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Update MD5 for weights

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Somshubra Majumdar
2017-09-07 08:50:05 -05:00
parent 5c6fd53a33
commit 72f6ca1716
1 changed files with 6 additions and 6 deletions
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keras_contrib/applications/densenet.py
+6 -6
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@@ -231,7 +231,7 @@ def DenseNet(input_shape=None,
weights_loaded = False
if (depth == 121) and (nb_dense_block == 4) and (growth_rate == 32) and (nb_filter == 64) and \
(bottleneck is True) and (reduction == 0.5) and (subsample_initial_block):
(bottleneck is True) and (reduction == 0.5) and (dropout_rate == 0.0) and (subsample_initial_block):
if include_top:
weights_path = get_file('DenseNet-BC-121-32.h5',
DENSENET_121_WEIGHTS_PATH,
@@ -241,12 +241,12 @@ def DenseNet(input_shape=None,
weights_path = get_file('DenseNet-BC-121-32-no-top.h5',
DENSENET_121_WEIGHTS_PATH_NO_TOP,
cache_subdir='models',
md5_hash='8804bcb37da5be4a52dc4e45d4425ba7')
md5_hash='55e62a6358af8a0af0eedf399b5aea99')
model.load_weights(weights_path)
weights_loaded = True
if (depth == 161) and (nb_dense_block == 4) and (growth_rate == 48) and (nb_filter == 96) and \
(bottleneck is True) and (reduction == 0.5) and (subsample_initial_block):
(bottleneck is True) and (reduction == 0.5) and (dropout_rate == 0.0) and (subsample_initial_block):
if include_top:
weights_path = get_file('DenseNet-BC-161-48.h5',
DENSENET_161_WEIGHTS_PATH,
@@ -256,12 +256,12 @@ def DenseNet(input_shape=None,
weights_path = get_file('DenseNet-BC-161-48-no-top.h5',
DENSENET_161_WEIGHTS_PATH_NO_TOP,
cache_subdir='models',
md5_hash='d38903b8732fe238c91dac7859271f26')
md5_hash='1a9476b79f6b7673acaa2769e6427b92')
model.load_weights(weights_path)
weights_loaded = True
if (depth == 169) and (nb_dense_block == 4) and (growth_rate == 32) and (nb_filter == 64) and \
(bottleneck is True) and (reduction == 0.5) and (subsample_initial_block):
(bottleneck is True) and (reduction == 0.5) and (dropout_rate == 0.0) and (subsample_initial_block):
if include_top:
weights_path = get_file('DenseNet-BC-169-32.h5',
DENSENET_169_WEIGHTS_PATH,
@@ -271,7 +271,7 @@ def DenseNet(input_shape=None,
weights_path = get_file('DenseNet-BC-169-32-no-top.h5',
DENSENET_169_WEIGHTS_PATH_NO_TOP,
cache_subdir='models',
md5_hash='a664d78a30ddd217dd38c0bb8d258461')
md5_hash='89c19e8276cfd10585d5fadc1df6859e')
model.load_weights(weights_path)
weights_loaded = True