d_reduced_literal = cuda.to_device(numpy.array(reduced_literal)) d_compact_flag = cuda.to_device(compact_flag)#print fill_wordgetIdx_gpu[1, tpb](d_fill_word, d_reduced_literal, d_index, d_compact_flag, reduced_length) compact_flag = d_compact_flag.copy_to_host()#print compact_flag...
# 需要导入模块: from numba import cuda [as 别名]# 或者: from numba.cuda importto_device[as 别名]defuniform(size, dtype=np.float, device=False):'''Generate floating point random number sampled from a uniform distribution :param size: Number of samples. :param dtype: np.float32 or np.flo...
1、目前主流方法:.to(device)方法 (推荐) import torch import time #1.通常用法 device = torch.device("cuda" if torch.cuda.is_available() else "cpu") data = data.to(device) model = model.to(device) ''' 1.先创建device对象 2.to函数指定数据或者模型放到哪里 ''' #2.将构建的tensor或者模...
dev_id = device['ip'] return_data = {} net_connect = ConnectHandler(**device) output = net_connect.send_command("show run") return_data[dev_id] = outputprint("Adding the result to the multiprocess queue") mp_queue.put(return_data) mp_queue = multiprocessing.Queue() processes = []...
How to send cloud-to-device messages from a back-end app and receive them on a device app using the Azure IoT SDKs for Python.
def test(args, model, device, test_loader): model.eval() test_loss = 0 correct = 0 with torch.no_grad(): for data, target in test_loader: data, target = data.to(device), target.to(device) output = model(data) test_loss += F.nll_loss(output, target, size_average=False).item...
def rotate_device(self) -> bytes: 1. 2. totate_device方法是ControlSender类的实例方法用于旋转Android设备的屏幕。 def totate_screen(self): self.server.control.totate_device() 1. 2. swipe方法 def swipe( self, start_x: int, start_y: int, ...
to_dict(orient='list') buildid = df3["ID"][0] sql_1 = """select * from t_device_info where buildid = '{0}'""".format( buildid) # #查询获取数据-设备配置表 df2 = pd.read_sql_query(sql_1, engine) #df4:设备配置信息 df4 = pd.DataFrame(df2,columns=["BUILDID","NAME","...
importsocketclassMyDevice(object):def__init__(self,ip,port=4011):self.ip=ipself.port=portself.socket=Noneself.sent=0defconnect(self,timeout=1.0):""" Connects to device, throws exception if can't connect """ifself.socket:self.socket.close()self.socket=socket.socket(socket.AF_INET,socket...
prefetch_to_device("/cpu:0")) >>> for element in dataset: ... print(f'Tensor {element} is on device {element.device}') Tensor 1 is on device /job:localhost/replica:0/task:0/device:CPU:0 Tensor 2 is on device /job:localhost/replica:0/task:0/device:CPU:0 Tensor 3 is on ...