Commit 087af16e authored by Yuxin Wu's avatar Yuxin Wu

fc with different init

parent a98f005a
......@@ -60,15 +60,12 @@ class Model(ModelDesc):
l = BatchNorm('bn3', l, is_training)
l = tf.nn.relu(l)
l = FullyConnected('fc0', l, 512,
W_init=tf.truncated_normal_initializer(stddev=0.04),
b_init=tf.constant_initializer(0.1))
l = FullyConnected('fc1', l, out_dim=512,
W_init=tf.truncated_normal_initializer(stddev=0.04),
b_init=tf.constant_initializer(0.1))
# fc will have activation summary by default. disable for the output layer
logits = FullyConnected('linear', l, out_dim=10, summary_activation=False,
nl=tf.identity,
W_init=tf.truncated_normal_initializer(stddev=1.0/192))
nl=tf.identity)
prob = tf.nn.softmax(logits, name='output')
y = one_hot(label, 10)
......@@ -134,7 +131,7 @@ def get_config():
dataset=dataset_train,
optimizer=tf.train.AdamOptimizer(lr),
callbacks=Callbacks([
SummaryWriter(print_tag=['train_cost', 'train_error']),
SummaryWriter(),
PeriodicSaver(),
ValidationError(dataset_test, prefix='test'),
]),
......
......@@ -20,7 +20,7 @@ from tensorpack.dataflow import *
"""
MNIST ConvNet example.
99.33% test accuracy after 50 epochs.
99.3% validation accuracy after 50 epochs.
"""
BATCH_SIZE = 128
......
......@@ -17,8 +17,8 @@ def FullyConnected(x, out_dim, W_init=None, b_init=None, nl=tf.nn.relu):
in_dim = x.get_shape().as_list()[1]
if W_init is None:
W_init = tf.truncated_normal_initializer(stddev=1 / math.sqrt(float(in_dim)))
#W_init = tf.uniform_unit_scaling_initializer()
#W_init = tf.truncated_normal_initializer(stddev=1 / math.sqrt(float(in_dim)))
W_init = tf.uniform_unit_scaling_initializer()
if b_init is None:
b_init = tf.constant_initializer(0.0)
......
......@@ -4,7 +4,7 @@
# Author: Yuxin Wu <ppwwyyxx@gmail.com>
# use user-space protobuf
#import sys, os
#site = os.path.join(os.environ['HOME'],
#'.local/lib/python2.7/site-packages')
#sys.path.insert(0, site)
import sys, os
site = os.path.join(os.environ['HOME'],
'.local/lib/python2.7/site-packages')
sys.path.insert(0, site)
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