def fn():
ret = zmq_recv(self._endpoint, [x.dtype for x in self.inputs_desc])
if isinstance(ret, tf.Tensor):
ret = [ret]
assert len(ret) == len(self.inputs_desc)
for qv, v in zip(ret, self.inputs_desc):
qv.set_shape(v.shape)
return ret
def get_input_tensors(self):
from tensorpack.user_ops import zmq_recv
ret = zmq_recv(self._endpoint, [x.dtype for x in self.input_placehdrs])
if isinstance(ret, tf.Tensor):
ret = [ret]
assert len(ret) == len(self.input_placehdrs)
for qv, v in zip(ret, self.input_placehdrs):
qv.set_shape(v.get_shape())
return ret
def fn():
ret = zmq_recv(self._endpoint,
[x.dtype for x in self.input_placehdrs])
if isinstance(ret, tf.Tensor):
ret = [ret]
assert len(ret) == len(self.input_placehdrs)
for qv, v in zip(ret, self.input_placehdrs):
qv.set_shape(v.get_shape())
return ret
def recv():
sess = tf.InteractiveSession()
recv = zmq_recv(ENDPOINT, [tf.float32, tf.uint8])
print(recv)
for truth in DATA:
arr = sess.run(recv)
assert (arr[0] == truth[0]).all()
assert (arr[1] == truth[1]).all()
