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CNNArch2Gluon
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monticore
EmbeddedMontiArc
generators
CNNArch2Gluon
Commits
bf56b53c
Commit
bf56b53c
authored
Jan 10, 2020
by
Sebastian N.
Browse files
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Plain Diff
Added shuffle_data and clip_global_grad_norm params
parent
fb939c7a
Changes
9
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9 changed files
with
84 additions
and
24 deletions
+84
-24
src/main/resources/templates/gluon/CNNDataLoader.ftl
src/main/resources/templates/gluon/CNNDataLoader.ftl
+6
-4
src/main/resources/templates/gluon/CNNSupervisedTrainer.ftl
src/main/resources/templates/gluon/CNNSupervisedTrainer.ftl
+18
-2
src/main/resources/templates/gluon/CNNTrainer.ftl
src/main/resources/templates/gluon/CNNTrainer.ftl
+6
-0
src/test/resources/target_code/CNNDataLoader_Alexnet.py
src/test/resources/target_code/CNNDataLoader_Alexnet.py
+6
-4
src/test/resources/target_code/CNNDataLoader_CifarClassifierNetwork.py
...urces/target_code/CNNDataLoader_CifarClassifierNetwork.py
+6
-4
src/test/resources/target_code/CNNDataLoader_VGG16.py
src/test/resources/target_code/CNNDataLoader_VGG16.py
+6
-4
src/test/resources/target_code/CNNSupervisedTrainer_Alexnet.py
...est/resources/target_code/CNNSupervisedTrainer_Alexnet.py
+12
-2
src/test/resources/target_code/CNNSupervisedTrainer_CifarClassifierNetwork.py
...arget_code/CNNSupervisedTrainer_CifarClassifierNetwork.py
+12
-2
src/test/resources/target_code/CNNSupervisedTrainer_VGG16.py
src/test/resources/target_code/CNNSupervisedTrainer_VGG16.py
+12
-2
No files found.
src/main/resources/templates/gluon/CNNDataLoader.ftl
View file @
bf56b53c
...
...
@@ -16,7 +16,7 @@ class ${tc.fileNameWithoutEnding}:
def __init__(self):
self._data_dir = "${tc.dataPath}/"
def load_data(self, batch_size):
def load_data(self, batch_size
, shuffle=False
):
train_h5, test_h5 = self.load_h5_files()
train_data = {}
...
...
@@ -40,7 +40,8 @@ class ${tc.fileNameWithoutEnding}:
train_iter = mx.io.NDArrayIter(data=train_data,
label=train_label,
batch_size=batch_size)
batch_size=batch_size,
shuffle=shuffle)
test_iter = None
...
...
@@ -65,7 +66,7 @@ class ${tc.fileNameWithoutEnding}:
return train_iter, test_iter, data_mean, data_std, train_images, test_images
def load_preprocessed_data(self, batch_size, preproc_lib):
def load_preprocessed_data(self, batch_size, preproc_lib
, shuffle=False
):
train_h5, test_h5 = self.load_h5_files()
wrapper = importlib.import_module(preproc_lib)
...
...
@@ -111,7 +112,8 @@ class ${tc.fileNameWithoutEnding}:
train_iter = mx.io.NDArrayIter(data=train_data,
label=train_label,
batch_size=batch_size)
batch_size=batch_size,
shuffle=shuffle)
test_data = {}
test_label = {}
...
...
src/main/resources/templates/gluon/CNNSupervisedTrainer.ftl
View file @
bf56b53c
...
...
@@ -193,6 +193,8 @@ class ${tc.fileNameWithoutEnding}:
save_attention_image=False,
use_teacher_forcing=False,
normalize=True,
shuffle_data=False,
clip_global_grad_norm=None,
preprocessing = False):
if context == 'gpu':
mx_context = mx.gpu()
...
...
@@ -203,9 +205,9 @@ class ${tc.fileNameWithoutEnding}:
if preprocessing:
preproc_lib = "CNNPreprocessor_${tc.fileNameWithoutEnding?keep_after("CNNSupervisedTrainer_")}_executor"
train_iter, test_iter, data_mean, data_std, train_images, test_images = self._data_loader.load_preprocessed_data(batch_size, preproc_lib)
train_iter, test_iter, data_mean, data_std, train_images, test_images = self._data_loader.load_preprocessed_data(batch_size, preproc_lib
, shuffle_data
)
else:
train_iter, test_iter, data_mean, data_std, train_images, test_images = self._data_loader.load_data(batch_size)
train_iter, test_iter, data_mean, data_std, train_images, test_images = self._data_loader.load_data(batch_size
, shuffle_data
)
if 'weight_decay' in optimizer_params:
optimizer_params['wd'] = optimizer_params['weight_decay']
...
...
@@ -282,6 +284,12 @@ class ${tc.fileNameWithoutEnding}:
tic = None
for epoch in range(begin_epoch, begin_epoch + num_epoch):
if shuffle_data:
if preprocessing:
preproc_lib = "CNNPreprocessor_${tc.fileNameWithoutEnding?keep_after("CNNSupervisedTrainer_")}_executor"
train_iter, test_iter, data_mean, data_std, train_images, test_images = self._data_loader.load_preprocessed_data(batch_size, preproc_lib, shuffle_data)
else:
train_iter, test_iter, data_mean, data_std, train_images, test_images = self._data_loader.load_data(batch_size, shuffle_data)
loss_total = 0
train_iter.reset()
...
...
@@ -297,6 +305,14 @@ class ${tc.fileNameWithoutEnding}:
loss_total += loss.sum().asscalar()
if clip_global_grad_norm:
grads = []
for network in self._networks.values():
grads.extend([param.grad(mx_context) for param in network.collect_params().values()])
gluon.utils.clip_global_norm(grads, clip_global_grad_norm)
for trainer in trainers:
trainer.step(batch_size)
...
...
src/main/resources/templates/gluon/CNNTrainer.ftl
View file @
bf56b53c
...
...
@@ -43,6 +43,12 @@ if __name__ == "__main__":
<#if (config.normalize)??>
normalize=${config.normalize?string("True","False")},
</#if>
<#if (config.shuffleData)??>
shuffle_data=${config.shuffleData?string("True","False")},
</#if>
<#if (config.clipGlobalGradNorm)??>
clip_global_grad_norm=${config.clipGlobalGradNorm},
</#if>
<#if (config.preprocessingName)??>
preprocessing=${config.preprocessingName???string("True","False")},
</#if>
...
...
src/test/resources/target_code/CNNDataLoader_Alexnet.py
View file @
bf56b53c
...
...
@@ -15,7 +15,7 @@ class CNNDataLoader_Alexnet:
def
__init__
(
self
):
self
.
_data_dir
=
"data/Alexnet/"
def
load_data
(
self
,
batch_size
):
def
load_data
(
self
,
batch_size
,
shuffle
=
False
):
train_h5
,
test_h5
=
self
.
load_h5_files
()
train_data
=
{}
...
...
@@ -39,7 +39,8 @@ class CNNDataLoader_Alexnet:
train_iter
=
mx
.
io
.
NDArrayIter
(
data
=
train_data
,
label
=
train_label
,
batch_size
=
batch_size
)
batch_size
=
batch_size
,
shuffle
=
shuffle
)
test_iter
=
None
...
...
@@ -64,7 +65,7 @@ class CNNDataLoader_Alexnet:
return
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
def
load_preprocessed_data
(
self
,
batch_size
,
preproc_lib
):
def
load_preprocessed_data
(
self
,
batch_size
,
preproc_lib
,
shuffle
=
False
):
train_h5
,
test_h5
=
self
.
load_h5_files
()
wrapper
=
importlib
.
import_module
(
preproc_lib
)
...
...
@@ -110,7 +111,8 @@ class CNNDataLoader_Alexnet:
train_iter
=
mx
.
io
.
NDArrayIter
(
data
=
train_data
,
label
=
train_label
,
batch_size
=
batch_size
)
batch_size
=
batch_size
,
shuffle
=
shuffle
)
test_data
=
{}
test_label
=
{}
...
...
src/test/resources/target_code/CNNDataLoader_CifarClassifierNetwork.py
View file @
bf56b53c
...
...
@@ -15,7 +15,7 @@ class CNNDataLoader_CifarClassifierNetwork:
def
__init__
(
self
):
self
.
_data_dir
=
"data/CifarClassifierNetwork/"
def
load_data
(
self
,
batch_size
):
def
load_data
(
self
,
batch_size
,
shuffle
=
False
):
train_h5
,
test_h5
=
self
.
load_h5_files
()
train_data
=
{}
...
...
@@ -39,7 +39,8 @@ class CNNDataLoader_CifarClassifierNetwork:
train_iter
=
mx
.
io
.
NDArrayIter
(
data
=
train_data
,
label
=
train_label
,
batch_size
=
batch_size
)
batch_size
=
batch_size
,
shuffle
=
shuffle
)
test_iter
=
None
...
...
@@ -64,7 +65,7 @@ class CNNDataLoader_CifarClassifierNetwork:
return
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
def
load_preprocessed_data
(
self
,
batch_size
,
preproc_lib
):
def
load_preprocessed_data
(
self
,
batch_size
,
preproc_lib
,
shuffle
=
False
):
train_h5
,
test_h5
=
self
.
load_h5_files
()
wrapper
=
importlib
.
import_module
(
preproc_lib
)
...
...
@@ -110,7 +111,8 @@ class CNNDataLoader_CifarClassifierNetwork:
train_iter
=
mx
.
io
.
NDArrayIter
(
data
=
train_data
,
label
=
train_label
,
batch_size
=
batch_size
)
batch_size
=
batch_size
,
shuffle
=
shuffle
)
test_data
=
{}
test_label
=
{}
...
...
src/test/resources/target_code/CNNDataLoader_VGG16.py
View file @
bf56b53c
...
...
@@ -15,7 +15,7 @@ class CNNDataLoader_VGG16:
def
__init__
(
self
):
self
.
_data_dir
=
"data/VGG16/"
def
load_data
(
self
,
batch_size
):
def
load_data
(
self
,
batch_size
,
shuffle
=
False
):
train_h5
,
test_h5
=
self
.
load_h5_files
()
train_data
=
{}
...
...
@@ -39,7 +39,8 @@ class CNNDataLoader_VGG16:
train_iter
=
mx
.
io
.
NDArrayIter
(
data
=
train_data
,
label
=
train_label
,
batch_size
=
batch_size
)
batch_size
=
batch_size
,
shuffle
=
shuffle
)
test_iter
=
None
...
...
@@ -64,7 +65,7 @@ class CNNDataLoader_VGG16:
return
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
def
load_preprocessed_data
(
self
,
batch_size
,
preproc_lib
):
def
load_preprocessed_data
(
self
,
batch_size
,
preproc_lib
,
shuffle
=
False
):
train_h5
,
test_h5
=
self
.
load_h5_files
()
wrapper
=
importlib
.
import_module
(
preproc_lib
)
...
...
@@ -110,7 +111,8 @@ class CNNDataLoader_VGG16:
train_iter
=
mx
.
io
.
NDArrayIter
(
data
=
train_data
,
label
=
train_label
,
batch_size
=
batch_size
)
batch_size
=
batch_size
,
shuffle
=
shuffle
)
test_data
=
{}
test_label
=
{}
...
...
src/test/resources/target_code/CNNSupervisedTrainer_Alexnet.py
View file @
bf56b53c
...
...
@@ -192,6 +192,8 @@ class CNNSupervisedTrainer_Alexnet:
save_attention_image
=
False
,
use_teacher_forcing
=
False
,
normalize
=
True
,
shuffle_data
=
False
,
clip_global_grad_norm
=
None
,
preprocessing
=
False
):
if
context
==
'gpu'
:
mx_context
=
mx
.
gpu
()
...
...
@@ -202,9 +204,9 @@ class CNNSupervisedTrainer_Alexnet:
if
preprocessing
:
preproc_lib
=
"CNNPreprocessor_Alexnet_executor"
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_preprocessed_data
(
batch_size
,
preproc_lib
)
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_preprocessed_data
(
batch_size
,
preproc_lib
,
shuffle_data
)
else
:
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_data
(
batch_size
)
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_data
(
batch_size
,
shuffle_data
)
if
'weight_decay'
in
optimizer_params
:
optimizer_params
[
'wd'
]
=
optimizer_params
[
'weight_decay'
]
...
...
@@ -309,6 +311,14 @@ class CNNSupervisedTrainer_Alexnet:
loss_total
+=
loss
.
sum
().
asscalar
()
if
clip_global_grad_norm
:
grads
=
[]
for
network
in
self
.
_networks
.
values
():
grads
.
extend
([
param
.
grad
(
mx_context
)
for
param
in
network
.
collect_params
().
values
()])
gluon
.
utils
.
clip_global_norm
(
grads
,
clip_global_grad_norm
)
for
trainer
in
trainers
:
trainer
.
step
(
batch_size
)
...
...
src/test/resources/target_code/CNNSupervisedTrainer_CifarClassifierNetwork.py
View file @
bf56b53c
...
...
@@ -192,6 +192,8 @@ class CNNSupervisedTrainer_CifarClassifierNetwork:
save_attention_image
=
False
,
use_teacher_forcing
=
False
,
normalize
=
True
,
shuffle_data
=
False
,
clip_global_grad_norm
=
None
,
preprocessing
=
False
):
if
context
==
'gpu'
:
mx_context
=
mx
.
gpu
()
...
...
@@ -202,9 +204,9 @@ class CNNSupervisedTrainer_CifarClassifierNetwork:
if
preprocessing
:
preproc_lib
=
"CNNPreprocessor_CifarClassifierNetwork_executor"
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_preprocessed_data
(
batch_size
,
preproc_lib
)
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_preprocessed_data
(
batch_size
,
preproc_lib
,
shuffle_data
)
else
:
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_data
(
batch_size
)
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_data
(
batch_size
,
shuffle_data
)
if
'weight_decay'
in
optimizer_params
:
optimizer_params
[
'wd'
]
=
optimizer_params
[
'weight_decay'
]
...
...
@@ -309,6 +311,14 @@ class CNNSupervisedTrainer_CifarClassifierNetwork:
loss_total
+=
loss
.
sum
().
asscalar
()
if
clip_global_grad_norm
:
grads
=
[]
for
network
in
self
.
_networks
.
values
():
grads
.
extend
([
param
.
grad
(
mx_context
)
for
param
in
network
.
collect_params
().
values
()])
gluon
.
utils
.
clip_global_norm
(
grads
,
clip_global_grad_norm
)
for
trainer
in
trainers
:
trainer
.
step
(
batch_size
)
...
...
src/test/resources/target_code/CNNSupervisedTrainer_VGG16.py
View file @
bf56b53c
...
...
@@ -192,6 +192,8 @@ class CNNSupervisedTrainer_VGG16:
save_attention_image
=
False
,
use_teacher_forcing
=
False
,
normalize
=
True
,
shuffle_data
=
False
,
clip_global_grad_norm
=
None
,
preprocessing
=
False
):
if
context
==
'gpu'
:
mx_context
=
mx
.
gpu
()
...
...
@@ -202,9 +204,9 @@ class CNNSupervisedTrainer_VGG16:
if
preprocessing
:
preproc_lib
=
"CNNPreprocessor_VGG16_executor"
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_preprocessed_data
(
batch_size
,
preproc_lib
)
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_preprocessed_data
(
batch_size
,
preproc_lib
,
shuffle_data
)
else
:
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_data
(
batch_size
)
train_iter
,
test_iter
,
data_mean
,
data_std
,
train_images
,
test_images
=
self
.
_data_loader
.
load_data
(
batch_size
,
shuffle_data
)
if
'weight_decay'
in
optimizer_params
:
optimizer_params
[
'wd'
]
=
optimizer_params
[
'weight_decay'
]
...
...
@@ -309,6 +311,14 @@ class CNNSupervisedTrainer_VGG16:
loss_total
+=
loss
.
sum
().
asscalar
()
if
clip_global_grad_norm
:
grads
=
[]
for
network
in
self
.
_networks
.
values
():
grads
.
extend
([
param
.
grad
(
mx_context
)
for
param
in
network
.
collect_params
().
values
()])
gluon
.
utils
.
clip_global_norm
(
grads
,
clip_global_grad_norm
)
for
trainer
in
trainers
:
trainer
.
step
(
batch_size
)
...
...
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