akaxlh / mb-gmn Goto Github PK
View Code? Open in Web Editor NEWMB-GMN, SIGIR 2021
MB-GMN, SIGIR 2021
我是Python 3.6.6 tensorflow 1.14.0
没有对代码作任何修改,直接运行python labcode.py时如下报错,请问这是什么原因呢?
tensorflow.python.framework.errors_impl.InternalError: 2 root error(s) found.
(0) Internal: Blas xGEMMBatched launch failed : a.shape=[6520,1,96], b.shape=[6520,1,32], m=96, n=32, k=1, batch_size=6520
[[{{node gradients/matmul_74_grad/MatMul_1}}]]
[[Adam/update/_148]]
(1) Internal: Blas xGEMMBatched launch failed : a.shape=[6520,1,96], b.shape=[6520,1,32], m=96, n=32, k=1, batch_size=6520
[[{{node gradients/matmul_74_grad/MatMul_1}}]]
0 successful operations.
0 derived errors ignored.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "labcode.py", line 344, in
recom.run()
File "labcode.py", line 50, in run
reses = self.trainEpoch()
File "labcode.py", line 246, in trainEpoch
res = self.sess.run(target, feed_dict=feed_dict, options=config_pb2.RunOptions(report_tensor_allocations_upon_oom=True))
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 950, in run
run_metadata_ptr)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1173, in _run
feed_dict_tensor, options, run_metadata)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1350, in _do_run
run_metadata)
File "/home/user/anaconda3/envs/tf/lib/python3.6/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 xGEMMBatched launch failed : a.shape=[6520,1,96], b.shape=[6520,1,32], m=96, n=32, k=1, batch_size=6520
[[node gradients/matmul_74_grad/MatMul_1 (defined at labcode.py:198) ]]
[[Adam/update/_148]]
(1) Internal: Blas xGEMMBatched launch failed : a.shape=[6520,1,96], b.shape=[6520,1,32], m=96, n=32, k=1, batch_size=6520
[[node gradients/matmul_74_grad/MatMul_1 (defined at labcode.py:198) ]]
0 successful operations.
0 derived errors ignored.
Errors may have originated from an input operation.
Input Source operations connected to node gradients/matmul_74_grad/MatMul_1:
ExpandDims_29 (defined at labcode.py:151)
Input Source operations connected to node gradients/matmul_74_grad/MatMul_1:
ExpandDims_29 (defined at labcode.py:151)
Original stack trace for 'gradients/matmul_74_grad/MatMul_1':
File "labcode.py", line 344, in
recom.run()
File "labcode.py", line 38, in run
self.prepareModel()
File "labcode.py", line 198, in prepareModel
self.optimizer = tf.train.AdamOptimizer(learningRate).minimize(self.loss, global_step=globalStep)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/training/optimizer.py", line 403, in minimize
grad_loss=grad_loss)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/training/optimizer.py", line 512, in compute_gradients
colocate_gradients_with_ops=colocate_gradients_with_ops)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/gradients_impl.py", line 158, in gradients
unconnected_gradients)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/gradients_util.py", line 731, in _GradientsHelper
lambda: grad_fn(op, *out_grads))
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/gradients_util.py", line 403, in _MaybeCompile
return grad_fn() # Exit early
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/gradients_util.py", line 731, in
lambda: grad_fn(op, *out_grads))
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/math_grad.py", line 1511, in _BatchMatMulV2
grad_y = math_ops.matmul(x, grad, adjoint_a=True, adjoint_b=False)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/util/dispatch.py", line 180, in wrapper
return target(*args, **kwargs)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py", line 2609, in matmul
return batch_mat_mul_fn(a, b, adj_x=adjoint_a, adj_y=adjoint_b, name=name)
File "/home/wangchao/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/gen_math_ops.py", line 1677, in batch_mat_mul_v2
"BatchMatMulV2", x=x, y=y, adj_x=adj_x, adj_y=adj_y, name=name)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3616, in create_op
op_def=op_def)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2005, in init
self._traceback = tf_stack.extract_stack()
...which was originally created as op 'matmul_74', defined at:
File "labcode.py", line 344, in
recom.run()
[elided 0 identical lines from previous traceback]
File "labcode.py", line 38, in run
self.prepareModel()
File "labcode.py", line 186, in prepareModel
preds = self.predict(src, tgt)
File "labcode.py", line 166, in predict
return self._predict(src_ulat, src_ilat, predParams) * args.mult
File "labcode.py", line 152, in _predict
predEmbed = Activate(predEmbed @ params['w1'] + params['b1'], self.actFunc)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py", line 884, in binary_op_wrapper
return func(x, y, name=name)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/util/dispatch.py", line 180, in wrapper
return target(*args, **kwargs)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py", line 2609, in matmul
return batch_mat_mul_fn(a, b, adj_x=adjoint_a, adj_y=adjoint_b, name=name)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/ops/gen_math_ops.py", line 1677, in batch_mat_mul_v2
"BatchMatMulV2", x=x, y=y, adj_x=adj_x, adj_y=adj_y, name=name)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3616, in create_op
op_def=op_def)
File "/home/user/anaconda3/envs/tf/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2005, in init
self._traceback = tf_stack.extract_stack()
About the tmall data, I wonder how to use the data trn_pv.part*.rar. Does it need us to unzip the rar files and then just use one file as the input or the combination of all the files?
I would appreciate very much if you help me with the question.
Please provide the list of required packages for this repo.
Thanks.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.