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new dc3ea81 [MXNET-313] Python: Resolve some of the undefined names
(#10490)
dc3ea81 is described below
commit dc3ea8161dab81b9b49daffcc09d36d8898e017b
Author: cclauss <ccla...@bluewin.ch>
AuthorDate: Mon Apr 23 21:35:13 2018 +0200
[MXNET-313] Python: Resolve some of the undefined names (#10490)
---
example/bi-lstm-sort/lstm_sort.py | 12 +++++----
.../data_helpers.py | 9 ++++---
example/cnn_text_classification/data_helpers.py | 10 +++++---
example/fcn-xs/solver.py | 2 +-
example/gluon/style_transfer/utils.py | 4 ++-
example/gluon/tree_lstm/dataset.py | 16 +++++++-----
example/reinforcement-learning/a3c/rl_data.py | 30 +++++++++++-----------
python/mxnet/gluon/parameter.py | 3 +--
python/mxnet/optimizer.py | 1 +
9 files changed, 50 insertions(+), 37 deletions(-)
diff --git a/example/bi-lstm-sort/lstm_sort.py
b/example/bi-lstm-sort/lstm_sort.py
index 3fd4a2a..3d7090a 100644
--- a/example/bi-lstm-sort/lstm_sort.py
+++ b/example/bi-lstm-sort/lstm_sort.py
@@ -17,27 +17,29 @@
# pylint:
disable=C0111,too-many-arguments,too-many-instance-attributes,too-many-locals,redefined-outer-name,fixme
# pylint: disable=superfluous-parens, no-member, invalid-name
+import argparse
+import errno
+import logging
import os
+import random
import sys
+
import numpy as np
-import mxnet as mx
-import random
-import argparse
+import mxnet as mx
from lstm import bi_lstm_unroll
from sort_io import BucketSentenceIter, default_build_vocab
-import logging
head = '%(asctime)-15s %(message)s'
logging.basicConfig(level=logging.DEBUG, format=head)
-
TRAIN_FILE = "sort.train.txt"
TEST_FILE = "sort.test.txt"
VALID_FILE = "sort.valid.txt"
DATA_DIR = os.path.join(os.getcwd(), "data")
SEQ_LEN = 5
+
def gen_data(seq_len, start_range, end_range):
if not os.path.exists(DATA_DIR):
try:
diff --git a/example/cnn_chinese_text_classification/data_helpers.py
b/example/cnn_chinese_text_classification/data_helpers.py
index 1a5c4ad..b3a13de 100644
--- a/example/cnn_chinese_text_classification/data_helpers.py
+++ b/example/cnn_chinese_text_classification/data_helpers.py
@@ -15,16 +15,17 @@
# specific language governing permissions and limitations
# under the License.
import codecs
-
-import numpy as np
-import re
import itertools
-from collections import Counter
import os
+import re
+from collections import Counter
+import numpy as np
+import word2vec
# from gensim.models import word2vec
+
def clean_str(string):
"""
Tokenization/string cleaning for all datasets except for SST.
diff --git a/example/cnn_text_classification/data_helpers.py
b/example/cnn_text_classification/data_helpers.py
index 3812683..b6fe1e6 100644
--- a/example/cnn_text_classification/data_helpers.py
+++ b/example/cnn_text_classification/data_helpers.py
@@ -15,13 +15,17 @@
# specific language governing permissions and limitations
# under the License.
-import numpy as np
-import re
import itertools
-from collections import Counter
import os
+import re
+from collections import Counter
+
+import numpy as np
+
+import word2vec
# from gensim.models import word2vec
+
def clean_str(string):
"""
Tokenization/string cleaning for all datasets except for SST.
diff --git a/example/fcn-xs/solver.py b/example/fcn-xs/solver.py
index cf7298b..e99b31a 100644
--- a/example/fcn-xs/solver.py
+++ b/example/fcn-xs/solver.py
@@ -63,7 +63,7 @@ class Solver(object):
else:
self.grad_params = None
aux_names = self.symbol.list_auxiliary_states()
- self.aux_params = {k : nd.zeros(s) for k, s in zip(aux_names,
aux_shapes)}
+ self.aux_params = {k: mx.nd.zeros(s) for k, s in zip(aux_names,
aux_shapes)}
data_name = train_data.data_name
label_name = train_data.label_name
input_names = [data_name, label_name]
diff --git a/example/gluon/style_transfer/utils.py
b/example/gluon/style_transfer/utils.py
index e027331..f869512 100644
--- a/example/gluon/style_transfer/utils.py
+++ b/example/gluon/style_transfer/utils.py
@@ -15,6 +15,7 @@
# specific language governing permissions and limitations
# under the License.
+import collections
import os
import numbers
from PIL import Image
@@ -23,6 +24,7 @@ import numpy as np
import mxnet as mx
import mxnet.ndarray as F
+
def tensor_load_rgbimage(filename, ctx, size=None, scale=None, keep_asp=False):
img = Image.open(filename).convert('RGB')
if size is not None:
@@ -209,7 +211,7 @@ class StyleLoader():
self.files = os.listdir(style_folder)
assert(len(self.files) > 0)
self.ctx = ctx
-
+
def get(self, i):
idx = i%len(self.files)
filepath = os.path.join(self.folder, self.files[idx])
diff --git a/example/gluon/tree_lstm/dataset.py
b/example/gluon/tree_lstm/dataset.py
index 4a836dd..02c57c0 100644
--- a/example/gluon/tree_lstm/dataset.py
+++ b/example/gluon/tree_lstm/dataset.py
@@ -15,14 +15,17 @@
# specific language governing permissions and limitations
# under the License.
-import os
import logging
-logging.basicConfig(level=logging.INFO)
-import numpy as np
+import os
import random
-from tqdm import tqdm
+
+import numpy as np
import mxnet as mx
+from tqdm import tqdm
+
+logging.basicConfig(level=logging.INFO)
+
class Vocab(object):
# constants for special tokens: padding, unknown, and beginning/end of
sentence.
@@ -34,6 +37,7 @@ class Vocab(object):
UNK_WORD = '<unk>'
BOS_WORD = '<s>'
EOS_WORD = '</s>'
+
def __init__(self, filepaths=[], embedpath=None, include_unseen=False,
lower=False):
self.idx2tok = []
self.tok2idx = {}
@@ -82,10 +86,10 @@ class Vocab(object):
return idx
def to_indices(self, tokens, add_bos=False, add_eos=False):
- vec = [BOS] if add_bos else []
+ vec = [Vocab.BOS] if add_bos else []
vec += [self.get_index(token) for token in tokens]
if add_eos:
- vec.append(EOS)
+ vec.append(Vocab.EOS)
return vec
def to_tokens(self, indices, stop):
diff --git a/example/reinforcement-learning/a3c/rl_data.py
b/example/reinforcement-learning/a3c/rl_data.py
index 70f2853..28ebec4 100644
--- a/example/reinforcement-learning/a3c/rl_data.py
+++ b/example/reinforcement-learning/a3c/rl_data.py
@@ -16,24 +16,26 @@
# under the License.
from __future__ import print_function
-import mxnet as mx
-import numpy as np
-import gym
-import cv2
+
import math
-from threading import Thread
-import time
import multiprocessing
import multiprocessing.pool
-from flask import Flask, render_template, Response
-import signal
-import sys
-is_py3 = sys.version[0] == '3'
-if is_py3:
+import time
+from threading import Thread
+
+import numpy as np
+from flask import Flask, Response, render_template
+
+import cv2
+import gym
+import mxnet as mx
+
+try:
import queue as queue
-else:
+except ImportError:
import Queue as queue
+
def make_web(queue):
app = Flask(__name__)
@@ -136,7 +138,7 @@ class RLDataIter(object):
try:
while self.queue.qsize() > 10:
self.queue.get(False)
- except Empty:
+ except queue.Empty:
pass
frame = self.visual()
self.queue.put(frame)
@@ -173,5 +175,3 @@ if __name__ == '__main__':
dataiter.next()
print(batch_size*100/(time.time() - tic))
tic = time.time()
-
-
diff --git a/python/mxnet/gluon/parameter.py b/python/mxnet/gluon/parameter.py
index 99885eb..04694df 100644
--- a/python/mxnet/gluon/parameter.py
+++ b/python/mxnet/gluon/parameter.py
@@ -26,7 +26,6 @@ from collections import OrderedDict
import warnings
import numpy as np
-
from ..base import mx_real_t, MXNetError
from .. import symbol, ndarray, initializer, context
from ..context import Context, cpu
@@ -645,7 +644,7 @@ class ParameterDict(object):
assert isinstance(param, Constant), \
"Parameter '{}' already exists but it is not a
constant.".format(
name)
- if isinstance(value, nd.NDArray):
+ if isinstance(value, ndarray.NDArray):
value = value.asnumpy()
assert param.shape == value.shape and \
(param.value.asnumpy() == value).all(), \
diff --git a/python/mxnet/optimizer.py b/python/mxnet/optimizer.py
index 2f7c51b..65540a9 100644
--- a/python/mxnet/optimizer.py
+++ b/python/mxnet/optimizer.py
@@ -18,6 +18,7 @@
# coding: utf-8
# pylint: disable=too-many-lines
"""Weight updating functions."""
+import logging
import math
import pickle
import warnings
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