sampled_loss() got an unexpected keyword argument 'logits'

[athuldevin]

I am using tesorflow version 1.2 (gpu)
i try to run tensorflow chatbot which is a varient of translate example . fixed many problems due to version change ,but can't fix this error

Traceback (most recent call last): File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 319, in <module> train() File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 137, in train model = create_model(sess, False) File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 104, in create_model model = seq2seq_model.Seq2SeqModel( gConfig['enc_vocab_size'], gConfig['dec_vocab_size'], _buckets, gConfig['layer_size'], gConfig['num_layers'], gConfig['max_gradient_norm'], gConfig['batch_size'], gConfig['learning_rate'], gConfig['learning_rate_decay_factor'], forward_only=forward_only) File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\seq2seq_model.py", line 150, in __init__ softmax_loss_function=softmax_loss_function) File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 1221, in model_with_buckets softmax_loss_function=softmax_loss_function)) File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 1134, in sequence_loss softmax_loss_function=softmax_loss_function)) File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 1089, in sequence_loss_by_example crossent = softmax_loss_function(labels=target, logits=logit) TypeError: sampled_loss() got an unexpected keyword argument 'logits'

error causing line of code
self.outputs, self.losses = tf.contrib.legacy_seq2seq.model_with_buckets( self.encoder_inputs, self.decoder_inputs, targets, self.target_weights, buckets, lambda x, y: seq2seq_f(x, y, False), softmax_loss_function=softmax_loss_function) <-- line 150 from seq2seq.py

and softmax_loss_function is come from here

def sampled_loss(inputs, labels): labels = tf.reshape(labels, [-1, 1]) return tf.nn.sampled_softmax_loss(w_t, b, labels, inputs, num_samples, self.target_vocab_size) softmax_loss_function = sampled_loss

please help

[StephenLee2016]

@athuldevin Hi, i also met this error, but when i changed 'sampled_loss(inputs, labels)' to 'sampled_loss(labels, logits) : labels = tf.reshape(labels, [-1, 1]) return tf.nn.sampled_softmax_loss(w_t, b, labels, logits, num_samples, self.target_vocab_size) ' , the error gone.

[athuldevin]

@StephenLee2016 hi, thanks that error is fixed but a new one is generated may be it is related to that one

Traceback (most recent call last): File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 319, in <module> train() File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 137, in train model = create_model(sess, False) File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\execute.py", line 104, in create_model model = seq2seq_model.Seq2SeqModel( gConfig['enc_vocab_size'], gConfig['dec_vocab_size'], _buckets, gConfig['layer_size'], gConfig['num_layers'], gConfig['max_gradient_norm'], gConfig['batch_size'], gConfig['learning_rate'], gConfig['learning_rate_decay_factor'], forward_only=forward_only) File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\seq2seq_model.py", line 150, in __init__ softmax_loss_function=softmax_loss_function) File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 1206, in model_with_buckets decoder_inputs[:bucket[1]]) File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\seq2seq_model.py", line 149, in <lambda> lambda x, y: seq2seq_f(x, y, False), File "C:\Users\win-7\Downloads\tensorflow_chatbot-master\new\seq2seq_model.py", line 113, in seq2seq_f feed_previous=do_decode) File "C:\Python35\lib\site-packages\tensorflow\contrib\legacy_seq2seq\python\ops\seq2seq.py", line 848, in embedding_attention_seq2seq encoder_cell = copy.deepcopy(cell) File "C:\Python35\lib\copy.py", line 166, in deepcopy y = copier(memo) File "C:\Python35\lib\site-packages\tensorflow\python\layers\base.py", line 476, in __deepcopy__ setattr(result, k, copy.deepcopy(v, memo)) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list y.append(deepcopy(a, memo)) File "C:\Python35\lib\copy.py", line 166, in deepcopy y = copier(memo) File "C:\Python35\lib\site-packages\tensorflow\python\layers\base.py", line 476, in __deepcopy__ setattr(result, k, copy.deepcopy(v, memo)) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list y.append(deepcopy(a, memo)) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list y.append(deepcopy(a, memo)) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 291, in _reconstruct args = deepcopy(args, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 223, in _deepcopy_tuple y = [deepcopy(a, memo) for a in x] File "C:\Python35\lib\copy.py", line 223, in <listcomp> y = [deepcopy(a, memo) for a in x] File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list y.append(deepcopy(a, memo)) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list y.append(deepcopy(a, memo)) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list y.append(deepcopy(a, memo)) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list y.append(deepcopy(a, memo)) File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 223, in _deepcopy_tuple y = [deepcopy(a, memo) for a in x] File "C:\Python35\lib\copy.py", line 223, in <listcomp> y = [deepcopy(a, memo) for a in x] File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo) File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo) File "C:\Python35\lib\copy.py", line 306, in _reconstruct y.__dict__.update(state) AttributeError: 'NoneType' object has no attribute 'update'

is i need to change this line of code from execute.py

"""Create model and initialize or load parameters"""
def create_model(session, forward_only): model = seq2seq_model.Seq2SeqModel( gConfig['enc_vocab_size'], gConfig['dec_vocab_size'], _buckets, gConfig['layer_size'], gConfig['num_layers'], gConfig['max_gradient_norm'], gConfig['batch_size'], gConfig['learning_rate'], gConfig['learning_rate_decay_factor'], forward_only=forward_only)

this error also happens in translate program
thanks for helping

[StephenLee2016]

@athuldevin Hi, I also met this issue now, maybe translate.py need be updated, and you can focus #1733

[Katsatsaka]

Hi,
I also got this error when trying to run seq2seq model (translate.py) with tensorflow 1.2 python 3.5.

...
File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 297, in _reconstruct state = deepcopy(state, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 243, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo)
File "C:\Python35\lib\copy.py", line 155, in deepcopy y = copier(x, memo)
File "C:\Python35\lib\copy.py", line 218, in _deepcopy_list y.append(deepcopy(a, memo))
File "C:\Python35\lib\copy.py", line 182, in deepcopy y = _reconstruct(x, rv, 1, memo)
File "C:\Python35\lib\copy.py", line 306, in _reconstruct y.dict.update(state) AttributeError: 'NoneType' object has no attribute 'update'
...

Please help to fix it.

[athuldevin]

can you share the full error message

[shahabaejaz]

@athuldevin Thanks my error is resolved but now i received another error

python3 execute.py

Mode : train

Preparing data in working_dir/
2017-09-05 17:03:48.291647: W 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.
2017-09-05 17:03:48.291668: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-09-05 17:03:48.291673: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-09-05 17:03:48.291677: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Creating 3 layers of 128 units.
Traceback (most recent call last):
File "execute.py", line 290, in
train()
File "execute.py", line 114, in train
model = create_model(sess, False)
File "execute.py", line 82, in create_model
model = seq2seq_model.Seq2SeqModel( gConfig['enc_vocab_size'], gConfig['dec_vocab_size'], _buckets, gConfig['layer_size'], gConfig['num_layers'], gConfig['max_gradient_norm'], gConfig['batch_size'], gConfig['learning_rate'], gConfig['learning_rate_decay_factor'], forward_only=forward_only)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/chatbot_model/chatbot-master/seq2seq_model.py", line 112, in init
softmax_loss_function=softmax_loss_function)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/site-packages/tensorflow/contrib/legacy_seq2seq/python/ops/seq2seq.py", line 1206, in model_with_buckets
decoder_inputs[:bucket[1]])
File "/Users/ttmac2/Documents/Shahab/MachineLearning/chatbot_model/chatbot-master/seq2seq_model.py", line 111, in
lambda x, y: seq2seq_f(x, y, False),
File "/Users/ttmac2/Documents/Shahab/MachineLearning/chatbot_model/chatbot-master/seq2seq_model.py", line 75, in seq2seq_f
feed_previous=do_decode)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/site-packages/tensorflow/contrib/legacy_seq2seq/python/ops/seq2seq.py", line 848, in embedding_attention_seq2seq
encoder_cell = copy.deepcopy(cell)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 161, in deepcopy
y = copier(memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 487, in deepcopy
setattr(result, k, copy.deepcopy(v, memo))
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 215, in _deepcopy_list
append(deepcopy(a, memo))
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 280, in _reconstruct
state = deepcopy(state, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 280, in _reconstruct
state = deepcopy(state, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 280, in _reconstruct
state = deepcopy(state, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 180, in deepcopy
y = _reconstruct(x, memo, *rv)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 280, in _reconstruct
state = deepcopy(state, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 150, in deepcopy
y = copier(x, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 240, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/Users/ttmac2/Documents/Shahab/MachineLearning/anaconda/lib/python3.6/copy.py", line 169, in deepcopy
rv = reductor(4)
TypeError: can't pickle _thread.lock objects

[athuldevin]

current solution for this error is downgrading your tensorflow version to 1.0.0 as said by the community

[MartinAbilev]

this not solution. solution is to update code !!!

[anne1994]

@MartinAbilev where do we update? could you give few directions?

[anne1994]

@shahabdroid i am also getting the same error.

[wantongtang]

@StephenLee2016 solved this problem

[Pk13055]

@shahabdroid @anne1994 This error is actually, firstly, not an error, and secondly, not related to tensorflow. Basically numpy or tensor objects cannot be pickled (atleast normally through the pickle module) since they are thread.locked, and deepcopy cannot copy such objects. Refer to this for a similar discussion.