Comments (3)
Hello, I am getting the exact same problem with tensorflow 1.14. in a docker container based on tensorflow:1.14.0-gpu image and cuda 10.0 and a GPU with 10GB of RAM . The execution also stops at:
Successfully opened dynamic library libcublas.so.10
Is there any adidtional information we could provide to help identify this issue?
Thanks in advance.
from coref.
This is probably not the issue for others, but I was also seeing the training hang with tensorflow 1.14 after
Successfully opened dynamic library libcublas.so.10
For me, the problem was that my train set was empty, so it might be helpful to double check that.
from coref.
Does anyone have resolved this issue after "Successfully opened dynamic library libcublas.so.10" ?
2022-02-01 15:06:35.916081: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
2022-02-01 15:07:28.841615: E tensorflow/stream_executor/cuda/cuda_blas.cc:428] failed to run cuBLAS routine: CUBLAS_STATUS_EXECUTION_FAILED
2022-02-01 15:07:28.848147: W tensorflow/core/kernels/queue_base.cc:277] _0_padding_fifo_queue: Skipping cancelled enqueue attempt with queue not closed
Traceback (most recent call last):
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1356, in _do_call
return fn(*args)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1341, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1429, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InternalError: 2 root error(s) found.
(0) Internal: Blas GEMM launch failed : a.shape=(30, 20), b.shape=(20, 3000), m=30, n=3000, k=20
[[{{node width_scores/xw_plus_b/MatMul}}]]
[[strided_slice_6/_1889]]
(1) Internal: Blas GEMM launch failed : a.shape=(30, 20), b.shape=(20, 3000), m=30, n=3000, k=20
[[{{node width_scores/xw_plus_b/MatMul}}]]
0 successful operations.
0 derived errors ignored.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "train.py", line 58, in
tf_loss, tf_global_step, _ = session.run([model.loss, model.global_step, model.train_op])
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 950, in run
run_metadata_ptr)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1173, in _run
feed_dict_tensor, options, run_metadata)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1350, in _do_run
run_metadata)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1370, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InternalError: 2 root error(s) found.
(0) Internal: Blas GEMM launch failed : a.shape=(30, 20), b.shape=(20, 3000), m=30, n=3000, k=20
[[node width_scores/xw_plus_b/MatMul (defined at /home/souid/coref/util.py:109) ]]
[[strided_slice_6/_1889]]
(1) Internal: Blas GEMM launch failed : a.shape=(30, 20), b.shape=(20, 3000), m=30, n=3000, k=20
[[node width_scores/xw_plus_b/MatMul (defined at /home/souid/coref/util.py:109) ]]
0 successful operations.
0 derived errors ignored.
Errors may have originated from an input operation.
Input Source operations connected to node width_scores/xw_plus_b/MatMul:
width_scores/hidden_weights_0/read (defined at /home/souid/coref/util.py:107)
span_width_prior_embeddings/read (defined at /home/souid/coref/independent.py:379)
Input Source operations connected to node width_scores/xw_plus_b/MatMul:
width_scores/hidden_weights_0/read (defined at /home/souid/coref/util.py:107)
span_width_prior_embeddings/read (defined at /home/souid/coref/independent.py:379)
Original stack trace for 'width_scores/xw_plus_b/MatMul':
File "train.py", line 26, in
model = util.get_model(config)
File "/home/souid/coref/util.py", line 21, in get_model
return independent.CorefModel(config)
File "/home/souid/coref/independent.py", line 54, in init
self.predictions, self.loss = self.get_predictions_and_loss(*self.input_tensors)
File "/home/souid/coref/independent.py", line 283, in get_predictions_and_loss
candidate_mention_scores = self.get_mention_scores(candidate_span_emb, candidate_starts, candidate_ends)
File "/home/souid/coref/independent.py", line 382, in get_mention_scores
width_scores = util.ffnn(span_width_emb, self.config["ffnn_depth"], self.config["ffnn_size"], 1, self.dropout) # [W, 1]
File "/home/souid/coref/util.py", line 109, in ffnn
current_outputs = tf.nn.relu(tf.nn.xw_plus_b(current_inputs, hidden_weights, hidden_bias))
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/ops/nn_ops.py", line 4066, in xw_plus_b
mm = math_ops.matmul(x, weights)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/util/dispatch.py", line 180, in wrapper
return target(*args, **kwargs)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/ops/math_ops.py", line 2647, in matmul
a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/ops/gen_math_ops.py", line 5925, in mat_mul
name=name)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3616, in create_op
op_def=op_def)
File "/home/souid/anaconda3/envs/arabic_coref/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2005, in init
self._traceback = tf_stack.extract_stack()
from coref.
Related Issues (20)
- Has anyone got this to work? HOT 3
- How to specify paths correctly? HOT 1
- why not pytorch code for that?
- How to evaluate SpanBERT using sample test data? HOT 3
- assert num_words == np.sum(input_mask), (num_words, np.sum(input_mask))
- Found too many repeated mentions (> 10) in the response, so refusing to score
- Requirements txt is broken
- libprotobuf FATAL : CHECK failed: it != end(): key not found
- converting predicted (subtoken) output to normal text HOT 1
- Num_docs and evaluating docs
- Predicting singletons HOT 1
- Does this model apply to Chinese data? HOT 2
- Too many errors while installing requirements HOT 1
- Custom training data for BERT
- Has anyone reproduced successfully on windows?
- can anyone explain why the execution kept stuck here without generating any error or something else ?
- how can i choose the batch size, in which code file should I modify ?
- can anyone help me with the gpu configuration? it works well on cpu but when i turn to the model to run on gpu it opens succefully all the related libraries but crashes it some step
- Sentence index when splitting long sentences into non-overlapping chunks
- F1 79.96 on ontonotes 5 with your pretrained spanbert_large HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from coref.