Traceback (most recent call last):
File "D:/CODE/project/tensorflow/seq2seq-couplet/couplet.py", line 13, in
restore_model=False)
File "D:\CODE\project\tensorflow\seq2seq-couplet\model.py", line 33, in init
train_target_file, vocab_file, batch_size)
File "D:\CODE\project\tensorflow\seq2seq-couplet\reader.py", line 50, in init
self.vocabs = read_vocab(vocab_file)
File "D:\CODE\project\tensorflow\seq2seq-couplet\reader.py", line 33, in read_vocab
f = open(vocab_file, 'rb')
FileNotFoundError: [Errno 2] No such file or directory: '/data/dl-data/couplet/vocabs'

上联： 蔡徐坤鸡你太美

如图。如果选择忽略并打开网页话请求也会因为证书过期无法加载。

请问我们这工程用的tensorflow版本是多少呀？我现在用的是tensorflow 1.11.0的版本，但运行couplet.py训练模型的过程中出现如下错误：

"D:\Program Files\Anaconda3\python.exe" K:/other_proj/seq2seq-couplet-master/couplet.py
D:\Program Files\Anaconda3\lib\site-packages\h5py_init_.py:34: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
from ._conv import register_converters as _register_converters
WARNING:tensorflow:From K:\other_proj\seq2seq-couplet-master\seq2seq.py:12: BasicLSTMCell.init (from tensorflow.python.ops.rnn_cell_impl) is deprecated and will be removed in a future version.
Instructions for updating:
This class is deprecated, please use tf.nn.rnn_cell.LSTMCell, which supports all the feature this cell currently has. Please replace the existing code with tf.nn.rnn_cell.LSTMCell(name='basic_lstm_cell').
2019-01-21 10:06:30.391998: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
Reloading model file before training.
Saving model. Step: 0, loss: 0.956932

src: 龙 湾 子 携 龙 坨 女 ， 龙 舟 赛 上 龙 腾 虎 跃
output: ， ，
target: 马 王 爷 带 马 云 孙 ， 马 街 书 会 马 壮 人 强

src:天 涯 寻 醉 客
output:
target: 海 角 觅 诗 行

src:凡 却 非 凡 ， 半 坡 烟 雨 国 风 里
output: ，
target: 了 而 未 了 ， 一 卷 文 心 吾 爱 中

src:分 牝 牡
output:
target: 辨 雄 雌

src:春 绿 千 村 ， 碧 江 共 旗 山 一 色
output: ，
target: 政 兴 百 业 ， 红 木 与 牛 仔 双 名

src:溪 头 几 串 童 年 梦
output:
target: 心 底 一 支 岁 月 歌

src:不 欲 干 鞋 沾 湿 水
output:
target: 何 妨 赤 脚 濯 清 流
Evaluate model. Step: 0, score: 0.000000, loss: 0.956932
2019-01-21 10:12:55.659938: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:56.320540: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:56.545342: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:56.794942: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:57.013343: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:57.233946: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:57.498948: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:57.717348: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:57.966949: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:58.214553: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:58.428354: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:58.678955: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:58.881755: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:59.141356: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:59.357157: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:59.591158: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:12:59.809558: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:00.027959: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:00.269563: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:00.524771: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:00.743172: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:00.977172: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:01.214173: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:01.448376: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:01.666776: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:01.885177: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
2019-01-21 10:13:02.119177: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at variable_ops.cc:104 : Already exists: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
Traceback (most recent call last):
File "D:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1292, in _do_call
return fn(*args)
File "D:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1277, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "D:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1367, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.AlreadyExistsError: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
[[{{node gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var}} = TemporaryVariabledtype=DT_FLOAT, shape=[1024], var_name="gradients/...dd/tmp_var", _device="/job:localhost/replica:0/task:0/device:CPU:0"]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "K:/other_proj/seq2seq-couplet-master/couplet.py", line 15, in
m.train(50000)
File "K:\other_proj\seq2seq-couplet-master\model.py", line 135, in train
self.train_target_seq_len: target_seq_len})
File "D:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 887, in run
run_metadata_ptr)
File "D:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1110, in _run
feed_dict_tensor, options, run_metadata)
File "D:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1286, in _do_run
run_metadata)
File "D:\Program Files\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1308, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.AlreadyExistsError: Resource __per_step_136/gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var/struct tensorflow::TemporaryVariableOp::TmpVar
[[{{node gradients/decoder/while/BasicDecoderStep/decoder/attention_wrapper/bahdanau_attention/mul/Enter_1_grad/ArithmeticOptimizer/AddOpsRewrite_Add/tmp_var}} = TemporaryVariabledtype=DT_FLOAT, shape=[1024], var_name="gradients/...dd/tmp_var", _device="/job:localhost/replica:0/task:0/device:CPU:0"]]

Process finished with exit code 1

上联: 包子包食饱
对的: 花生子女香

上联: 深水潭 冷冰寒
对的: 古松石 古柏枯

革命尚未成功, 小AI尚需努力~

for layer_id in range(bi_layer_size):
encoder_state.append(bi_encoder_state[0][layer_id])
encoder_state.append(bi_encoder_state[1][layer_id])
encoder_state = tuple(encoder_state)

and i do not know why we should change the order of encoder_state? And i think the attention model just use the last output about encoder.

大神666

InvalidArgumentError (see above for traceback): Found Inf or NaN global norm. : Tensor had Inf values
[[node VerifyFinite/CheckNumerics (defined at C:\Users\xxx\seq2seq-couplet-master1\model.py:79) = CheckNumericsT=DT_FLOAT, message="Found Inf or NaN global norm.", _device="/job:localhost/replica:0/task:0/device:GPU:0"]]

上联：我对钱不感兴趣，下联竟是：你和气生财生财
完全对不上啊

2018-04-12 15:19:39.686884: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2018-04-12 15:19:39.763650: W tensorflow/core/framework/op_kernel.cc:1273] OP_REQUIRES failed at save_restore_tensor.cc:170 : Not found: Unsuccessful TensorSliceReader constructor: Failed to find any matching files for /Users/info_kerwin/Desktop/seq2seq/data/dl-data/models/tf-lib/output_couplet_prod/model.ckpl

couplet.py训练完后的数据是四个：model.ckpl.data-00000-of-00001、model.ckpl.index、model.ckpl.meta、checkpoint，运行server.py是如何产生model.ckpl文件的？

Tensorflow版本是多少

上联： 一点青山 二分秋水 藏不住 三里桃花

上联：水映青山山映水

Why the loss when I train the net? I use the set of download.

作者您好，我并没有在程序页面看到能够选择哪块GPU的选项啊，求问如何做到选择第几块GPU来训练呢？

上联：
李云龙平安夜打平安县城
下联：
花莲喷水池水喷莲花莲湖

还需努力学习

兄弟，你看看“百万坦克上广场”下一句是什么，祝好

今天偶然间知乎推送了这个项目，打开看了下真有意思。试了一下这个对联的接口，发现主页面还是nginx的欢迎界面，哈哈！

深度学习模型怎么跑在后端提供接口

有点好奇深度学习跑出来的模型，怎么运行产生后端接口来访问？是怎么的一套流程呢？老哥有空的时候方便说下？

想借你的接口用在自己的应用

我想在自己的小项目网站加上这个对对联的功能，不会有多少访问量，纯属自娱自乐。
要是兄弟你觉得不行，跟我说下我随时撤掉。
最后膜拜大佬！

'gbk' codec can't decode byte 0x9a in position 2: illegal multibyte sequence

我跑数据集跑了一下午，现在到了step：86600，loss：34.250666
有什么结束标志嘛==

试试：“一生只爱孙笑川”

E5-2620 24核，没有gpu，已经一个月多了，才训练到
Saving model. Step: 520900, loss: 27.184117。
求训练好的模型，谢谢

才down下来的代码，加载库的时候， TensorFlow 的contrib 和 python.layers都me的了，有大神教教怎么解决么

在demo里，有几个词语都被对成了“开发区”
目前我看到的有：
好运气
运动会
大新闻

这是不是一个bug的征兆？

上联：
坝长千尺难防民口，墙高万丈莫拦人心
下联：
钱通万件不通法眼，量大千秋牢记公平

能否提供下已经下载好的数据集，感谢

上联：
一枕松风声更幽
下联：
半窗竹影韵尤幽
下联：
一枕松风声更幽
下联：
半窗竹影韵尤幽
（无限循环）

感觉这个损失函数是不是有点问题啊，tf.reduce_sum(cost) / tf.to_float(batch_size)，分子是cost的和，分母怎么会是batchsize?不应该是tf.reduce_sum(loss_mask)么？

跪求解答...

能提供最新的数据吗？谢谢！[email protected]

作者吃点好的

不小心贴了一句繁体字，然后发现行为很迷啊。

1. 學士衣冠無彩色 -> 文章黼黻芳名
2. 學士衣冠无彩色 -> 人面壁有光辉
3. 学士衣冠無彩色 -> 先生仪表聿元辉
4. 学士衣冠无彩色 -> 英雄肝胆有余香

Traceback (most recent call last):
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1322, in _do_call
return fn(*args)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1307, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1409, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[32,4096] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/concat, bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/MatMul/Enter)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

 [[Node: decoder/while/BasicDecoderStep/decoder/attention_wrapper/assert_equal/All/_129 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_862_d..._equal/All", tensor_type=DT_BOOL, _device="/job:localhost/replica:0/task:0/device:CPU:0"](^_cloopdecoder/while/BasicDecoderStep/decoder/attention_wrapper/assert_equal/Assert/Assert/data_0/_5)]]

Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "D:/CODE/project/tensorflow/seq2seq-couplet/couplet.py", line 15, in
m.train(5000000)
File "D:\CODE\project\tensorflow\seq2seq-couplet\model.py", line 149, in train
self.train_target_seq_len: target_seq_len})
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 900, in run
run_metadata_ptr)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1135, in _run
feed_dict_tensor, options, run_metadata)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1316, in _do_run
run_metadata)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 1335, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[32,4096] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/concat, bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/MatMul/Enter)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

 [[Node: decoder/while/BasicDecoderStep/decoder/attention_wrapper/assert_equal/All/_129 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_862_d..._equal/All", tensor_type=DT_BOOL, _device="/job:localhost/replica:0/task:0/device:CPU:0"](^_cloopdecoder/while/BasicDecoderStep/decoder/attention_wrapper/assert_equal/Assert/Assert/data_0/_5)]]

Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

Caused by op 'bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/MatMul', defined at:
File "D:/CODE/project/tensorflow/seq2seq-couplet/couplet.py", line 13, in
restore_model=False)
File "D:\CODE\project\tensorflow\seq2seq-couplet\model.py", line 45, in init
self._init_train()
File "D:\CODE\project\tensorflow\seq2seq-couplet\model.py", line 72, in _init_train
self.num_units, self.layers, self.dropout)
File "D:\CODE\project\tensorflow\seq2seq-couplet\seq2seq.py", line 129, in seq2seq
num_units, layers, input_keep_prob)
File "D:\CODE\project\tensorflow\seq2seq-couplet\seq2seq.py", line 26, in bi_encoder
time_major = False)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn.py", line 403, in bidirectional_dynamic_rnn
time_major=time_major, scope=fw_scope)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn.py", line 618, in dynamic_rnn
dtype=dtype)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn.py", line 815, in _dynamic_rnn_loop
swap_memory=swap_memory)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 3209, in while_loop
result = loop_context.BuildLoop(cond, body, loop_vars, shape_invariants)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 2941, in BuildLoop
pred, body, original_loop_vars, loop_vars, shape_invariants)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 2878, in _BuildLoop
body_result = body(*packed_vars_for_body)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 3179, in
body = lambda i, lv: (i + 1, orig_body(*lv))
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn.py", line 784, in _time_step
skip_conditionals=True)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn.py", line 239, in _rnn_step
new_output, new_state = call_cell()
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn.py", line 772, in
call_cell = lambda: cell(input_t, state)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 232, in call
return super(RNNCell, self).call(inputs, state)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\layers\base.py", line 329, in call
outputs = super(Layer, self).call(inputs, *args, **kwargs)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 703, in call
outputs = self.call(inputs, *args, **kwargs)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 1325, in call
cur_inp, new_state = cell(cur_inp, cur_state)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 1126, in call
output, new_state = self._cell(inputs, state, scope=scope)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 339, in call
*args, **kwargs)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\layers\base.py", line 329, in call
outputs = super(Layer, self).call(inputs, *args, **kwargs)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 703, in call
outputs = self.call(inputs, *args, **kwargs)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 638, in call
array_ops.concat([inputs, h], 1), self._kernel)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\math_ops.py", line 2014, in matmul
a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 4567, in mat_mul
name=name)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 3414, in create_op
op_def=op_def)
File "C:\Users\47263\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1740, in init
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access

ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[32,4096] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/concat, bidirectional_rnn/fw/fw/while/fw/multi_rnn_cell/cell_1/basic_lstm_cell/MatMul/Enter)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

 [[Node: decoder/while/BasicDecoderStep/decoder/attention_wrapper/assert_equal/All/_129 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_862_d..._equal/All", tensor_type=DT_BOOL, _device="/job:localhost/replica:0/task:0/device:CPU:0"](^_cloopdecoder/while/BasicDecoderStep/decoder/attention_wrapper/assert_equal/Assert/Assert/data_0/_5)]]

Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

In the README.md
Line 30, Column 29
Nivida -> Nvidia
meh

想知道给出下联，能得到什么样的上联

如题

大神你好，能否提供一下你的训练好的模型？可以的话感激不尽~~~

喵喵喵？

2019-08-06 00:52:38.476421: E tensorflow/core/kernels/check_numerics_op.cc:185] abnormal_detected_host @0x7fb3e960d900 = {0, 1} Found Inf or
NaN global norm.Traceback (most recent call last):
File "/root/anaconda3/envs/fjpy36/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1334, in _do_call
return fn(*args)
File "/root/anaconda3/envs/fjpy36/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/root/anaconda3/envs/fjpy36/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Found Inf or NaN global norm. : Tensor had Inf values
[[{{node VerifyFinite/CheckNumerics}} = CheckNumericsT=DT_FLOAT, message="Found Inf or NaN global norm.", _device="/job:localhost/r
eplica:0/task:0/device:GPU:0"]] [[{{node clip_by_global_norm/mul_1/_301}} = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0
", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_2818_clip_by_global_norm/mul_1", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]