Added a conda_env.yaml file that locks tested package versions.
Problem:
h5py_cache is deprecated with its functionality built-in to h5py. Currently h5py_cache packages installed from pip has some conflict with numpy versions. I recommed removing this dependency in favor of using h5py directly.
Traceback (most recent call last):
File "record_sim_episodes.py", line 189, in <module>
main(vars(parser.parse_args()))
File "record_sim_episodes.py", line 161, in main
with h5py_cache.File(dataset_path + '.hdf5', 'w', chunk_cache_mem_size=1024 ** 2 * 2) as root:
File "/local/crv/cchi/mambaforge/envs/aloha/lib/python3.8/site-packages/h5py_cache/__init__.py", line 67, in File
bytes_per_object = np.dtype(np.float).itemsize # assume float as most likely
File "/local/crv/cchi/mambaforge/envs/aloha/lib/python3.8/site-packages/numpy/__init__.py", line 305, in __getattr__
raise AttributeError(__former_attrs__[attr])
AttributeError: module 'numpy' has no attribute 'float'.
`np.float` was a deprecated alias for the builtin `float`. To avoid this error in existing code, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
Changes:
Problem: h5py_cache is deprecated with its functionality built-in to h5py. Currently h5py_cache packages installed from pip has some conflict with numpy versions. I recommed removing this dependency in favor of using h5py directly.