我在我的Windows7上使用python 3.5和tensorflow r0.12 cpu运行了这段代码（https://github.com/monkut/tensorflow_chatbot主要代码在execute.py中），并且在300步之后发生错误。然后我尝试将词汇量大小更改为30000并每100步设置一个checkpiont。对于1层128个单元，在3900步之后出现错误，并且在5400步之后出现3层256单元。 那是什么错误？有办法解决吗？
错误：
>> Mode : train
Preparing data in working_dir/
Creating vocabulary working_dir/vocab20000.enc from data/train.enc
processing line 100000
>> Full Vocabulary Size : 45408
>>>> Vocab Truncated to: 20000
Creating vocabulary working_dir/vocab20000.dec from data/train.dec
processing line 100000
>> Full Vocabulary Size : 44271
>>>> Vocab Truncated to: 20000
Tokenizing data in data/train.enc
tokenizing line 100000
Tokenizing data in data/train.dec
tokenizing line 100000
Tokenizing data in data/test.enc
Creating 3 layers of 256 units.
Created model with fresh parameters.
Reading development and training data (limit: 0).
reading data line 100000
global step 300 learning rate 0.5000 step-time 3.34 perplexity 377.45
eval: bucket 0 perplexity 96.25
eval: bucket 1 perplexity 210.94
eval: bucket 2 perplexity 267.86
eval: bucket 3 perplexity 365.77
Traceback (most recent call last):
File "C:\Python35 64\lib\site-packages\tensorflow\python\client\session.py", l
ine 1021, in _do_call
return fn(*args)
File "C:\Python35 64\lib\site-packages\tensorflow\python\client\session.py", l
ine 1003, in _run_fn
status, run_metadata)
File "C:\Python35 64\lib\contextlib.py", line 66, in __exit__
next(self.gen)
File "C:\Python35 64\lib\site-packages\tensorflow\python\framework\errors_impl
.py", line 469, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: indices[40] = 2000
0 is not in [0, 20000)
[[Node: model_with_buckets/sequence_loss_3/sequence_loss_by_example/sam
pled_softmax_loss_28/embedding_lookup_1 = Gather[Tindices=DT_INT64, Tparams=DT_F
LOAT, _class=["loc:@proj_b"], validate_indices=true, _device="/job:localhost/rep
lica:0/task:0/cpu:0"](proj_b/read, model_with_buckets/sequence_loss_3/sequence_l
oss_by_example/sampled_softmax_loss_28/concat)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "execute.py", line 352, in <module>
train()
File "execute.py", line 180, in train
target_weights, bucket_id, False)
File "C:\Users\Администратор\Downloads\tensorflow_chatbot-master (1)\tensorflo
w_chatbot-master\seq2seq_model.py", line 230, in step
outputs = session.run(output_feed, input_feed)
File "C:\Python35 64\lib\site-packages\tensorflow\python\client\session.py", l
ine 766, in run
run_metadata_ptr)
File "C:\Python35 64\lib\site-packages\tensorflow\python\client\session.py", l
ine 964, in _run
feed_dict_string, options, run_metadata)
File "C:\Python35 64\lib\site-packages\tensorflow\python\client\session.py", l
ine 1014, in _do_run
target_list, options, run_metadata)
File "C:\Python35 64\lib\site-packages\tensorflow\python\client\session.py", l
ine 1034, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: indices[40] = 2000
0 is not in [0, 20000)
[[Node: model_with_buckets/sequence_loss_3/sequence_loss_by_example/sam
pled_softmax_loss_28/embedding_lookup_1 = Gather[Tindices=DT_INT64, Tparams=DT_F
LOAT, _class=["loc:@proj_b"], validate_indices=true, _device="/job:localhost/rep
lica:0/task:0/cpu:0"](proj_b/read, model_with_buckets/sequence_loss_3/sequence_l
oss_by_example/sampled_softmax_loss_28/concat)]]
Caused by op 'model_with_buckets/sequence_loss_3/sequence_loss_by_example/sample
d_softmax_loss_28/embedding_lookup_1', defined at:
File "execute.py", line 352, in <module>
train()
File "execute.py", line 148, in train
model = create_model(sess, False)
File "execute.py", line 109, in create_model
gConfig['learning_rate_decay_factor'], forward_only=forward_only)
File "C:\Users\Администратор\Downloads\tensorflow_chatbot-master (1)\tensorflo
w_chatbot-master\seq2seq_model.py", line 158, in __init__
softmax_loss_function=softmax_loss_function)
File "C:\Python35 64\lib\site-packages\tensorflow\python\ops\seq2seq.py", line
1130, in model_with_buckets
softmax_loss_function=softmax_loss_function))
File "C:\Python35 64\lib\site-packages\tensorflow\python\ops\seq2seq.py", line
1058, in sequence_loss
softmax_loss_function=softmax_loss_function))
File "C:\Python35 64\lib\site-packages\tensorflow\python\ops\seq2seq.py", line
1022, in sequence_loss_by_example
crossent = softmax_loss_function(logit, target)
File "C:\Users\Администратор\Downloads\tensorflow_chatbot-master (1)\tensorflo
w_chatbot-master\seq2seq_model.py", line 101, in sampled_loss
self.target_vocab_size)
File "C:\Python35 64\lib\site-packages\tensorflow\python\ops\nn.py", line 1412
, in sampled_softmax_loss
name=name)
File "C:\Python35 64\lib\site-packages\tensorflow\python\ops\nn.py", line 1184
, in _compute_sampled_logits
all_b = embedding_ops.embedding_lookup(biases, all_ids)
File "C:\Python35 64\lib\site-packages\tensorflow\python\ops\embedding_ops.py"
, line 110, in embedding_lookup
validate_indices=validate_indices)
File "C:\Python35 64\lib\site-packages\tensorflow\python\ops\gen_array_ops.py"
, line 1293, in gather
validate_indices=validate_indices, name=name)
File "C:\Python35 64\lib\site-packages\tensorflow\python\framework\op_def_libr
ary.py", line 759, in apply_op
op_def=op_def)
File "C:\Python35 64\lib\site-packages\tensorflow\python\framework\ops.py", li
ne 2240, in create_op
original_op=self._default_original_op, op_def=op_def)
File "C:\Python35 64\lib\site-packages\tensorflow\python\framework\ops.py", li
ne 1128, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): indices[40] = 20000 is not in [0
, 20000)
[[Node: model_with_buckets/sequence_loss_3/sequence_loss_by_example/sam
pled_softmax_loss_28/embedding_lookup_1 = Gather[Tindices=DT_INT64, Tparams=DT_F
LOAT, _class=["loc:@proj_b"], validate_indices=true, _device="/job:localhost/rep
lica:0/task:0/cpu:0"](proj_b/read, model_with_buckets/sequence_loss_3/sequence_l
oss_by_example/sampled_softmax_loss_28/concat)]]
答案 0 :(得分：0)
符号[)表示在区间符号中包含独占。
[表示包含该号码。 (表示不包括该号码。
右括号和括号也是如此，即]＆amp; )。例如[0,20000)
意味着从零包含到20000不包括在内。括号意味着＆＃34;是包括这个＆＃34;括号表示＆＃34;不，不要一直到这个数字＆＃34;
答案 1 :(得分：0)
似乎使用virtualenv和tensorflow-gpu 0.12.0解决了我的问题。