The s-fsvi from timrudner

Problems setting the environment

Hi,
Thanks for your work and to have made your code publicly available!
I want to reproduce some of your experiments, but I'm having problems setting up the environment. I followed the installation instructions in the README and then following the code in the notebook split_mnist_singlehead.ipynb, I wrote this simple script to run the same experiment using S-FSVI:

import os
import sys
import sfsvi.exps.utils.load_utils as lutils
from notebooks.nb_utils.common import read_config_and_run, show_final_average_accuracy

root = os.path.abspath(os.path.join(os.getcwd(), ".."))
if root not in sys.path:
    sys.path.insert(0, root)

task_sequence = "smnist_sh"
config_path = 'notebooks/configs'

logdir = read_config_and_run(os.path.join(config_path, "fsvi_match.pkl"),
                             task_sequence)
exp = lutils.read_exp(logdir)
show_final_average_accuracy(exp)

Running this code snippet I get these warnings/errors:

/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/tensorflow_probability/python/__init__.py:69: UserWarning: TensorFloat-32 matmul/conv are enabled for NVIDIA Ampere+ GPUs. The resulting loss of precision may hinder MCMC convergence. To turn off, run `tf.config.experimental.enable_tensor_float_32_execution(False)`. For more detail, see https://github.com/tensorflow/community/pull/287.
  'TensorFloat-32 matmul/conv are enabled for NVIDIA Ampere+ GPUs. The '
/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/tensorflow_probability/python/__init__.py:69: UserWarning: TensorFloat-32 matmul/conv are enabled for NVIDIA Ampere+ GPUs. The resulting loss of precision may hinder MCMC convergence. To turn off, run `tf.config.experimental.enable_tensor_float_32_execution(False)`. For more detail, see https://github.com/tensorflow/community/pull/287.
  'TensorFloat-32 matmul/conv are enabled for NVIDIA Ampere+ GPUs. The '
/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/tensorflow_probability/python/__init__.py:69: UserWarning: TensorFloat-32 matmul/conv are enabled for NVIDIA Ampere+ GPUs. The resulting loss of precision may hinder MCMC convergence. To turn off, run `tf.config.experimental.enable_tensor_float_32_execution(False)`. For more detail, see https://github.com/tensorflow/community/pull/287.
  'TensorFloat-32 matmul/conv are enabled for NVIDIA Ampere+ GPUs. The '
/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/tensorflow_addons/utils/ensure_tf_install.py:67: UserWarning: Tensorflow Addons supports using Python ops for all Tensorflow versions above or equal to 2.3.0 and strictly below 2.6.0 (nightly versions are not supported). 
 The versions of TensorFlow you are currently using is 2.6.5 and is not supported. 
Some things might work, some things might not.
If you were to encounter a bug, do not file an issue.
If you want to make sure you're using a tested and supported configuration, either change the TensorFlow version or the TensorFlow Addons's version. 
You can find the compatibility matrix in TensorFlow Addon's readme:
https://github.com/tensorflow/addons
  UserWarning,
Traceback (most recent call last):
  File "/home/usr/workspace/S-FSVI/main.py", line 8, in <module>
    from notebooks.nb_utils.common import read_config_and_run, show_final_average_accuracy
  File "/home/usr/workspace/S-FSVI/notebooks/nb_utils/common.py", line 39, in <module>
    from cli import run_config
  File "/home/usr/workspace/S-FSVI/cli.py", line 20, in <module>
    from sfsvi.run import run as cl_run
  File "/home/usr/workspace/S-FSVI/sfsvi/run.py", line 23, in <module>
    from benchmarking.method_cl_fsvi import MethodCLFSVI
  File "/home/usr/workspace/S-FSVI/benchmarking/method_cl_fsvi.py", line 17, in <module>
    import optax
  File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/optax/__init__.py", line 18, in <module>
    from optax._src.alias import adabelief
  File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/optax/_src/alias.py", line 18, in <module>
    from optax._src import combine
  File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/optax/_src/combine.py", line 18, in <module>
    from optax._src import transform
  File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/optax/_src/transform.py", line 19, in <module>
    import chex
  File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/chex/__init__.py", line 17, in <module>
    from chex._src.asserts import assert_axis_dimension
  File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/chex/_src/asserts.py", line 26, in <module>
    from chex._src import asserts_internal as _ai
  File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/chex/_src/asserts_internal.py", line 34, in <module>
    from chex._src import pytypes
  File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/chex/_src/pytypes.py", line 36, in <module>
    PRNGKey = jax.random.KeyArray
AttributeError: module 'jax.random' has no attribute 'KeyArray'

Do you know how I can fix this problem?

Thanks

baselines/vcl is identical to vcl/ddm?

Hi Tim,

Thanks for sharing the code - look forward to using it. Just checking if the vcl code under baselines/vcl is the same as in this repo? If yes, perhaps baselines/vcl should be a git submodule, or it should include an ack and link to the original repo.

Cheers,
Thang

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baselines/vcl is identical to vcl/ddm?

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