input的值是什么意思呀，大佬，还有个问题，怎么历史数据不会更新点着没用

问题一
缺少这个方法，
get_exl_data_v2

问题二：
Traceback (most recent call last):
File "ssq4all.py", line 121, in
tf.compat.v1.app.run()
raise ValueError(
ValueError: Cannot feed value of shape (2656, 1, 7, 1) for Tensor 'Placeholder:0', which has shape '(2656, 1, 13, 1)'

AttributeError: module 'tensorflow' has no attribute 'app'

训练完了，怎么预测。
谢谢

NameError: name 'get_exl_data_v2' is not defined

谁中过奖的，都在这里填一下中奖的时间和金额吧！
让新来的友友们 羡慕一下呢？

最近也想弄个类似的功能，想学习学习思路

python ssq.py
Traceback (most recent call last):
File "ssq.py", line 24, in
from poems.model import rnn_model
ImportError: No module named model
想問一下這個錯誤怎麼解決？謝謝

训练到Epoch 149999 会停止，但是保存的进度为145000。请问下是不是有BUG

如题。。报错

使用python的版本是什么，我这边import tensorflow as tf提示ImportError: DLL load failed: 动态链接库(DLL)初始化例程失败。

花两块钱买一注双色球彩票，想要中一等奖的概率是17721088 分之一，它是个随机的结果，有这么多的变量，无法预测。

哥们别浪费时间做这个项目。

考上清华和中500万彩票哪个更难？李永乐老师讲解正态分布的应用（2018最新）

Traceback (most recent call last):
File "ssq4all_v4.py", line 13, in
import win_unicode_console
ModuleNotFoundError: No module named 'win_unicode_console'
想問一下這個錯誤怎麼解決？謝謝
"ssq4all_v4.py"这个是windows运行还是ubuntu下运行呢?

大佬,tf2分支,我没办法使用GPU训练, 只能使用效率低的CPU训练, 好不容易训练了5000次了, ctrl+c取消训练后, 没有保存结果, 我再次训练的时候,还是从第一次开始训练

跑ssq4all.py没问题，跑dlt4all.py出错如下：
Traceback (most recent call last):
File "C:\ssq\dlt\dlt4all.py", line 126, in
tf.compat.v1.app.run()
File "C:\Program Files\Python39\lib\site-packages\tensorflow\python\platform\app.py", line 36, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "C:\Program Files\Python39\lib\site-packages\absl\app.py", line 312, in run
_run_main(main, args)
File "C:\Program Files\Python39\lib\site-packages\absl\app.py", line 258, in _run_main
sys.exit(main(argv))
File "C:\ssq\dlt\dlt4all.py", line 122, in main
run_training()
File "C:\ssq\dlt\dlt4all.py", line 59, in run_training
input_data = tf.compat.v1.placeholder(tf.float32, [FLAGS.batch_size, 1,7,1])
File "C:\Program Files\Python39\lib\site-packages\tensorflow\python\ops\array_ops.py", line 3298, in placeholder
raise RuntimeError("tf.placeholder() is not compatible with "
RuntimeError: tf.placeholder() is not compatible with eager execution.

用的是ty2分支，python3.9

我的电脑配置很好，已经训练一天了，还是这样子？

第一轮训练就一直卡在那边

ssq_data.py里的get_exl_data方法用来获取数据，想问下红色球的数字都减了1，蓝色球的数字加了32，这样是有什么特殊作用吗？

这个方法没有，是不是漏了

D:\python\Anaconda3\python.exe D:/ProgramData/ssq-master/dlt4all.py
2019-10-31 15:03:33.152776: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
2019-10-31 15:03:33.152776: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
2019-10-31 15:03:33.152776: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2019-10-31 15:03:33.152776: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2019-10-31 15:03:33.155276: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.

restore from the checkpoint D:\ProgramData\ssq-master\dlt_model\poems-0

start training...

2019-10-31 15:03:38.997865: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:1158] Invalid argument: stride must be less than or equal to kernel size
WARNING:tensorflow:Error encountered when serializing LAYER_NAME_UIDS.
Type is unsupported, or the types of the items don't match field type in CollectionDef.
'dict' object has no attribute 'name'

Last epoch were saved, next time will start from epoch 0.

Traceback (most recent call last):
File "D:\python\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1139, in _do_call
return fn(*args)
File "D:\python\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1121, in _run_fn
status, run_metadata)
File "D:\python\Anaconda3\lib\contextlib.py", line 66, in exit
next(self.gen)
File "D:\python\Anaconda3\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 466, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: stride must be less than or equal to kernel size
[[Node: gradients/conv3_0/AvgPool_grad/AvgPoolGrad = AvgPoolGrad[T=DT_FLOAT, data_format="NHWC", ksize=[1, 1, 1, 1], padding="VALID", strides=[1, 2, 2, 1], _device="/job:localhost/replica:0/task:0/cpu:0"](gradients/conv3_0/AvgPool_grad/Shape, gradients/conv3_0/Pad_grad/Slice_1)]]

F:\GitHub\ssq\venv\Scripts\python.exe "D:\Program Files\JetBrains\PyCharm 2020.1\plugins\python\helpers\pydev\pydevconsole.py" --mode=client --port=2435
import sys; print('Python %s on %s' % (sys.version, sys.platform))
sys.path.extend(['F:\GitHub\ssq', 'F:/GitHub/ssq'])
PyDev console: starting.
Python 3.7.7 (tags/v3.7.7:d7c567b08f, Mar 10 2020, 10:41:24) [MSC v.1900 64 bit (AMD64)] on win32

runfile('F:/GitHub/ssq/ssq4all_v4.py', wdir='F:/GitHub/ssq')
2021-05-15 15:22:44.122567: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
WARNING:tensorflow:From F:\GitHub\ssq\poems\resnet.py:69: calling Constant.init (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
W0515 15:22:48.327268 3008 deprecation.py:537] From F:\GitHub\ssq\poems\resnet.py:69: calling Constant.init (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
2021-05-15 15:22:48.348672: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-05-15 15:22:48.357103: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-05-15 15:22:48.432472: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:04:00.0 name: GeForce GTX 760 computeCapability: 3.0
coreClock: 1.0975GHz coreCount: 6 deviceMemorySize: 2.00GiB deviceMemoryBandwidth: 179.05GiB/s
2021-05-15 15:22:48.432961: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-05-15 15:22:48.525946: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-05-15 15:22:48.526119: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-05-15 15:22:48.568220: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-05-15 15:22:48.579939: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-05-15 15:22:48.584193: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
2021-05-15 15:22:48.611621: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-05-15 15:22:48.617375: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-05-15 15:22:48.617576: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
F:\GitHub\ssq\venv\lib\site-packages\tensorflow\python\keras\layers\legacy_rnn\rnn_cell_impl.py:702: UserWarning: tf.nn.rnn_cell.BasicLSTMCell is deprecated and will be removed in a future version. This class is equivalent as tf.keras.layers.LSTMCell, and will be replaced by that in Tensorflow 2.0.
warnings.warn("tf.nn.rnn_cell.BasicLSTMCell is deprecated and will be "
WARNING:tensorflow:tf.nn.rnn_cell.MultiRNNCell is deprecated. This class is equivalent as tf.keras.layers.StackedRNNCells, and will be replaced by that in Tensorflow 2.0.
W0515 15:22:48.860270 3008 rnn_cell_impl.py:1242] tf.nn.rnn_cell.MultiRNNCell is deprecated. This class is equivalent as tf.keras.layers.StackedRNNCells, and will be replaced by that in Tensorflow 2.0.
WARNING:tensorflow:At least two cells provided to MultiRNNCell are the same object and will share weights.
W0515 15:22:48.860270 3008 rnn_cell_impl.py:1254] At least two cells provided to MultiRNNCell are the same object and will share weights.
WARNING:tensorflow:From F:\GitHub\ssq\poems\model.py:93: dynamic_rnn (from tensorflow.python.ops.rnn) is deprecated and will be removed in a future version.
Instructions for updating:
Please use keras.layers.RNN(cell), which is equivalent to this API
W0515 15:22:48.942326 3008 deprecation.py:339] From F:\GitHub\ssq\poems\model.py:93: dynamic_rnn (from tensorflow.python.ops.rnn) is deprecated and will be removed in a future version.
Instructions for updating:
Please use keras.layers.RNN(cell), which is equivalent to this API
F:\GitHub\ssq\venv\lib\site-packages\tensorflow\python\keras\engine\base_layer_v1.py:1727: UserWarning: layer.add_variable is deprecated and will be removed in a future version. Please use layer.add_weight method instead.
warnings.warn('layer.add_variable is deprecated and '
WARNING:tensorflow:From F:\GitHub\ssq\venv\lib\site-packages\tensorflow\python\keras\layers\legacy_rnn\rnn_cell_impl.py:753: calling Zeros.init (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
W0515 15:22:48.992315 3008 deprecation.py:537] From F:\GitHub\ssq\venv\lib\site-packages\tensorflow\python\keras\layers\legacy_rnn\rnn_cell_impl.py:753: calling Zeros.init (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
2021-05-15 15:22:50.472322: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-05-15 15:22:50.472797: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]
2021-05-15 15:22:50.473007: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-05-15 15:22:50.508668: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:196] None of the MLIR optimization passes are enabled (registered 0 passes)

start training...

till 100000

Hello, I am a learner!
I found that It is useless when I clicked the 'auto update' button. Please tell me why I cannot update data?

1.训练17721088次后，验证上上一次开奖结果应该得到上一次的开奖结果。电脑配置不行，还没跑完。有谁跑完可以分享一下模型文件
2.（假设开奖结果受到干预）当第T期模型结果和实际开奖结果不一样的时候，应该让它按照实际结果运行一下。就是按照第t期开奖结果重新跑，历史开奖记录都跑一篇
3.（假设开奖结果完全随机）不应该按照开奖顺序跑，应该按照红球从小打大排列的结果跑。按照开奖顺序，则第一个球的概率是三十三分之一。按照从小到大的第一个球的概率是下一个球数减一分之一。这样可以较少运算次数和提高准确率

昨天晚上执行了模型，执行ssq。发现预测的球有重复，是不是哪里算法。。。我还在学习这个机器学习。所以只能反馈

input: [[ 1 4 10 12 30 32 14]]
output:[14 8 7 26 8 8 10]

你好，我是在epochs跑到35w左右的时候，相差一千多epochs，预测结果完全不一样，这个正常吗？此时的loss在0.2左右

安装版本tf_nightly_gpu-2.5.0. ,cuda 11.1,第一部执行了ssq4all_test_v4.py进行训练，训练到十万的时候手动中断，执行ssq4all_test_v4.py，但是在## loading model from ./model4all_v4/ 之后回到界面
中间自行更改了os.environ["CUDA_VISIBLE_DEVICES"] = "0"跟model_dir = './model4all_v4/'
请教大佬是啥原因

怎么使用GPU

跑的速度比较慢。
WIN10 。 TensorFlow 2.8 。 python 3.10