| import numpy as np | |
| import torch | |
| from torch import nn | |
| from torch import Tensor | |
| from torch.func import functional_call | |
| import torchopt | |
| import matplotlib.pyplot as plt | |
| class SimpleNN(nn.Module): |
| module Euclid | |
| import Syntax.PreorderReasoning | |
| %default total | |
| Divides : (divisor, dividend : Nat) -> Type | |
| Divides d n = (q : Nat ** (n = q * d)) | |
| data Direction = LTR | RTL |
| #!/bin/bash | |
| ## Entrypoint for docker RUN directives as well as ENTRYPOINT with conda env | |
| ## Enable by adding: | |
| ## COPY entry.sh ./ | |
| ## SHELL ["/entry.sh", "/bin/bash", "-c"] | |
| ## | |
| ## Optionally, set the following env to select a conda env to run in | |
| ## ENV CONDA_DEFAULT_ENV=foo | |
| ## You may also want to add something like | |
| ## RUN conda init bash && echo 'conda activate "${CONDA_TARGET_ENV:-base}"' >> ~/.bashrc |
| type | |
| MaybeKind = enum Just, Nothing | |
| Maybe[T] = object | |
| case kind: MaybeKind | |
| of Just: value: T | |
| of Nothing: discard | |
| EitherKind = enum Left, Right | |
| Either[L, R] = object | |
| case kind: EitherKind |
rr is a great debugging tool. it records a trace of a program's execution, as well as the results of
any syscalls it executes, so that you can "rewind" while you debug, and get deterministic forward and reverse
instrumented playback. it works with rust, but by default if you try it out, it could be pretty ugly when you
inspect variables. if this bothers you, configure gdb to use a rust pretty-printer
rr is probably in your system's package manager.
| FILES=*.rst | |
| for f in $FILES | |
| do | |
| filename="${f%.*}" | |
| echo "Converting $f to $filename.md" | |
| `pandoc $f -f rst -t markdown -o $filename.md` | |
| done |
| import sys | |
| from rdkit import Chem | |
| from rdkit.Chem import AllChem, TorsionFingerprints | |
| from rdkit.ML.Cluster import Butina | |
| def gen_conformers(mol, numConfs=100, maxAttempts=1000, pruneRmsThresh=0.1, useExpTorsionAnglePrefs=True, useBasicKnowledge=True, enforceChirality=True): | |
| ids = AllChem.EmbedMultipleConfs(mol, numConfs=numConfs, maxAttempts=maxAttempts, pruneRmsThresh=pruneRmsThresh, useExpTorsionAnglePrefs=useExpTorsionAnglePrefs, useBasicKnowledge=useBasicKnowledge, enforceChirality=enforceChirality, numThreads=0) | |
| return list(ids) | |
Let's compile midipix from source and play with it!
| -- with regards to: http://stackoverflow.com/questions/32630035/replicating-numpys-advanced-indexing-slicing-in-haskell | |
| -- let's create some tensors: | |
| -- 5 rows, 4 columns | |
| two_d_matrix = | |
| [ | |
| [ | |
| 0 | |
| | _ <- [0..3]] |
