Comments (9)
@dikjstra Hi, please git clone the repository and build. The pip installation does not work now.
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@dikjstra Hi, please git clone the repository and build. The pip installation does not work now.
I used this method to install the framework:
git clone https://github.com/tf-encrypted/tf-encrypted.git
cd tf-encrypted
pip install -e .
make build
When I run the “make build” command I get the following error:
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@dikjstra as the error pointed out, depending on your system, you will have to install autoconf
before moving on. For example, on Ubuntu, try this.
from tf-encrypted.
@dikjstra as the error pointed out, depending on your system, you will have to install
autoconf
before moving on. For example, on Ubuntu, try this.
After I installed it, I still got this error:
from tf-encrypted.
@dikjstra as the error pointed out, depending on your system, you will have to install
autoconf
before moving on. For example, on Ubuntu, try this.
is libtool installed on your system? you could check by libtool --version
.
are you using a docker to run tf-encrypted? We suggest you to use the python3.8 docker image.
from tf-encrypted.
@dikjstra as the error pointed out, depending on your system, you will have to install
autoconf
before moving on. For example, on Ubuntu, try this.is libtool installed on your system? you could check by
libtool --version
. are you using a docker to run tf-encrypted? We suggest you to use the python3.8 docker image.
Thanks for the answer, I'll keep trying
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Ran into this as well. Did you manage to solve it @dikjstra ?
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not work for me......
from tf-encrypted.
linux glibc version is too low to load sercure_random.so.
it need glibc 2.25+...
so i change to use docker with python3.8 gcc 12.2 glibc 2.36 to pip install tf-encrypted
it work for me
i suggest that tf-encrypte need to notify user when compile or pip install tf-encrypted need glibc 2.25+ gcc version an so on ...
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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
- 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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