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higher capacity model from run 38

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matpalm committed Jun 5, 2019
1 parent 620d42e commit 6ab76fc6813334421b051222c020cc620e02b8ee
Showing with 7 additions and 5 deletions.
  1. +1 −1 debug_calc_embedding_near_neighbours.sh
  2. +6 −3 model.py
  3. +0 −1 stitch.py
@@ -53,7 +53,7 @@ join /tmp/source_target_[ab].nns > runs/$1/source_target_joined.ssv
exit

# stitch images
./stitch.py < source_target_joined.ssv > stitch.out
./stitch.py < runs/$1/source_target_joined.ssv

# make a gif
convert stitch*png runs/$1/near_neighbour_egs.gif
@@ -53,12 +53,15 @@ def construct_model(embedding_dim, initial_model=None, learning_rate=None, margi

conv = Conv2D(filters=16, kernel_size=5, strides=2, padding='same', activation='elu')(inputs)
conv = Conv2D(filters=32, kernel_size=3, strides=2, padding='same', activation='elu')(conv)
conv = Conv2D(filters=32, kernel_size=3, strides=2, padding='same', activation='elu')(conv)
conv = Conv2D(filters=32, kernel_size=3, strides=2, padding='same', activation='elu')(conv)
conv = Conv2D(filters=64, kernel_size=3, strides=2, padding='same', activation='elu')(conv)
conv = Conv2D(filters=128, kernel_size=3, strides=2, padding='same', activation='elu')(conv)
conv = Conv2D(filters=128, kernel_size=1, strides=1, padding='same', activation='elu')(conv)
conv = Conv2D(filters=256, kernel_size=3, strides=2, padding='same', activation='elu')(conv)
conv = Conv2D(filters=256, kernel_size=1, strides=1, padding='same', activation='elu')(conv)

mlp = Flatten()(conv)
mlp = Dropout(rate=0.5)(mlp)
mlp = Dense(units=64, activation='elu')(mlp)
mlp = Dense(units=128, activation='elu')(mlp)

embeddings = Dense(units=embedding_dim, activation=None, name='embedding')(mlp)
embeddings = NormaliseLayer()(embeddings)
@@ -10,7 +10,6 @@
collage = None
for i, line in enumerate(sys.stdin):
cols = line.strip().split(" ")
print("/t".join(cols))
if N is None:
N = len(cols)
else:

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