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Posted to commits@mxnet.apache.org by zh...@apache.org on 2018/01/13 22:47:23 UTC
[incubator-mxnet] 03/03: fix path separator (#9352)
This is an automated email from the ASF dual-hosted git repository.
zhasheng pushed a commit to branch v1.0.0
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
commit 9ef196909ec7bf9cdda66d5b97c92793109798e1
Author: Sheng Zha <sz...@users.noreply.github.com>
AuthorDate: Mon Jan 8 21:25:56 2018 -0800
fix path separator (#9352)
---
python/mxnet/gluon/data/vision.py | 16 ++++++++--------
python/mxnet/gluon/model_zoo/model_store.py | 4 ++--
python/mxnet/gluon/model_zoo/vision/alexnet.py | 5 ++++-
python/mxnet/gluon/model_zoo/vision/densenet.py | 5 ++++-
python/mxnet/gluon/model_zoo/vision/inception.py | 5 ++++-
python/mxnet/gluon/model_zoo/vision/mobilenet.py | 5 ++++-
python/mxnet/gluon/model_zoo/vision/resnet.py | 5 ++++-
python/mxnet/gluon/model_zoo/vision/squeezenet.py | 5 ++++-
python/mxnet/gluon/model_zoo/vision/vgg.py | 5 ++++-
9 files changed, 38 insertions(+), 17 deletions(-)
diff --git a/python/mxnet/gluon/data/vision.py b/python/mxnet/gluon/data/vision.py
index 54da152..cb40af5 100644
--- a/python/mxnet/gluon/data/vision.py
+++ b/python/mxnet/gluon/data/vision.py
@@ -88,8 +88,8 @@ class MNIST(_DownloadedDataset):
transform=lambda data, label: (data.astype(np.float32)/255, label)
"""
- def __init__(self, root='~/.mxnet/datasets/mnist', train=True,
- transform=None):
+ def __init__(self, root=os.path.join('~', '.mxnet', 'datasets', 'mnist'),
+ train=True, transform=None):
self._train_data = ('train-images-idx3-ubyte.gz',
'6c95f4b05d2bf285e1bfb0e7960c31bd3b3f8a7d')
self._train_label = ('train-labels-idx1-ubyte.gz',
@@ -146,8 +146,8 @@ class FashionMNIST(MNIST):
transform=lambda data, label: (data.astype(np.float32)/255, label)
"""
- def __init__(self, root='~/.mxnet/datasets/fashion-mnist', train=True,
- transform=None):
+ def __init__(self, root=os.path.join('~', '.mxnet', 'datasets', 'fashion-mnist'),
+ train=True, transform=None):
self._train_data = ('train-images-idx3-ubyte.gz',
'0cf37b0d40ed5169c6b3aba31069a9770ac9043d')
self._train_label = ('train-labels-idx1-ubyte.gz',
@@ -177,8 +177,8 @@ class CIFAR10(_DownloadedDataset):
transform=lambda data, label: (data.astype(np.float32)/255, label)
"""
- def __init__(self, root='~/.mxnet/datasets/cifar10', train=True,
- transform=None):
+ def __init__(self, root=os.path.join('~', '.mxnet', 'datasets', 'cifar10'),
+ train=True, transform=None):
self._archive_file = ('cifar-10-binary.tar.gz', 'fab780a1e191a7eda0f345501ccd62d20f7ed891')
self._train_data = [('data_batch_1.bin', 'aadd24acce27caa71bf4b10992e9e7b2d74c2540'),
('data_batch_2.bin', 'c0ba65cce70568cd57b4e03e9ac8d2a5367c1795'),
@@ -239,8 +239,8 @@ class CIFAR100(CIFAR10):
transform=lambda data, label: (data.astype(np.float32)/255, label)
"""
- def __init__(self, root='~/.mxnet/datasets/cifar100', fine_label=False, train=True,
- transform=None):
+ def __init__(self, root=os.path.join('~', '.mxnet', 'datasets', 'cifar100'),
+ fine_label=False, train=True, transform=None):
self._archive_file = ('cifar-100-binary.tar.gz', 'a0bb982c76b83111308126cc779a992fa506b90b')
self._train_data = [('train.bin', 'e207cd2e05b73b1393c74c7f5e7bea451d63e08e')]
self._test_data = [('test.bin', '8fb6623e830365ff53cf14adec797474f5478006')]
diff --git a/python/mxnet/gluon/model_zoo/model_store.py b/python/mxnet/gluon/model_zoo/model_store.py
index bb54974..e7b53af 100644
--- a/python/mxnet/gluon/model_zoo/model_store.py
+++ b/python/mxnet/gluon/model_zoo/model_store.py
@@ -58,7 +58,7 @@ def short_hash(name):
raise ValueError('Pretrained model for {name} is not available.'.format(name=name))
return _model_sha1[name][:8]
-def get_model_file(name, root='~/.mxnet/models/'):
+def get_model_file(name, root=os.path.join('~', '.mxnet', 'models')):
r"""Return location for the pretrained on local file system.
This function will download from online model zoo when model cannot be found or has mismatch.
@@ -108,7 +108,7 @@ def get_model_file(name, root='~/.mxnet/models/'):
else:
raise ValueError('Downloaded file has different hash. Please try again.')
-def purge(root='~/.mxnet/models/'):
+def purge(root=os.path.join('~', '.mxnet', 'models')):
r"""Purge all pretrained model files in local file store.
Parameters
diff --git a/python/mxnet/gluon/model_zoo/vision/alexnet.py b/python/mxnet/gluon/model_zoo/vision/alexnet.py
index 05669d0..5549947 100644
--- a/python/mxnet/gluon/model_zoo/vision/alexnet.py
+++ b/python/mxnet/gluon/model_zoo/vision/alexnet.py
@@ -20,6 +20,8 @@
"""Alexnet, implemented in Gluon."""
__all__ = ['AlexNet', 'alexnet']
+import os
+
from ....context import cpu
from ...block import HybridBlock
from ... import nn
@@ -65,7 +67,8 @@ class AlexNet(HybridBlock):
return x
# Constructor
-def alexnet(pretrained=False, ctx=cpu(), root='~/.mxnet/models', **kwargs):
+def alexnet(pretrained=False, ctx=cpu(),
+ root=os.path.join('~', '.mxnet', 'models'), **kwargs):
r"""AlexNet model from the `"One weird trick..." <https://arxiv.org/abs/1404.5997>`_ paper.
Parameters
diff --git a/python/mxnet/gluon/model_zoo/vision/densenet.py b/python/mxnet/gluon/model_zoo/vision/densenet.py
index 16afb2d..37a91e6 100644
--- a/python/mxnet/gluon/model_zoo/vision/densenet.py
+++ b/python/mxnet/gluon/model_zoo/vision/densenet.py
@@ -20,6 +20,8 @@
"""DenseNet, implemented in Gluon."""
__all__ = ['DenseNet', 'densenet121', 'densenet161', 'densenet169', 'densenet201']
+import os
+
from ....context import cpu
from ...block import HybridBlock
from ... import nn
@@ -119,7 +121,8 @@ densenet_spec = {121: (64, 32, [6, 12, 24, 16]),
# Constructor
-def get_densenet(num_layers, pretrained=False, ctx=cpu(), root='~/.mxnet/models', **kwargs):
+def get_densenet(num_layers, pretrained=False, ctx=cpu(),
+ root=os.path.join('~', '.mxnet', 'models'), **kwargs):
r"""Densenet-BC model from the
`"Densely Connected Convolutional Networks" <https://arxiv.org/pdf/1608.06993.pdf>`_ paper.
diff --git a/python/mxnet/gluon/model_zoo/vision/inception.py b/python/mxnet/gluon/model_zoo/vision/inception.py
index 3ef0fb9..42f0d3d 100644
--- a/python/mxnet/gluon/model_zoo/vision/inception.py
+++ b/python/mxnet/gluon/model_zoo/vision/inception.py
@@ -20,6 +20,8 @@
"""Inception, implemented in Gluon."""
__all__ = ['Inception3', 'inception_v3']
+import os
+
from ....context import cpu
from ...block import HybridBlock
from ... import nn
@@ -196,7 +198,8 @@ class Inception3(HybridBlock):
return x
# Constructor
-def inception_v3(pretrained=False, ctx=cpu(), root='~/.mxnet/models', **kwargs):
+def inception_v3(pretrained=False, ctx=cpu(),
+ root=os.path.join('~', '.mxnet', 'models'), **kwargs):
r"""Inception v3 model from
`"Rethinking the Inception Architecture for Computer Vision"
<http://arxiv.org/abs/1512.00567>`_ paper.
diff --git a/python/mxnet/gluon/model_zoo/vision/mobilenet.py b/python/mxnet/gluon/model_zoo/vision/mobilenet.py
index 0ba0933..4b94b27 100644
--- a/python/mxnet/gluon/model_zoo/vision/mobilenet.py
+++ b/python/mxnet/gluon/model_zoo/vision/mobilenet.py
@@ -21,6 +21,8 @@
__all__ = ['MobileNet', 'mobilenet1_0', 'mobilenet0_75', 'mobilenet0_5', 'mobilenet0_25',
'get_mobilenet']
+import os
+
from ....context import cpu
from ...block import HybridBlock
from ... import nn
@@ -73,7 +75,8 @@ class MobileNet(HybridBlock):
return x
# Constructor
-def get_mobilenet(multiplier, pretrained=False, ctx=cpu(), root='~/.mxnet/models', **kwargs):
+def get_mobilenet(multiplier, pretrained=False, ctx=cpu(),
+ root=os.path.join('~', '.mxnet', 'models'), **kwargs):
r"""MobileNet model from the
`"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications"
<https://arxiv.org/abs/1704.04861>`_ paper.
diff --git a/python/mxnet/gluon/model_zoo/vision/resnet.py b/python/mxnet/gluon/model_zoo/vision/resnet.py
index d720d64..3ba9c13 100644
--- a/python/mxnet/gluon/model_zoo/vision/resnet.py
+++ b/python/mxnet/gluon/model_zoo/vision/resnet.py
@@ -27,6 +27,8 @@ __all__ = ['ResNetV1', 'ResNetV2',
'resnet18_v2', 'resnet34_v2', 'resnet50_v2', 'resnet101_v2', 'resnet152_v2',
'get_resnet']
+import os
+
from ....context import cpu
from ...block import HybridBlock
from ... import nn
@@ -353,7 +355,8 @@ resnet_block_versions = [{'basic_block': BasicBlockV1, 'bottle_neck': Bottleneck
# Constructor
-def get_resnet(version, num_layers, pretrained=False, ctx=cpu(), root='~/.mxnet/models', **kwargs):
+def get_resnet(version, num_layers, pretrained=False, ctx=cpu(),
+ root=os.path.join('~', '.mxnet', 'models'), **kwargs):
r"""ResNet V1 model from `"Deep Residual Learning for Image Recognition"
<http://arxiv.org/abs/1512.03385>`_ paper.
ResNet V2 model from `"Identity Mappings in Deep Residual Networks"
diff --git a/python/mxnet/gluon/model_zoo/vision/squeezenet.py b/python/mxnet/gluon/model_zoo/vision/squeezenet.py
index 60ef393..7eff102 100644
--- a/python/mxnet/gluon/model_zoo/vision/squeezenet.py
+++ b/python/mxnet/gluon/model_zoo/vision/squeezenet.py
@@ -20,6 +20,8 @@
"""SqueezeNet, implemented in Gluon."""
__all__ = ['SqueezeNet', 'squeezenet1_0', 'squeezenet1_1']
+import os
+
from ....context import cpu
from ...block import HybridBlock
from ... import nn
@@ -107,7 +109,8 @@ class SqueezeNet(HybridBlock):
return x
# Constructor
-def get_squeezenet(version, pretrained=False, ctx=cpu(), root='~/.mxnet/models', **kwargs):
+def get_squeezenet(version, pretrained=False, ctx=cpu(),
+ root=os.path.join('~', '.mxnet', 'models'), **kwargs):
r"""SqueezeNet model from the `"SqueezeNet: AlexNet-level accuracy with 50x fewer parameters
and <0.5MB model size" <https://arxiv.org/abs/1602.07360>`_ paper.
SqueezeNet 1.1 model from the `official SqueezeNet repo
diff --git a/python/mxnet/gluon/model_zoo/vision/vgg.py b/python/mxnet/gluon/model_zoo/vision/vgg.py
index c524e8e..dbae538 100644
--- a/python/mxnet/gluon/model_zoo/vision/vgg.py
+++ b/python/mxnet/gluon/model_zoo/vision/vgg.py
@@ -24,6 +24,8 @@ __all__ = ['VGG',
'vgg11_bn', 'vgg13_bn', 'vgg16_bn', 'vgg19_bn',
'get_vgg']
+import os
+
from ....context import cpu
from ....initializer import Xavier
from ...block import HybridBlock
@@ -91,7 +93,8 @@ vgg_spec = {11: ([1, 1, 2, 2, 2], [64, 128, 256, 512, 512]),
# Constructors
-def get_vgg(num_layers, pretrained=False, ctx=cpu(), root='~/.mxnet/models', **kwargs):
+def get_vgg(num_layers, pretrained=False, ctx=cpu(),
+ root=os.path.join('~', '.mxnet', 'models'), **kwargs):
r"""VGG model from the `"Very Deep Convolutional Networks for Large-Scale Image Recognition"
<https://arxiv.org/abs/1409.1556>`_ paper.
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