Comments (1)
After looking more deeply into the logreg
refactor with @mortendahl , we concluded that it’s not really possible to work on parallel on this for now. So I put on hold my work until @mortendahl refactor the InputProvider architecture.
In the mean time, I’m going to look into input pipelines for TF and TF serving to see if we can avoid python completely when sending a request to the graph and also get a “start once, predict multiple requests” behavior.
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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
- '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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