不是呢，是别人原封不动抄我的啦...

等等看

可以自己简单转换一下

目前广州还没有研发部门

这个支持 https 吗？

请问为什么我这执行 train_model.py 的时候，会如下错误？我的 tensorflow 版本是 2.4.0，python3.8 环境

2020-12-18 17:54:06.073 | DEBUG    | stagesepx.classifier.base:__init__:297 - compress rate: None
2020-12-18 17:54:06.073 | DEBUG    | stagesepx.classifier.base:__init__:298 - target size: (600, 800)
2020-12-18 17:54:06.073 | DEBUG    | stagesepx.hook:__init__:13 - start initialing: CompressHook ...
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.hook:__init__:80 - compress rate: None
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.hook:__init__:81 - target size: (600, 800)
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.hook:__init__:13 - start initialing: GreyHook ...
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.classifier.base:add_hook:319 - add hook: CompressHook
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.classifier.base:add_hook:319 - add hook: GreyHook
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.classifier.keras:__init__:50 - score threshold: 0.0
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.classifier.keras:__init__:51 - data size: (200, 200)
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.classifier.keras:__init__:52 - nb train samples: 64
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.classifier.keras:__init__:53 - nb validation samples: 64
2020-12-18 17:54:06.074 | DEBUG    | stagesepx.classifier.keras:__init__:54 - epochs: 10
2020-12-18 17:54:06.075 | DEBUG    | stagesepx.classifier.keras:__init__:55 - batch size: 4
2020-12-18 17:54:06.075 | DEBUG    | stagesepx.classifier.keras:train:151 - no model can be used. build a new one.
2020-12-18 17:54:06.075 | INFO     | stagesepx.classifier.keras:create_model:99 - creating keras sequential model
2020-12-18 17:54:06.080939: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-12-18 17:54:06.081188: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-12-18 17:54:06.186 | INFO     | stagesepx.classifier.keras:create_model:129 - model created
Found 56 images belonging to 10 classes.
Found 21 images belonging to 10 classes.
2020-12-18 17:54:06.386301: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
Epoch 1/10
2020-12-18 17:54:07.361360: W tensorflow/core/framework/op_kernel.cc:1763] OP_REQUIRES failed at sparse_xent_op.cc:90 : Invalid argument: Received a label value of 9 which is outside the valid range of [0, 6).  Label values: 9 4 7 0
Traceback (most recent call last):
  File "/Users/aaa/Downloads/work_with_stagesepx-master/dynamic/train_model.py", line 13, in <module>
    cl.train(data_home)
  File "/usr/local/lib/python3.8/site-packages/stagesepx/classifier/keras.py", line 178, in train
    self._model.fit(
  File "/usr/local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1100, in fit
    tmp_logs = self.train_function(iterator)
  File "/usr/local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 828, in __call__
    result = self._call(*args, **kwds)
  File "/usr/local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 888, in _call
    return self._stateless_fn(*args, **kwds)
  File "/usr/local/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2942, in __call__
    return graph_function._call_flat(
  File "/usr/local/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 1918, in _call_flat
    return self._build_call_outputs(self._inference_function.call(
  File "/usr/local/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 555, in call
    outputs = execute.execute(
  File "/usr/local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py", line 59, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InvalidArgumentError:  Received a label value of 9 which is outside the valid range of [0, 6).  Label values: 9 4 7 0
   [[node sparse_categorical_crossentropy/SparseSoftmaxCrossEntropyWithLogits/SparseSoftmaxCrossEntropyWithLogits (defined at usr/local/lib/python3.8/site-packages/stagesepx/classifier/keras.py:178) ]] [Op:__inference_train_function_984]

Function call stack:
train_function

请问是否可以设置自定义的连接时间？在实际跑自动化过程中，经常需要强杀应用，再重新起起来，但是 perfdog 直接断掉了

我的是 Mac，目前还没解决

请问第三个 pause 是什么意思呢？

我是 Mac，放弃 Jenkins 了，改用 crontab 定时器搞了，网上也没有搜到解决方案

试过了，也不行，估计是因为我的是 Mac，打算放弃 Jenkins 了，改用 crontab 定时器进行处理，也能满足我的需求

大佬可以用 Jenkins 帮忙试试看？我的 demo 脚本也比较简单，然后我的 Execute Shell 配置的是/usr/local/Cellar/python/3.7.0/bin/python3 /Users/aaa/JenkinProjects/test.py 拜谢~

试了，Jenkins 执行还是无效

我的脚本用本地命令行跑是正常的，也能看到打开了浏览器，窗口也足够大。就是用 Jenkins 跑的时候，看不到有浏览器有打开，所以导致找不到元素就报错了。试用了一楼的代码依然是无效。我怀疑是 Jenkins 需要配置什么才能通过 chromedriver 调起 Chrome 浏览器

~ $ python3 -m weditor
listening on http://172.31.126.53:17310
[I 200410 21:38:57 web:2162] 304 GET / (::1) 11.53ms
[I 200410 21:38:57 web:2162] 304 GET /api/v1/version (::1) 0.71ms
[W 200410 21:39:00 connectionpool:662] Retrying (Retry(total=2, connect=3, read=None, redirect=None, status=None)) after connection broken by 'ProtocolError('Connection aborted.', RemoteDisconnected('Remote end closed connection without response'))': /version
[W 200410 21:39:01 connectionpool:662] Retrying (Retry(total=1, connect=3, read=None, redirect=None, status=None)) after connection broken by 'ProtocolError('Connection aborted.', RemoteDisconnected('Remote end closed connection without response'))': /version
[W 200410 21:39:03 connectionpool:662] Retrying (Retry(total=0, connect=3, read=None, redirect=None, status=None)) after connection broken by 'ProtocolError('Connection aborted.', RemoteDisconnected('Remote end closed connection without response'))': /version
[I 200410 21:39:03 init:129] uiautomator2 version: 2.4.3.dev8

连接 weditor 无法 connect 设备。有人遇到过这样的问题吗？一直无法解决...

应该是不可点，可以用两种方法：
1、看看上一级或者上上级的父元素，看看是不是可以点得到
2、获取该元素的中心坐标点，点坐标👈

获取控件的左上角坐标点 (x,y)，宽高 (width,height)，然后计算三个 tab 的大致坐标点
买入：((x+1/4*width), (y+1/2*height)
卖出：((x+2/4*width), (y+1/2*height)
仓位：((x+3/4*width), (y+1/2*height)
最后用 adb shell input tap (x+1/4*width) (y+1/2*height) 去点

图片为什么这么糊？请问有没有清晰一点的呢？

噗，尴尬了，怎么办？

Jmeter 用的是线程，gatling 用的是协程，所以 jmeter 的单机并发数比 gatling 要低，加上 gatling 代码控制比较方便，而 jmeter 相对比较适合不用代码操作的童鞋，我是不太喜欢操作界面

看看生成的 reports 目录下是否有像我截图那样的 data、widgets、app.js、style.css 等文件？

支持，我就用的 Chrome

学习了

并不能这样，因为你的 data 是 json 结构，不是纯 dict，是无法请求成功的

如果是这种 form data，就用 data 就行，也可以看 content-type，再决定用哪个