Comments (8)
I met the same problems, exactly in the same way. “when run this code "w = tfe.define_private_variable(tf.ones(shape=(10,10)))", Segmentation fault (core dumped) occured.“
all I did is trying to run the tutorial code in the readme.md.
my env:
- platform is CentOS Linux release 7.8.2003 (Core)
- i isntalled tfe by the 2nd way, from source, and build completed with no error.
- python version is 3.6.5.
- tf version is 1.15.2 as required.
please help. thx
Could you check if the problem exists on tf 1.13.2 and tf 1.14.0 ?
Thank you for quick reply. I will take a try, but why the requirements said 1.15.2?
OK, I have tried both 1.13.2 and 1.14.0, they both work well. problem solved.
Thank you again, and could you do a favor explaining some of the deep reason for the problem in 1.15.2?
from tf-encrypted.
got any idea in mind ?
Unfortunately nothing solid, I haven't been keeping up with the tf1 compatibility recently. Just looking at the readme code, I don't see anything obvious. One possibility I could imagine is if you built tensorflow with our patch for secure randomness. That secure randomness op uses their Custom Op API in tensorflow_core, but they may have introduced breaking changes to it in the jump from 1.14.0 -> 1.15.2, since that API does not have stability guarantees. I think they were interested in phasing that API out w/ TF2, because they had some other things in the works for adding new Ops to TF (maybe related to their work on TFRT).
from tf-encrypted.
Could you provide your TF version, and the script you ran ?
from tf-encrypted.
when run this code "w = tfe.define_private_variable(tf.ones(shape=(10,10)))", Segmentation fault (core dumped) occured.
@purpleyun it would help to debug the issue if you could provide:
- Detailed platform information with
uname -a
if you are on linux or macos - How you install the library? Building from source, or using
pip install tf-encrypted
? - TF version, script (showing which mpc protocol you use)
from tf-encrypted.
I met the same problems, exactly in the same way. “when run this code "w = tfe.define_private_variable(tf.ones(shape=(10,10)))", Segmentation fault (core dumped) occured.“
all I did is trying to run the tutorial code in the readme.md.
my env:
- platform is CentOS Linux release 7.8.2003 (Core)
- i isntalled tfe by the 2nd way, from source, and build completed with no error.
- python version is 3.6.5.
- tf version is 1.15.2 as required.
please help. thx
from tf-encrypted.
I met the same problems, exactly in the same way. “when run this code "w = tfe.define_private_variable(tf.ones(shape=(10,10)))", Segmentation fault (core dumped) occured.“
all I did is trying to run the tutorial code in the readme.md.
my env:
- platform is CentOS Linux release 7.8.2003 (Core)
- i isntalled tfe by the 2nd way, from source, and build completed with no error.
- python version is 3.6.5.
- tf version is 1.15.2 as required.
please help. thx
Could you check if the problem exists on tf 1.13.2 and tf 1.14.0 ?
from tf-encrypted.
I met the same problems, exactly in the same way. “when run this code "w = tfe.define_private_variable(tf.ones(shape=(10,10)))", Segmentation fault (core dumped) occured.“
all I did is trying to run the tutorial code in the readme.md.
my env:
- platform is CentOS Linux release 7.8.2003 (Core)
- i isntalled tfe by the 2nd way, from source, and build completed with no error.
- python version is 3.6.5.
- tf version is 1.15.2 as required.
please help. thx
Could you check if the problem exists on tf 1.13.2 and tf 1.14.0 ?
Thank you for quick reply. I will take a try, but why the requirements said 1.15.2?
OK, I have tried both 1.13.2 and 1.14.0, they both work well. problem solved. Thank you again, and could you do a favor explaining some of the deep reason for the problem in 1.15.2?
Actually I don't know why :( , I suggested that because I encountered a similar problem last year when using tf1.15. @zicofish @jvmncs got any idea in mind ?
from tf-encrypted.
I met the same problems, exactly in the same way. “when run this code "w = tfe.define_private_variable(tf.ones(shape=(10,10)))", Segmentation fault (core dumped) occured.“
all I did is trying to run the tutorial code in the readme.md.
my env:
- platform is CentOS Linux release 7.8.2003 (Core)
- i isntalled tfe by the 2nd way, from source, and build completed with no error.
- python version is 3.6.5.
- tf version is 1.15.2 as required.
please help. thx
Could you check if the problem exists on tf 1.13.2 and tf 1.14.0 ?
Thank you for quick reply. I will take a try, but why the requirements said 1.15.2?
OK, I have tried both 1.13.2 and 1.14.0, they both work well. problem solved. Thank you again, and could you do a favor explaining some of the deep reason for the problem in 1.15.2?Actually I don't know why :( , I suggested that because I encountered a similar problem last year when using tf1.15. @zicofish @jvmncs got any idea in mind ?
Anyway, thank you a lot for replying. Looking for further discussion.
from tf-encrypted.
Related Issues (20)
- Save and Load ABY3 Model
- Can this framework use encrypted training data to train network models? Are there any relevant cases to learn from? HOT 7
- version 0.8 federation-learning example seems contain an error in validation dataset setting HOT 2
- AssertionError When running Server HOT 2
- Scaling base question HOT 2
- 'NoneType' object has no attribute 'secure_seed' HOT 9
- TypeError: can only concatenate list (not "TensorShapeV1") to list. (An error in sample_seeded_uniform) HOT 2
- In the federated learning of examples, how to protect the DataOwner's gradient? HOT 1
- I can't install TF-Encrypted HOT 1
- Is it possible to evaluate the BaseModel with other keras metrics aside from binary and categorical accuracy? HOT 5
- Trying to better understand the framework beahavior HOT 2
- ValueError: Invalid dtype tf.int16 HOT 2
- why I can see all secret shares in one party? HOT 3
- Can't import tf_encrypted in Colab notebook
- windows install tf-encrypted issue HOT 2
- make: *** [Makefile:322:tf_encrypted/operations/secure_random/secure_random_module_tf_2.13.0.so]; make build error HOT 1
- DepthwiseConv2D output shape bug???
- WAN setting benchmarks. HOT 4
- ImportError: cannot import name 'glob_stateful_parallelism' from 'tensorflow.python.ops.while_v2' HOT 3
- fatal error: tensorflow/core/util/work_sharder.h: No such file or directory #include "tensorflow/core/util/work_sharder.h" HOT 1
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