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ModelZoo
ResNet50_tensorflow
Commits
71bf3d47
Commit
71bf3d47
authored
May 16, 2017
by
Neal Wu
Committed by
GitHub
May 16, 2017
Browse files
Merge pull request #1473 from kemaswill/FixTypo_20170515
Fix Typo
parents
d066ee74
22c95c54
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inception/inception/inception_train.py
inception/inception/inception_train.py
+2
-2
tutorials/image/cifar10/cifar10_multi_gpu_train.py
tutorials/image/cifar10/cifar10_multi_gpu_train.py
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-1
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inception/inception/inception_train.py
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71bf3d47
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@@ -12,7 +12,7 @@
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@@ -12,7 +12,7 @@
# See the License for the specific language governing permissions and
# See the License for the specific language governing permissions and
# limitations under the License.
# limitations under the License.
# ==============================================================================
# ==============================================================================
"""A library to train Inception using multiple GPU
'
s with synchronous updates.
"""A library to train Inception using multiple GPUs with synchronous updates.
"""
"""
from
__future__
import
absolute_import
from
__future__
import
absolute_import
from
__future__
import
division
from
__future__
import
division
...
@@ -83,7 +83,7 @@ def _tower_loss(images, labels, num_classes, scope, reuse_variables=None):
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@@ -83,7 +83,7 @@ def _tower_loss(images, labels, num_classes, scope, reuse_variables=None):
"""Calculate the total loss on a single tower running the ImageNet model.
"""Calculate the total loss on a single tower running the ImageNet model.
We perform 'batch splitting'. This means that we cut up a batch across
We perform 'batch splitting'. This means that we cut up a batch across
multiple GPU
'
s. For instance, if the batch size = 32 and num_gpus = 2,
multiple GPUs. For instance, if the batch size = 32 and num_gpus = 2,
then each tower will operate on an batch of 16 images.
then each tower will operate on an batch of 16 images.
Args:
Args:
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tutorials/image/cifar10/cifar10_multi_gpu_train.py
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71bf3d47
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@@ -13,7 +13,7 @@
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@@ -13,7 +13,7 @@
# limitations under the License.
# limitations under the License.
# ==============================================================================
# ==============================================================================
"""A binary to train CIFAR-10 using multiple GPU
'
s with synchronous updates.
"""A binary to train CIFAR-10 using multiple GPUs with synchronous updates.
Accuracy:
Accuracy:
cifar10_multi_gpu_train.py achieves ~86% accuracy after 100K steps (256
cifar10_multi_gpu_train.py achieves ~86% accuracy after 100K steps (256
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