pylint error: no-else-raise in _translation_utils.py
* fix pylint error: Bad option value 'no-else-raise' (bad-option-value) in
vocab.py
* fix pylint error: Bad option value 'no-else-raise' (bad-option-value) in
trainer.py
* fix pylint error: Bad option value 'no-else-raise' (bad-option-value) in
utils.py
* fix pylint error: Bad option value 'no-else-raise' (bad-option-value) in
detection.py
* fix pylint error: Bad option value 'no-else-raise' (bad-option-value) in
image.py
* fix pylint error: Bad option value 'no-else-raise' (bad-option-value) in
model.py
* fix pylint error: Bad option value 'no-else-raise' (bad-option-value) in
sparse.py
* fix pylint error: Bad option value 'no-else-raise' (bad-option-value) in
test_utils.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
vocab.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
model.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
_translation_utils.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
_export_helper.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
test_utils.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
image.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
trainer.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
detection.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
utils.py
* fix pylint error: R1720: Unnecessary else after raise (no-else-raise) for
sparse.py
* fix pylint error:R1719: The if expression can be replaced with
'bool(test)' (simplifiable-if-expression)
---
.../mxnet/contrib/onnx/mx2onnx/_export_helper.py | 38 +++++++++++-----------
.../contrib/onnx/onnx2mx/_translation_utils.py | 30 ++++++++---------
python/mxnet/contrib/text/vocab.py | 5 ++-
python/mxnet/gluon/trainer.py | 12 +++----
python/mxnet/gluon/utils.py | 8 ++---
python/mxnet/image/detection.py | 18 +++++-----
python/mxnet/image/image.py | 24 +++++++-------
python/mxnet/model.py | 5 ++-
python/mxnet/ndarray/sparse.py | 10 +++---
python/mxnet/test_utils.py | 28 ++++++++--------
10 files changed, 88 insertions(+), 90 deletions(-)
diff --git a/python/mxnet/contrib/onnx/mx2onnx/_export_helper.py
b/python/mxnet/contrib/onnx/mx2onnx/_export_helper.py
index e73ff70..fdb6689 100644
--- a/python/mxnet/contrib/onnx/mx2onnx/_export_helper.py
+++ b/python/mxnet/contrib/onnx/mx2onnx/_export_helper.py
@@ -40,26 +40,26 @@ def load_module(sym_filepath, params_filepath):
params : params object
Model weights including both arg and aux params.
"""
- if not (os.path.isfile(sym_filepath) and os.path.isfile(params_filepath)):
# pylint: disable=no-else-raise
+ if not (os.path.isfile(sym_filepath) and os.path.isfile(params_filepath)):
raise ValueError("Symbol and params files provided are invalid")
- else:
- try:
- # reads symbol.json file from given path and
- # retrieves model prefix and number of epochs
- model_name = sym_filepath.rsplit('.', 1)[0].rsplit('-', 1)[0]
- params_file_list = params_filepath.rsplit('.', 1)[0].rsplit('-', 1)
- # Setting num_epochs to 0 if not present in filename
- num_epochs = 0 if len(params_file_list) == 1 else
int(params_file_list[1])
- except IndexError:
- logging.info("Model and params name should be in format: "
- "prefix-symbol.json, prefix-epoch.params")
- raise
- sym, arg_params, aux_params = mx.model.load_checkpoint(model_name,
num_epochs)
+ try:
+ # reads symbol.json file from given path and
+ # retrieves model prefix and number of epochs
+ model_name = sym_filepath.rsplit('.', 1)[0].rsplit('-', 1)[0]
+ params_file_list = params_filepath.rsplit('.', 1)[0].rsplit('-', 1)
+ # Setting num_epochs to 0 if not present in filename
+ num_epochs = 0 if len(params_file_list) == 1 else
int(params_file_list[1])
+ except IndexError:
+ logging.info("Model and params name should be in format: "
+ "prefix-symbol.json, prefix-epoch.params")
+ raise
- # Merging arg and aux parameters
- params = {}
- params.update(arg_params)
- params.update(aux_params)
+ sym, arg_params, aux_params = mx.model.load_checkpoint(model_name,
num_epochs)
- return sym, params
+ # Merging arg and aux parameters
+ params = {}
+ params.update(arg_params)
+ params.update(aux_params)
+
+ return sym, params
diff --git a/python/mxnet/contrib/onnx/onnx2mx/_translation_utils.py
b/python/mxnet/contrib/onnx/onnx2mx/_translation_utils.py
index 48ede28..0160c5c 100644
--- a/python/mxnet/contrib/onnx/onnx2mx/_translation_utils.py
+++ b/python/mxnet/contrib/onnx/onnx2mx/_translation_utils.py
@@ -178,23 +178,23 @@ def _fix_channels(op_name, attrs, inputs, proto_obj):
these attributes. We check the shape of weights provided to get the number.
"""
weight_name = inputs[1].name
- if not weight_name in proto_obj._params: # pylint: disable=no-else-raise
+ if not weight_name in proto_obj._params:
raise ValueError("Unable to get channels/units attr from onnx graph.")
- else:
- wshape = proto_obj._params[weight_name].shape
- assert len(wshape) >= 2, "Weights shape is invalid: {}".format(wshape)
- if op_name == 'FullyConnected':
- attrs['num_hidden'] = wshape[0]
- else:
- if op_name == 'Convolution':
- # Weight shape for Conv and FC: (M x C x kH x kW) : M is
number of
- # feature maps/hidden and C is number of channels
- attrs['num_filter'] = wshape[0]
- elif op_name == 'Deconvolution':
- # Weight shape for DeConv : (C x M x kH x kW) : M is number of
- # feature maps/filters and C is number of channels
- attrs['num_filter'] = wshape[1]
+ wshape = proto_obj._params[weight_name].shape
+ assert len(wshape) >= 2, "Weights shape is invalid: {}".format(wshape)
+
+ if op_name == 'FullyConnected':
+ attrs['num_hidden'] = wshape[0]
+ else:
+ if op_name == 'Convolution':
+ # Weight shape for Conv and FC: (M x C x kH x kW) : M is number of
+ # feature maps/hidden and C is number of channels
+ attrs['num_filter'] = wshape[0]
+ elif op_name == 'Deconvolution':
+ # Weight shape for DeConv : (C x M x kH x kW) : M is number of
+ # feature maps/filters and C is number of channels
+ attrs['num_filter'] = wshape[1]
return attrs
diff --git a/python/mxnet/contrib/text/vocab.py
b/python/mxnet/contrib/text/vocab.py
index 6e9920d..7db3ee8 100644
--- a/python/mxnet/contrib/text/vocab.py
+++ b/python/mxnet/contrib/text/vocab.py
@@ -210,9 +210,8 @@ class Vocabulary(object):
tokens = []
for idx in indices:
- if not isinstance(idx, int) or idx > max_idx: # pylint:
disable=no-else-raise
+ if not isinstance(idx, int) or idx > max_idx:
raise ValueError('Token index %d in the provided `indices` is
invalid.' % idx)
- else:
- tokens.append(self.idx_to_token[idx])
+ tokens.append(self.idx_to_token[idx])
return tokens[0] if to_reduce else tokens
diff --git a/python/mxnet/gluon/trainer.py b/python/mxnet/gluon/trainer.py
index 0939490..c8aeb61 100644
--- a/python/mxnet/gluon/trainer.py
+++ b/python/mxnet/gluon/trainer.py
@@ -249,11 +249,11 @@ class Trainer(object):
@property
def learning_rate(self):
- if not isinstance(self._optimizer, opt.Optimizer): # pylint:
disable=no-else-raise
+ if not isinstance(self._optimizer, opt.Optimizer):
raise UserWarning("Optimizer has to be defined before its learning
"
"rate can be accessed.")
- else:
- return self._optimizer.learning_rate
+
+ return self._optimizer.learning_rate
@property
def optimizer(self):
@@ -270,11 +270,11 @@ class Trainer(object):
lr : float
The new learning rate of the optimizer.
"""
- if not isinstance(self._optimizer, opt.Optimizer): # pylint:
disable=no-else-raise
+ if not isinstance(self._optimizer, opt.Optimizer):
raise UserWarning("Optimizer has to be defined before its learning
"
"rate is mutated.")
- else:
- self._optimizer.set_learning_rate(lr)
+
+ self._optimizer.set_learning_rate(lr)
def _row_sparse_pull(self, parameter, out, row_id, full_idx=False):
"""Internal method to invoke pull operations on KVStore. If `full_idx`
is set to True,
diff --git a/python/mxnet/gluon/utils.py b/python/mxnet/gluon/utils.py
index 3957b74..2060f61 100644
--- a/python/mxnet/gluon/utils.py
+++ b/python/mxnet/gluon/utils.py
@@ -341,11 +341,11 @@ def download(url, path=None, overwrite=False,
sha1_hash=None, retries=5, verify_
break
except Exception as e:
retries -= 1
- if retries <= 0: # pylint: disable=no-else-raise
+ if retries <= 0:
raise e
- else:
- print('download failed due to {}, retrying, {} attempt{}
left'
- .format(repr(e), retries, 's' if retries > 1 else
''))
+
+ print('download failed due to {}, retrying, {} attempt{} left'
+ .format(repr(e), retries, 's' if retries > 1 else ''))
return fname
diff --git a/python/mxnet/image/detection.py b/python/mxnet/image/detection.py
index a70e572..48cf5bc 100644
--- a/python/mxnet/image/detection.py
+++ b/python/mxnet/image/detection.py
@@ -809,23 +809,23 @@ class ImageDetIter(ImageIter):
pad = batch_size - i
# handle padding for the last batch
if pad != 0:
- if self.last_batch_handle == 'discard': # pylint:
disable=no-else-raise
+ if self.last_batch_handle == 'discard':
raise StopIteration
# if the option is 'roll_over', throw StopIteration and cache the
data
- elif self.last_batch_handle == 'roll_over' and \
+ if self.last_batch_handle == 'roll_over' and \
self._cache_data is None:
self._cache_data = batch_data
self._cache_label = batch_label
self._cache_idx = i
raise StopIteration
+
+ _ = self._batchify(batch_data, batch_label, i)
+ if self.last_batch_handle == 'pad':
+ self._allow_read = False
else:
- _ = self._batchify(batch_data, batch_label, i)
- if self.last_batch_handle == 'pad':
- self._allow_read = False
- else:
- self._cache_data = None
- self._cache_label = None
- self._cache_idx = None
+ self._cache_data = None
+ self._cache_label = None
+ self._cache_idx = None
return io.DataBatch([batch_data], [batch_label], pad=pad)
diff --git a/python/mxnet/image/image.py b/python/mxnet/image/image.py
index a142282..bffd286 100644
--- a/python/mxnet/image/image.py
+++ b/python/mxnet/image/image.py
@@ -1198,10 +1198,10 @@ class ImageIter(io.DataIter):
logging.info('%s: loading recordio %s...',
class_name, path_imgrec)
if path_imgidx:
- self.imgrec = recordio.MXIndexedRecordIO(path_imgidx,
path_imgrec, 'r') # pylint: disable=redefined-variable-type
+ self.imgrec = recordio.MXIndexedRecordIO(path_imgidx,
path_imgrec, 'r')
self.imgidx = list(self.imgrec.keys)
else:
- self.imgrec = recordio.MXRecordIO(path_imgrec, 'r') # pylint:
disable=redefined-variable-type
+ self.imgrec = recordio.MXRecordIO(path_imgrec, 'r')
self.imgidx = None
else:
self.imgrec = None
@@ -1224,7 +1224,7 @@ class ImageIter(io.DataIter):
imgkeys = []
index = 1
for img in imglist:
- key = str(index) # pylint: disable=redefined-variable-type
+ key = str(index)
index += 1
if len(img) > 2:
label = nd.array(img[:-1], dtype=dtype)
@@ -1374,23 +1374,23 @@ class ImageIter(io.DataIter):
pad = batch_size - i
# handle padding for the last batch
if pad != 0:
- if self.last_batch_handle == 'discard': # pylint:
disable=no-else-raise
+ if self.last_batch_handle == 'discard':
raise StopIteration
# if the option is 'roll_over', throw StopIteration and cache the
data
- elif self.last_batch_handle == 'roll_over' and \
+ if self.last_batch_handle == 'roll_over' and \
self._cache_data is None:
self._cache_data = batch_data
self._cache_label = batch_label
self._cache_idx = i
raise StopIteration
+
+ _ = self._batchify(batch_data, batch_label, i)
+ if self.last_batch_handle == 'pad':
+ self._allow_read = False
else:
- _ = self._batchify(batch_data, batch_label, i)
- if self.last_batch_handle == 'pad':
- self._allow_read = False
- else:
- self._cache_data = None
- self._cache_label = None
- self._cache_idx = None
+ self._cache_data = None
+ self._cache_label = None
+ self._cache_idx = None
return io.DataBatch([batch_data], [batch_label], pad=pad)
diff --git a/python/mxnet/model.py b/python/mxnet/model.py
index 7e324a1..aee4a8c 100644
--- a/python/mxnet/model.py
+++ b/python/mxnet/model.py
@@ -642,10 +642,9 @@ class FeedForward(BASE_ESTIMATOR):
"""Initialize the iterator given input."""
if isinstance(X, (np.ndarray, nd.NDArray)):
if y is None:
- if is_train: # pylint: disable=no-else-raise
+ if is_train:
raise ValueError('y must be specified when X is
numpy.ndarray')
- else:
- y = np.zeros(X.shape[0])
+ y = np.zeros(X.shape[0])
if not isinstance(y, (np.ndarray, nd.NDArray)):
raise TypeError('y must be ndarray when X is numpy.ndarray')
if X.shape[0] != y.shape[0]:
diff --git a/python/mxnet/ndarray/sparse.py b/python/mxnet/ndarray/sparse.py
index 4987cb5..52c5de7 100644
--- a/python/mxnet/ndarray/sparse.py
+++ b/python/mxnet/ndarray/sparse.py
@@ -639,10 +639,10 @@ class RowSparseNDArray(BaseSparseNDArray):
if isinstance(key, int):
raise Exception("__getitem__ with int key is not implemented for
RowSparseNDArray yet")
if isinstance(key, py_slice):
- if key.step is not None or key.start is not None or key.stop is
not None: # pylint: disable=no-else-raise
+ if key.step is not None or key.start is not None or key.stop is
not None:
raise Exception('RowSparseNDArray only supports [:] for
__getitem__')
- else:
- return self
+
+ return self
if isinstance(key, tuple):
raise ValueError('Multi-dimension indexing is not supported')
raise ValueError('Undefined behaviour for {}'.format(key))
@@ -1102,9 +1102,9 @@ def row_sparse_array(arg1, shape=None, ctx=None,
dtype=None):
# construct a row sparse array from (D0, D1 ..) or (data, indices)
if isinstance(arg1, tuple):
arg_len = len(arg1)
- if arg_len < 2: # pylint: disable=no-else-raise
+ if arg_len < 2:
raise ValueError("Unexpected length of input tuple: " +
str(arg_len))
- elif arg_len > 2:
+ if arg_len > 2:
# empty ndarray with shape
_check_shape(arg1, shape)
return empty('row_sparse', arg1, ctx=ctx, dtype=dtype)
diff --git a/python/mxnet/test_utils.py b/python/mxnet/test_utils.py
index aa46a96..0e260ce 100644
--- a/python/mxnet/test_utils.py
+++ b/python/mxnet/test_utils.py
@@ -212,11 +212,11 @@ def _get_powerlaw_dataset_csr(num_rows, num_cols,
density=0.1, dtype=None):
return mx.nd.array(output_arr).tostype("csr")
col_max = col_max * 2
- if unused_nnz > 0: # pylint: disable=no-else-raise
+ if unused_nnz > 0:
raise ValueError("not supported for this density: %s"
" for this shape (%s,%s)" % (density, num_rows,
num_cols))
- else:
- return mx.nd.array(output_arr).tostype("csr")
+
+ return mx.nd.array(output_arr).tostype("csr")
def assign_each(the_input, function):
@@ -1407,10 +1407,10 @@ def check_consistency(sym, ctx_list, scale=1.0,
grad_req='write',
except AssertionError as e:
print('Predict Err: ctx %d vs ctx %d at %s'%(i, max_idx, name))
traceback.print_exc()
- if raise_on_err: # pylint: disable=no-else-raise
+ if raise_on_err:
raise e
- else:
- print(str(e))
+
+ print(str(e))
# train
if grad_req != 'null':
@@ -1434,10 +1434,10 @@ def check_consistency(sym, ctx_list, scale=1.0,
grad_req='write',
except AssertionError as e:
print('Train Err: ctx %d vs ctx %d at %s'%(i, max_idx,
name))
traceback.print_exc()
- if raise_on_err: # pylint: disable=no-else-raise
+ if raise_on_err:
raise e
- else:
- print(str(e))
+
+ print(str(e))
return gt
@@ -1514,11 +1514,11 @@ def download(url, fname=None, dirname=None,
overwrite=False, retries=5):
break
except Exception as e:
retries -= 1
- if retries <= 0: # pylint: disable=no-else-raise
+ if retries <= 0:
raise e
- else:
- print("download failed, retrying, {} attempt{} left"
- .format(retries, 's' if retries > 1 else ''))
+
+ print("download failed, retrying, {} attempt{} left"
+ .format(retries, 's' if retries > 1 else ''))
logging.info("downloaded %s into %s successfully", url, fname)
return fname
@@ -1661,7 +1661,7 @@ def get_mnist_iterator(batch_size, input_shape,
num_parts=1, part_index=0):
"""
get_mnist_ubyte()
- flat = False if len(input_shape) == 3 else True # pylint:
disable=simplifiable-if-expression
+ flat = not bool(len(input_shape) == 3)
train_dataiter = mx.io.MNISTIter(
image="data/train-images-idx3-ubyte",
