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: ```python 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 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 from cli import run_config File "/home/usr/workspace/S-FSVI/cli.py", line 20, in from sfsvi.run import run as cl_run File "/home/usr/workspace/S-FSVI/sfsvi/run.py", line 23, in from benchmarking.method_cl_fsvi import MethodCLFSVI File "/home/usr/workspace/S-FSVI/benchmarking/method_cl_fsvi.py", line 17, in import optax File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/optax/__init__.py", line 18, in from optax._src.alias import adabelief File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/optax/_src/alias.py", line 18, in from optax._src import combine File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/optax/_src/combine.py", line 18, in from optax._src import transform File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/optax/_src/transform.py", line 19, in import chex File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/chex/__init__.py", line 17, in 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 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 from chex._src import pytypes File "/home/usr/miniconda3/envs/fsvi/lib/python3.7/site-packages/chex/_src/pytypes.py", line 36, in PRNGKey = jax.random.KeyArray AttributeError: module 'jax.random' has no attribute 'KeyArray' ``` Do you know how I can fix this problem? Thanks

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