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The following commit(s) were added to refs/heads/master by this push:
new 2dcb35e Modernize Python 2 code to get ready for Python 3 (#11648)
2dcb35e is described below
commit 2dcb35ed101a3a1ea1ac6420b5061cc1f7473e7b
Author: cclauss <[email protected]>
AuthorDate: Thu Jul 12 17:38:43 2018 +0200
Modernize Python 2 code to get ready for Python 3 (#11648)
---
benchmark/python/sparse/sparse_op.py | 5 +++--
cpp-package/scripts/lint.py | 3 ++-
example/kaggle-ndsb1/train_dsb.py | 3 ++-
example/python-howto/multiple_outputs.py | 3 ++-
example/speech_recognition/singleton.py | 3 ++-
tests/nightly/TestDoc/doc_spell_checker.py | 7 ++++---
tests/nightly/compilation_warnings/process_output.py | 19 ++++++++++---------
tests/nightly/multi_lenet.py | 3 ++-
tools/accnn/utils.py | 9 +++++----
tools/coreml/converter/_mxnet_converter.py | 9 +++++----
tools/coreml/test/test_mxnet_image.py | 17 +++++++++--------
tools/coreml/test/test_mxnet_models.py | 3 ++-
tools/ipynb2md.py | 3 ++-
tools/kill-mxnet.py | 9 +++++----
14 files changed, 55 insertions(+), 41 deletions(-)
diff --git a/benchmark/python/sparse/sparse_op.py
b/benchmark/python/sparse/sparse_op.py
index 95ea7d5..ffa6de6 100644
--- a/benchmark/python/sparse/sparse_op.py
+++ b/benchmark/python/sparse/sparse_op.py
@@ -1,3 +1,4 @@
+from __future__ import print_function
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
@@ -96,9 +97,9 @@ def test_dot_real(data_dict):
os.system("head -n 2000 %r > %r" % (path, mini_path))
assert os.path.exists(mini_path)
- print "Running Benchmarking on %r data" % data_dict['data_mini']
+ print("Running Benchmarking on %r data" % data_dict['data_mini'])
for batch_size in data_dict['batch_size']: # iterator through different
batch size of choice
- print "batch_size is %d" % batch_size
+ print("batch_size is %d" % batch_size)
# model
data_shape = (k, )
train_iter = get_iter(mini_path, data_shape, batch_size)
diff --git a/cpp-package/scripts/lint.py b/cpp-package/scripts/lint.py
index f9f284f..f6e5498 100644
--- a/cpp-package/scripts/lint.py
+++ b/cpp-package/scripts/lint.py
@@ -21,6 +21,7 @@
"""Lint helper to generate lint summary of source.
Copyright by Contributors
"""
+from __future__ import print_function
import codecs
import sys
import re
@@ -91,7 +92,7 @@ class LintHelper(object):
(pylint_stdout, pylint_stderr) = epylint.py_run(
' '.join([str(path)] + self.pylint_opts), return_std=True)
emap = {}
- print pylint_stderr.read()
+ print(pylint_stderr.read())
for line in pylint_stdout:
sys.stderr.write(line)
key = line.split(':')[-1].split('(')[0].strip()
diff --git a/example/kaggle-ndsb1/train_dsb.py
b/example/kaggle-ndsb1/train_dsb.py
index 5cec0f6..dc2084a 100644
--- a/example/kaggle-ndsb1/train_dsb.py
+++ b/example/kaggle-ndsb1/train_dsb.py
@@ -1,3 +1,4 @@
+from __future__ import print_function
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
@@ -98,4 +99,4 @@ def get_iterator(args, kv):
# train
tic=time.time()
train_model.fit(args, net, get_iterator)
-print "time elapsed to train model", time.time()-tic
+print("time elapsed to train model", time.time()-tic)
diff --git a/example/python-howto/multiple_outputs.py
b/example/python-howto/multiple_outputs.py
index 43b4538..7c1ddd2 100644
--- a/example/python-howto/multiple_outputs.py
+++ b/example/python-howto/multiple_outputs.py
@@ -19,6 +19,7 @@
This example shows how to create a multiple output configuration.
"""
+from __future__ import print_function
import mxnet as mx
net = mx.symbol.Variable('data')
@@ -28,7 +29,7 @@ net = mx.symbol.FullyConnected(data=net, name='fc2',
num_hidden=64)
out = mx.symbol.SoftmaxOutput(data=net, name='softmax')
# group fc1 and out together
group = mx.symbol.Group([fc1, out])
-print group.list_outputs()
+print(group.list_outputs())
# You can go ahead and bind on the group
# executor = group.simple_bind(data=data_shape)
diff --git a/example/speech_recognition/singleton.py
b/example/speech_recognition/singleton.py
index aa9531b..1d68edf 100644
--- a/example/speech_recognition/singleton.py
+++ b/example/speech_recognition/singleton.py
@@ -1,3 +1,4 @@
+from __future__ import print_function
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
@@ -30,7 +31,7 @@ class Singleton:
return self._instance
def __new__(class_, *args, **kwargs):
- print "__new__"
+ print("__new__")
class_.instances[class_] = super(Singleton, class_).__new__(class_,
*args, **kwargs)
return class_.instances[class_]
diff --git a/tests/nightly/TestDoc/doc_spell_checker.py
b/tests/nightly/TestDoc/doc_spell_checker.py
index a33807e..88baab8 100644
--- a/tests/nightly/TestDoc/doc_spell_checker.py
+++ b/tests/nightly/TestDoc/doc_spell_checker.py
@@ -21,6 +21,7 @@
An exclude list is provided to avoid checking specific word,
such as NDArray.
"""
+from __future__ import print_function
import os
import sys
@@ -171,8 +172,8 @@ if __name__ == "__main__":
spell_check_res = DOC_PARSER.get_res()[0]
grammar_check_res = DOC_PARSER.get_res()[1]
if len(spell_check_res) > 0:
- print "%s has typo:" % os.path.join(root, read_file)
- print "%s\n" % spell_check_res
+ print("%s has typo:" % os.path.join(root, read_file))
+ print("%s\n" % spell_check_res)
ALL_CLEAR = False
if ALL_CLEAR:
- print "No typo is found."
+ print("No typo is found.")
diff --git a/tests/nightly/compilation_warnings/process_output.py
b/tests/nightly/compilation_warnings/process_output.py
index d7ed329..3d2dd91 100755
--- a/tests/nightly/compilation_warnings/process_output.py
+++ b/tests/nightly/compilation_warnings/process_output.py
@@ -1,3 +1,4 @@
+from __future__ import print_function
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
@@ -40,17 +41,17 @@ def generate_stats(warnings):
def print_summary(time, warnings):
sorted_warnings, total_count = generate_stats(warnings)
- print "START - Compilation warnings count"
- print total_count, 'warnings'
- print "END - Compilation warnings count"
- print 'START - Compilation warnings summary'
- print 'Time taken to compile:', time, 's'
- print 'Total number of warnings:', total_count, '\n'
+ print("START - Compilation warnings count")
+ print(total_count, 'warnings')
+ print("END - Compilation warnings count")
+ print('START - Compilation warnings summary')
+ print('Time taken to compile:', time, 's')
+ print('Total number of warnings:', total_count, '\n')
if total_count>0:
- print 'Below is the list of unique warnings and the number of
occurrences of that warning'
+ print('Below is the list of unique warnings and the number of
occurrences of that warning')
for warning, count in sorted_warnings:
- print count, ': ', warning
- print 'END - Compilation warnings summary'
+ print(count, ': ', warning)
+ print('END - Compilation warnings summary')
c_output = open(sys.argv[1],'r')
time, warnings = process_output(c_output.read())
diff --git a/tests/nightly/multi_lenet.py b/tests/nightly/multi_lenet.py
index 687588b..9475c72 100644
--- a/tests/nightly/multi_lenet.py
+++ b/tests/nightly/multi_lenet.py
@@ -29,6 +29,7 @@
# are performed, which can be controlled by either increasing the batch size or
# decreasing the number of epochs
+from __future__ import print_function
import os, sys
curr_path = os.path.abspath(os.path.dirname(__file__))
sys.path.append(os.path.join(curr_path, "../../example/image-classification"))
@@ -89,7 +90,7 @@ def get_XY(data_iter):
def test_data(data_iter):
# test whether we will get the identical data each time
X, Y = get_XY(data_iter)
- print X.shape, Y.shape
+ print(X.shape, Y.shape)
for i in range(4):
A, B = get_XY(data_iter)
assert(A.shape == X.shape)
diff --git a/tools/accnn/utils.py b/tools/accnn/utils.py
index 2795f85..b19521f 100644
--- a/tools/accnn/utils.py
+++ b/tools/accnn/utils.py
@@ -1,3 +1,4 @@
+from __future__ import print_function
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
@@ -62,7 +63,7 @@ def sym_factory(node, data):
for k, v in node['param'].items():
try:
params[k] = ast.literal_eval(v)
- except ValueError, e:
+ except ValueError as e:
params[k] = v
return getattr(mx.symbol, node['op'])(data=data, name=name, **params)
@@ -83,8 +84,8 @@ def replace_conv_layer(layer_name, old_model, sym_handle,
arg_handle):
if not
input_node['name'].startswith(node['name'])]
try:
data=sym_dict[datas[0]]
- except Exception, e:
- print 'can not find symbol %s'%(datas[0])
+ except Exception as e:
+ print('can not find symbol %s'%(datas[0]))
raise e
if node['name'] == layer_name:
sym = sym_handle(data, node)
@@ -101,7 +102,7 @@ def replace_conv_layer(layer_name, old_model, sym_handle,
arg_handle):
arg_shape_dic = dict(zip(arg_names, arg_shapes))
try:
arg_handle(arg_shape_dic, arg_params)
- except Exception, e:
+ except Exception as e:
raise Exception('Exception in arg_handle')
new_model = mx.model.FeedForward(
diff --git a/tools/coreml/converter/_mxnet_converter.py
b/tools/coreml/converter/_mxnet_converter.py
index a9ea0f4..2d91eb8 100644
--- a/tools/coreml/converter/_mxnet_converter.py
+++ b/tools/coreml/converter/_mxnet_converter.py
@@ -1,3 +1,4 @@
+from __future__ import print_function
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
@@ -68,9 +69,9 @@ def check_error(model, path, shapes, output =
'softmax_output', verbose = True):
error = _np.linalg.norm(e_out - mx_out)
if verbose:
- print "First few predictions from CoreML : %s" % e_out[0:10]
- print "First few predictions from MXNet : %s" % e_out[0:10]
- print "L2 Error on random data %s" % error
+ print("First few predictions from CoreML : %s" % e_out[0:10])
+ print("First few predictions from MXNet : %s" % e_out[0:10])
+ print("L2 Error on random data %s" % error)
return error
def _set_input_output_layers(builder, input_names, output_names):
@@ -228,4 +229,4 @@ def convert(model, input_shape, order = None, class_labels
= None, mode = None,
builder.set_class_labels(class_labels = labels)
# Return the model
- return _coremltools.models.MLModel(builder.spec)
\ No newline at end of file
+ return _coremltools.models.MLModel(builder.spec)
diff --git a/tools/coreml/test/test_mxnet_image.py
b/tools/coreml/test/test_mxnet_image.py
index 2bbf7b1..e373cae 100644
--- a/tools/coreml/test/test_mxnet_image.py
+++ b/tools/coreml/test/test_mxnet_image.py
@@ -1,3 +1,4 @@
+from __future__ import print_function
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
@@ -107,27 +108,27 @@ class ImageNetTest(unittest.TestCase):
num_batch += 1
if (num_batch == 5): break # we only use a subset of the batches.
- print "MXNet acc %s" % np.mean(mxnet_acc)
- print "Coreml acc %s" % np.mean(coreml_acc)
- print "MXNet top 5 acc %s" % np.mean(mxnet_top_5_acc)
- print "Coreml top 5 acc %s" % np.mean(coreml_top_5_acc)
+ print("MXNet acc %s" % np.mean(mxnet_acc))
+ print("Coreml acc %s" % np.mean(coreml_acc))
+ print("MXNet top 5 acc %s" % np.mean(mxnet_top_5_acc))
+ print("Coreml top 5 acc %s" % np.mean(coreml_top_5_acc))
self.assertAlmostEqual(np.mean(mxnet_acc), np.mean(coreml_acc),
delta=1e-4)
self.assertAlmostEqual(np.mean(mxnet_top_5_acc),
np.mean(coreml_top_5_acc), delta=1e-4)
def test_squeezenet(self):
- print "Testing Image Classification with Squeezenet"
+ print("Testing Image Classification with Squeezenet")
self._test_image_prediction(model_name='squeezenet_v1.1', epoch=0,
label_name='prob_label')
def test_inception_with_batch_normalization(self):
- print "Testing Image Classification with Inception/BatchNorm"
+ print("Testing Image Classification with Inception/BatchNorm")
self._test_image_prediction(model_name='Inception-BN', epoch=126,
label_name='softmax_label')
def test_resnet18(self):
- print "Testing Image Classification with ResNet18"
+ print("Testing Image Classification with ResNet18")
self._test_image_prediction(model_name='resnet-18', epoch=0,
label_name='softmax_label')
def test_vgg16(self):
- print "Testing Image Classification with vgg16"
+ print("Testing Image Classification with vgg16")
self._test_image_prediction(model_name='vgg16', epoch=0,
label_name='prob_label')
diff --git a/tools/coreml/test/test_mxnet_models.py
b/tools/coreml/test/test_mxnet_models.py
index 1732fb8..36ac0ec 100644
--- a/tools/coreml/test/test_mxnet_models.py
+++ b/tools/coreml/test/test_mxnet_models.py
@@ -1,3 +1,4 @@
+from __future__ import print_function
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
@@ -116,7 +117,7 @@ class ModelsTest(unittest.TestCase):
self.assertEqual(len(mxnet_pred), len(coreml_pred))
div.append(_kl_divergence(mxnet_pred, coreml_pred))
- print "Average KL divergence is % s" % np.mean(div)
+ print("Average KL divergence is % s" % np.mean(div))
self.assertTrue(np.mean(div) < 1e-4)
def test_pred_inception_bn(self):
diff --git a/tools/ipynb2md.py b/tools/ipynb2md.py
index 227174c..3708e81 100755
--- a/tools/ipynb2md.py
+++ b/tools/ipynb2md.py
@@ -24,6 +24,7 @@ removed.
It is heavily adapted from
https://gist.github.com/decabyte/0ed87372774cf5d34d7e
"""
+from __future__ import print_function
import sys
import io
@@ -61,7 +62,7 @@ def main():
old_ipynb = args.notebook[0]
new_ipynb = 'tmp.ipynb'
md_file = args.output
- print md_file
+ print(md_file)
if not md_file:
md_file = os.path.splitext(old_ipynb)[0] + '.md'
diff --git a/tools/kill-mxnet.py b/tools/kill-mxnet.py
index 2a4a430..321b2b8 100644
--- a/tools/kill-mxnet.py
+++ b/tools/kill-mxnet.py
@@ -18,11 +18,12 @@
# under the License.
+from __future__ import print_function
import os, sys
import subprocess
if len(sys.argv) != 4:
- print "usage: %s <hostfile> <user> <prog>" % sys.argv[0]
+ print("usage: %s <hostfile> <user> <prog>" % sys.argv[0])
sys.exit(1)
host_file = sys.argv[1]
@@ -36,19 +37,19 @@ kill_cmd = (
"awk '{if($1==\"" + user + "\")print $2;}' | "
"xargs kill -9"
)
-print kill_cmd
+print(kill_cmd)
# Kill program on remote machines
with open(host_file, "r") as f:
for host in f:
if ':' in host:
host = host[:host.index(':')]
- print host
+ print(host)
subprocess.Popen(["ssh", "-oStrictHostKeyChecking=no", "%s" % host,
kill_cmd],
shell=False,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
- print "Done killing"
+ print("Done killing")
# Kill program on local machine
os.system(kill_cmd)
