Hi Eric
1. It seems that I don't have sufficient GPU memory in colab.
I have the following error message:
INFO:colabfold.batch:Running model_1
/usr/local/lib/python3.7/dist-packages/haiku/_src/data_structures.py:195: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.
leaves, structure = jax.tree_flatten(mapping)
/usr/local/lib/python3.7/dist-packages/haiku/_src/data_structures.py:203: FutureWarning: jax.tree_unflatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_unflatten instead.
self._mapping = jax.tree_unflatten(self._structure, self._leaves)
/usr/local/lib/python3.7/dist-packages/haiku/_src/stateful.py:457: FutureWarning: jax.tree_leaves is deprecated, and will be removed in a future release. Use jax.tree_util.tree_leaves instead.
length = jax.tree_leaves(xs)[0].shape[0]
/usr/local/lib/python3.7/dist-packages/alphafold/model/geometry/struct_of_array.py:136: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.
flat_array_like, inner_treedef = jax.tree_flatten(array_like)
/usr/local/lib/python3.7/dist-packages/alphafold/model/geometry/struct_of_array.py:210: FutureWarning: jax.tree_unflatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_unflatten instead.
inner_treedef, data[array_start:array_start + num_array])
/usr/local/lib/python3.7/dist-packages/alphafold/model/mapping.py:50: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.
values_tree_def = jax.tree_flatten(values)[1]
/usr/local/lib/python3.7/dist-packages/alphafold/model/mapping.py:54: FutureWarning: jax.tree_unflatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_unflatten instead.
return jax.tree_unflatten(values_tree_def, flat_axes)
/usr/local/lib/python3.7/dist-packages/alphafold/model/mapping.py:129: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.
flat_sizes = jax.tree_flatten(in_sizes)[0]
ERROR:colabfold.batch:Could not predict af1819. Not Enough GPU memory? INTERNAL: cublas error
INFO:colabfold.batch:Done
Downloading structure predictions to directory Downloads/ChimeraX/AlphaFold
cp: cannot stat '*_relaxed_rank_1_model_*.pdb': No such file or directory
cp: cannot stat '*_unrelaxed_rank_1_model_*_scores.json': No such file or directory
2. Would it be possible to run this in jupyter? Or are there alternatives?
3. " Prediction may fail with total sequence length over 1000 residues due to limited GPU memory." - this total sequence length meaning all the sequences in the list to be concatenated?
4. I seem to also have some pdbxx.m8 and afxxxx.csv files - may I know what these files are for?
Thanks!
-Dennis