def builder(inputs=None):
return models.dense_classifier(builder_dims,
inputs=inputs,
act_fn=activation_func,
optimizer=builder_opt,
epoch=True)
builder_opt = tf.train.AdagradOptimizer(learning_rate)
builder_dims = [784, 100, 10]
# ------------------------------------------------------------------------- #
# Dataset instantiation
dataset = datasets.load_mnist()
train_set = dataset.cut(0, 50000, 50000).shuffle().cut(0, 50000, batch_size)
test_set = dataset.cut(50000, 60000, 10000)
# Model instantiation
graph = tf.Graph()
with graph.as_default():
model = models.dense_classifier(builder_dims,
inputs=None,
act_fn=activation_func,
optimizer=builder_opt,
epoch=True)
# Establish connections with workers
sockets = []
for worker_HOST in worker_HOSTS:
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect(worker_HOST)
sockets.append(s)
# Testing + Training
with graph.as_default():
sess = tf.Session(graph=graph)
with sess.as_default():