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()