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体验新版 GitCode,发现更多精彩内容 >>
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8e7dff30
编写于
2月 27, 2018
作者:
A
Aston Zhang
提交者:
GitHub
2月 27, 2018
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Merge pull request #212 from astonzhang/nin
Add transform=None in utils.DataLoader
上级
f111a6c2
f1203616
变更
1
隐藏空白更改
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1 changed file
with
6 addition
and
5 deletion
+6
-5
utils.py
utils.py
+6
-5
未找到文件。
utils.py
浏览文件 @
8e7dff30
...
...
@@ -16,7 +16,7 @@ class DataLoader(object):
time. But the limits are 1) all examples in dataset have the same shape, 2)
data transfomer needs to process multiple examples at each time
"""
def
__init__
(
self
,
dataset
,
batch_size
,
shuffle
,
transform
):
def
__init__
(
self
,
dataset
,
batch_size
,
shuffle
,
transform
=
None
):
self
.
dataset
=
dataset
self
.
batch_size
=
batch_size
self
.
shuffle
=
shuffle
...
...
@@ -47,7 +47,7 @@ class DataLoader(object):
def
load_data_fashion_mnist
(
batch_size
,
resize
=
None
,
root
=
"~/.mxnet/datasets/fashion-mnist"
):
"""download the fashion mnist dataest and then load into memory"""
def
transform_mnist
(
data
,
label
):
#
transform a batch of examples
#
Transform a batch of examples.
if
resize
:
n
=
data
.
shape
[
0
]
new_data
=
nd
.
zeros
((
n
,
resize
,
resize
,
data
.
shape
[
3
]))
...
...
@@ -56,11 +56,12 @@ def load_data_fashion_mnist(batch_size, resize=None, root="~/.mxnet/datasets/fas
data
=
new_data
# change data from batch x height x width x channel to batch x channel x height x width
return
nd
.
transpose
(
data
.
astype
(
'float32'
),
(
0
,
3
,
1
,
2
))
/
255
,
label
.
astype
(
'float32'
)
mnist_train
=
gluon
.
data
.
vision
.
FashionMNIST
(
root
=
root
,
train
=
True
,
transform
=
None
)
mnist_test
=
gluon
.
data
.
vision
.
FashionMNIST
(
root
=
root
,
train
=
False
,
transform
=
None
)
train_data
=
DataLoader
(
mnist_train
,
batch_size
,
shuffle
=
True
,
transform
=
transform_mnist
)
test_data
=
DataLoader
(
mnist_test
,
batch_size
,
shuffle
=
False
,
transform
=
transform_mnist
)
# Transform later to avoid memory explosion.
train_data
=
DataLoader
(
mnist_train
,
batch_size
,
shuffle
=
True
,
transform
=
transform_mnist
)
test_data
=
DataLoader
(
mnist_test
,
batch_size
,
shuffle
=
False
,
transform
=
transform_mnist
)
return
(
train_data
,
test_data
)
def
try_gpu
():
...
...
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