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Reference energies implemented in sparse-dispatch framework; entirely python

Torch 2.5.0, 2.5.1, and 2.7 also seem to work just fine for tmol; Torch 2.4 does not work.

Also updating the code relying on cattrs.structure

The newest versions of cattrs (>=24.1.0) throw errors that previously were
not errors or that could be worked around or something so that now
the code in tmol/chemical/restypes.py produces errors that weren't
there before.

One small issue: numpy.array cannot be used as a type name for attrs
and this produces a weird complaint out of cattrs. numpy.array is
for creating ndrarrays; ndarrays are the types, array is the function
Nicely enough, termini variants are being properly handled
already; the tests simply had to be updated.
Now the sampler is responsible for mapping their samples onto the
DOFs that define the conformations, allowing samplers to define more
than only the chi DOFs for the samples; e.g., if I want to build
hydroxyl rotamers onto the heavy-atom coordinates of an existing SER
This code is "used" by the on-the-fly RPE calculation code
which itself is not really used
This allows me to talk about global-block-type index (not a great name)
when building rotamers for disallowed block types as will happen
when a block has all of its block-types disallowed.
Pack rotamers is now agreeing with the final energy after scoring
This includes a bug in neighbor detection that was allowing the
first rotamer from pose i+1 to get checked as a neighbor with
rotamers of the last residue of pose i!
* Update modern GPU to CUDA13 compatibility (See moderngpu/moderngpu#56)
* Add conda/mamba-installed nvtx to search path
* Update NVidia conda channel to  torch 2.8.0 for CUDA 13 compatibility
* Add nvtx to conda packages
* Fix broken unit test enable_tensor_view that lead to a "Illegal Operation" error
* Change error-propogation command location in "linting" script until after conda activation
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