can't pickle _thread.lock objects

[Jatapiaro]

I'm running the twitter chatbot code but I'm getting the next error: "can't pickle _thread.lock objects"

What does that means?

[dexterchan]

I got the same issue with Python 3.6 with tensor 1.1.0

Building Graph --------------------------------------------------------------------------- TypeError Traceback (most recent call last) in () 5 ckpt_path='ckpt/cmudict/', 6 emb_dim=emb_dim, ----> 7 num_layers=3 8 ) /Users/dexter/Downloads/TensorFlowTutorial/practical_seq2seq-master/seq2seq_wrapper.py in __init__(self, xseq_len, yseq_len, xvocab_size, yvocab_size, emb_dim, num_layers, ckpt_path, lr, epochs, model_name) 77 sys.stdout.write(' Building Graph ') 78 # build comput graph ---> 79 __graph__() 80 sys.stdout.write('') 81 /Users/dexter/Downloads/TensorFlowTutorial/practical_seq2seq-master/seq2seq_wrapper.py in __graph__() 56 # inputs : encoder, decoder inputs, LSTM cell type, vocabulary sizes, embedding dimensions 57 self.decode_outputs, self.decode_states = tf.contrib.legacy_seq2seq.embedding_rnn_seq2seq(self.enc_ip,self.dec_ip, stacked_lstm, ---> 58 xvocab_size, yvocab_size, emb_dim) 59 # share parameters 60 scope.reuse_variables() /Users/dexter/anaconda/lib/python3.6/site-packages/tensorflow/contrib/legacy_seq2seq/python/ops/seq2seq.py in embedding_rnn_seq2seq(encoder_inputs, decoder_inputs, cell, num_encoder_symbols, num_decoder_symbols, embedding_size, output_projection, feed_previous, dtype, scope) 356 357 # Encoder. --> 358 encoder_cell = copy.deepcopy(cell) 359 encoder_cell = core_rnn_cell.EmbeddingWrapper( 360 encoder_cell, /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 178 y = x 179 else: --> 180 y = _reconstruct(x, memo, *rv) 181 182 # If is its own copy, don't memoize. /Users/dexter/anaconda/lib/python3.6/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 278 if state is not None: 279 if deep: --> 280 state = deepcopy(state, memo) 281 if hasattr(y, '__setstate__'): 282 y.__setstate__(state) /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 148 copier = _deepcopy_dispatch.get(cls) 149 if copier: --> 150 y = copier(x, memo) 151 else: 152 try: /Users/dexter/anaconda/lib/python3.6/copy.py in _deepcopy_dict(x, memo, deepcopy) 238 memo[id(x)] = y 239 for key, value in x.items(): --> 240 y[deepcopy(key, memo)] = deepcopy(value, memo) 241 return y 242 d[dict] = _deepcopy_dict /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 148 copier = _deepcopy_dispatch.get(cls) 149 if copier: --> 150 y = copier(x, memo) 151 else: 152 try: /Users/dexter/anaconda/lib/python3.6/copy.py in _deepcopy_list(x, memo, deepcopy) 213 append = y.append 214 for a in x: --> 215 append(deepcopy(a, memo)) 216 return y 217 d[list] = _deepcopy_list /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 178 y = x 179 else: --> 180 y = _reconstruct(x, memo, *rv) 181 182 # If is its own copy, don't memoize. /Users/dexter/anaconda/lib/python3.6/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 278 if state is not None: 279 if deep: --> 280 state = deepcopy(state, memo) 281 if hasattr(y, '__setstate__'): 282 y.__setstate__(state) /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 148 copier = _deepcopy_dispatch.get(cls) 149 if copier: --> 150 y = copier(x, memo) 151 else: 152 try: /Users/dexter/anaconda/lib/python3.6/copy.py in _deepcopy_dict(x, memo, deepcopy) 238 memo[id(x)] = y 239 for key, value in x.items(): --> 240 y[deepcopy(key, memo)] = deepcopy(value, memo) 241 return y 242 d[dict] = _deepcopy_dict /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 178 y = x 179 else: --> 180 y = _reconstruct(x, memo, *rv) 181 182 # If is its own copy, don't memoize. /Users/dexter/anaconda/lib/python3.6/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 278 if state is not None: 279 if deep: --> 280 state = deepcopy(state, memo) 281 if hasattr(y, '__setstate__'): 282 y.__setstate__(state) /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 148 copier = _deepcopy_dispatch.get(cls) 149 if copier: --> 150 y = copier(x, memo) 151 else: 152 try: /Users/dexter/anaconda/lib/python3.6/copy.py in _deepcopy_dict(x, memo, deepcopy) 238 memo[id(x)] = y 239 for key, value in x.items(): --> 240 y[deepcopy(key, memo)] = deepcopy(value, memo) 241 return y 242 d[dict] = _deepcopy_dict /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 178 y = x 179 else: --> 180 y = _reconstruct(x, memo, *rv) 181 182 # If is its own copy, don't memoize. /Users/dexter/anaconda/lib/python3.6/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 278 if state is not None: 279 if deep: --> 280 state = deepcopy(state, memo) 281 if hasattr(y, '__setstate__'): 282 y.__setstate__(state) /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 148 copier = _deepcopy_dispatch.get(cls) 149 if copier: --> 150 y = copier(x, memo) 151 else: 152 try: /Users/dexter/anaconda/lib/python3.6/copy.py in _deepcopy_dict(x, memo, deepcopy) 238 memo[id(x)] = y 239 for key, value in x.items(): --> 240 y[deepcopy(key, memo)] = deepcopy(value, memo) 241 return y 242 d[dict] = _deepcopy_dict /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 178 y = x 179 else: --> 180 y = _reconstruct(x, memo, *rv) 181 182 # If is its own copy, don't memoize. /Users/dexter/anaconda/lib/python3.6/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 278 if state is not None: 279 if deep: --> 280 state = deepcopy(state, memo) 281 if hasattr(y, '__setstate__'): 282 y.__setstate__(state) /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 148 copier = _deepcopy_dispatch.get(cls) 149 if copier: --> 150 y = copier(x, memo) 151 else: 152 try: /Users/dexter/anaconda/lib/python3.6/copy.py in _deepcopy_dict(x, memo, deepcopy) 238 memo[id(x)] = y 239 for key, value in x.items(): --> 240 y[deepcopy(key, memo)] = deepcopy(value, memo) 241 return y 242 d[dict] = _deepcopy_dict /Users/dexter/anaconda/lib/python3.6/copy.py in deepcopy(x, memo, _nil) 167 reductor = getattr(x, "__reduce_ex__", None) 168 if reductor: --> 169 rv = reductor(4) 170 else: 171 reductor = getattr(x, "__reduce__", None) TypeError: can't pickle _thread.lock objects

[Jatapiaro]

I found a solution for it. You should check my code https://github.com/Jatapiaro/TwinkerBot_Revival Twitter traning starts the bot training, that's where I got the error. Copy paste my seq2seq_wrapper code, use python 3 and please use tensorflow 1.0.0

[dexterchan]

then I receive this... thank you

Building Graph --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) in () 5 ckpt_path='ckpt/twitter/', 6 emb_dim=emb_dim, ----> 7 num_layers=3 8 ) /Users/dexter/Downloads/TensorFlowTutorial/TwinkerBot_Revival-master/seq2seq_wrapper.py in __init__(self, xseq_len, yseq_len, xvocab_size, yvocab_size, emb_dim, num_layers, ckpt_path, lr, epochs, model_name) 76 sys.stdout.write(' Building Graph ') 77 # build comput graph ---> 78 __graph__() 79 sys.stdout.write('') 80 /Users/dexter/Downloads/TensorFlowTutorial/TwinkerBot_Revival-master/seq2seq_wrapper.py in __graph__() 39 self.keep_prob = tf.placeholder(tf.float32) 40 # define the basic cell ---> 41 basic_cell = tf.contrib.rnn.core_rnn_cell.DropoutWrapper( 42 tf.contrib.rnn.core_rnn_cell.BasicLSTMCell(emb_dim, state_is_tuple=True), 43 output_keep_prob=self.keep_prob) AttributeError: module 'tensorflow.contrib.rnn' has no attribute 'core_rnn_cell'

[Jatapiaro]

@dexterchan Are you shure that you're using Tensorflow 1.0.0 and python3? You can check your tensorflow version using the command below: python3 -c "import tensorflow as tf; print(tf.version)"

[dexterchan]

Sorry, forget to upgrade my tensorflow.... it is running training now... thank you for your support.... :)

[Jatapiaro]

@dexterchan You're welcome :) And please be careful with this https://github.com/suriyadeepan/practical_seq2seq/issues/2 I recommend you to left your training running as most as you can, I've lost one day trying to restore sessions but it doesn't work, for some reason begins again.

[say4n]

To anyone trying to run python3 -c "import tensorflow as tf; print(tf.version)", you'll get a AttributeError, version has been renamed to VERSION, so, now you've to run python3 -c "import tensorflow as tf; print(tf.VERSION)"

[anthdm]

Using Tensorflow 1.0.0 fix this issue. To downgrade the gpu version pip3 install tensorflow-gpu==1.0.0 To downgrade the cpu version pip3 install tensorflow==1.0.0

[Macintoshxz]

@anthdm Thank you ! That works for me! Downgrade the Tensorflow to 1.0.0.

[LilyDreamZhao]

Is there any other way ?I wouldn't downgrade the tensorflow to 1.0.0