Comments (1)
It seems that the README was not updated to reflect a change that consolidated the binaries into a single flag-based binary. I've updated the readme (commit 88c2118) to reflect this change. Thanks for the heads up!
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Related Issues (20)
- Question on the Implementation of FedYOGI HOT 1
- some questions when run examples in [federated optimization] module. HOT 2
- Issues of federated-gans HOT 2
- AttributeError while trying to run optimization HOT 1
- [optimization]reproduce the result of paper "ADAPTIVE FEDERATED OPTIMIZATION" HOT 7
- [optimization]Split EMNIST and Stackoverflow Evenly HOT 1
- On Dirichlet Concentration Factor HOT 3
- Clarification the result of paper "ADAPTIVE FEDERATED OPTIMIZATION" HOT 2
- TFF reconstruction for time-series prediction HOT 1
- [distributed_dp] Including package versions into the requirements file HOT 12
- [distributed-dp] running of fl_run: AttributeError: module 'tensorflow_federated.python.program' has no attribute 'TensorBoardReleaseManager' HOT 2
- [differential_privacy] Learning rates used for Adaptive Clipping experiments HOT 6
- Flags not consistent in federated/utils/optimizers/optimizer_utils.py
- [large_cohort] AttributeError: 'LearningAlgorithmState' object has no attribute 'model' HOT 3
- Calling bazel within cache directory fails: experiments/emnist:run_experiments
- [federated/targeted_attack] targeted_attack example documentation is inconsistent
- `optimization/`: `num_validation_examples` batches instead of examples
- [distributed-dp] DSkellam goes weird w/ small num_bits HOT 3
- [Distributed DP] Cannot capture a result of an unsupported type NoneType
- Can you provide a Linux version of jaxlib 0.3.14 for download
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