def alexnet_train_job():
(labels, images) = _data_load_layer(args, args.train_dir)
loss = alexnet(args, images, labels)
flow.optimizer.SGD(flow.optimizer.PiecewiseConstantScheduler(
[], [0.00001]),
momentum=0).minimize(loss)
return flow.pack(loss, args.num_piece_in_batch)
def alexnet_eval_job():
with flow.scope.consistent_view():
(labels, images) = _data_load_layer(args, args.eval_dir)
loss = alexnet(args, images, labels)
return flow.pack(loss, args.num_piece_in_batch)
def UnpackPackJob(a: oft.Numpy.Placeholder((3, 4))):
return flow.pack(flow.unpack(a, 3), 3)
def alexnet_train_job():
(labels, images) = _data_load_layer(args, args.train_dir)
loss = alexnet(args, images, labels)
flow.losses.add_loss(loss)
return flow.pack(loss, args.num_piece_in_batch)