def read_cmd():
cmd = deepwater_pb2.Cmd()
size_bytes = sys.stdin.buffer.read(4)
if len(size_bytes) == 0:
return None
size = struct.unpack('>I', size_bytes)[0]
data = sys.stdin.buffer.read(size)
cmd.ParseFromString(data)
if debug:
print('Received', size, file=sys.stderr)
return cmd
#!/usr/bin/env python3
import numpy as np
import backend
import deepwater_pb2
backend.size = 1
backend.gpus = []
res = deepwater_pb2.Cmd()
sizes = [784, 1024, 1024, 512, 10]
types = ['data', 'relu', 'relu', 'relu', 'loss']
drops = [.8, .5, .5, .5, 0]
create = deepwater_pb2.Cmd()
create.type = deepwater_pb2.Create
create.input_shape.extend([64, 1, 1, sizes[0]])
create.solver_type = 'SGD'
create.sizes.extend(sizes)
create.types.extend(types)
create.dropout_ratios.extend(drops)
create.learning_rate = .01
create.momentum = .9
backend.message(create, res)
for i in range(2):
train = deepwater_pb2.Cmd()
train.type = deepwater_pb2.Train
train.input_shape.extend(create.input_shape)
batch = np.zeros(train.input_shape, dtype=np.float32)
#!/usr/bin/env python3
from multiprocessing import *
from solver import *
import numpy as np
import deepwater_pb2
cmd = deepwater_pb2.Cmd()
cmd.type = deepwater_pb2.Create
cmd.graph = 'lenet'
cmd.input_shape.extend([128, 1, 28, 28])
cmd.solver_type = 'SGD'
cmd.learning_rate = .01
cmd.momentum = .9
size = 1
uid = None
gpus = []
pool = Pool(size, initializer=create, initargs=(cmd, uid, size, gpus))
pool.map(start, range(size))
for i in range(2):
batch = np.zeros(cmd.input_shape, dtype=np.float32)
label = np.zeros([cmd.input_shape[0], 1], dtype=np.float32)
if i % 10 == 0:
print('map', (batch.shape, label.shape), file=sys.stderr)
tmp = zip(np.split(batch, size), np.split(label, size))
if i % 10 == 0:
batch = np.frombuffer(req.data[0], dtype=np.float32)
batch = batch.reshape(req.input_shape)
data = np.split(batch, size)
data = pool.map(predict, data)
data = np.concatenate(data)
res.data.append(data.tobytes())
res.type = deepwater_pb2.Success
if req.type == deepwater_pb2.SaveGraph:
print('Saving graph to', req.path, file=sys.stderr)
pool.map(save_graph, [req.path])
if req.type == deepwater_pb2.Save:
print('Saving model to', req.path, file=sys.stderr)
pool.map(save, [req.path])
if req.type == deepwater_pb2.Load:
print('Loading model to', req.path, file=sys.stderr)
pool.map(load, [req.path])
if __name__ == '__main__':
print('Started Caffe backend', file=sys.stderr)
while True:
req = read_cmd()
if req is None:
break
res = deepwater_pb2.Cmd()
message(req, res)
write_cmd(res)