tbenst

[13:44:03.327] Log Level: 2
[13:44:03.334] SSH Resolver called for "ssh-remote+jaimie-80g-forward", attempt 1
[13:44:03.334] "remote.SSH.useLocalServer": true
[13:44:03.334] "remote.SSH.useExecServer": false
[13:44:03.334] "remote.SSH.path": undefined
[13:44:03.335] "remote.SSH.configFile": undefined
[13:44:03.335] "remote.SSH.useFlock": true
[13:44:03.335] "remote.SSH.lockfilesInTmp": false
[13:44:03.335] "remote.SSH.localServerDownload": auto
[13:44:03.335] "remote.SSH.remoteServerListenOnSocket": false

tbenst

##
# Dynamic time warping of TTS audio & phoneme textgrids onto T12 audio envelopes.

##
import os, sys, glob
import torch
from tqdm import tqdm
import numpy as np
from textgrids import TextGrid
import torch.nn as nn, scipy

tbenst

run.py(448):             self.define(self._stderr_path, StringSeries([]))
 --- modulename: string_series, funcname: __init__
string_series.py(51):         if is_stringify_value(values):
 --- modulename: __init__, funcname: is_stringify_value
__init__.py(123):     return isinstance(var, StringifyValue)
string_series.py(54):         if not is_collection(values):
 --- modulename: __init__, funcname: is_collection
__init__.py(137):     return isinstance(var, (list, set, tuple))
string_series.py(57):         self._truncated = any([len(value) > MAX_STRING_SERIES_VALUE_LENGTH for value in values])
 --- modulename: string_series, funcname: <listcomp>

tbenst

silly
watermelon
task

tbenst

(base) [tbenst@sh03-ln02 login ~/.vscode-server]$ module load devel
(base) [tbenst@sh03-ln02 login ~/.vscode-server]$ module load valgrind
(base) [tbenst@sh03-ln02 login ~/.vscode-server]$ valgrind -v /home/users/tbenst/.vscode-server/bin/e8a3071ea4344d9d48ef8a4df2c097372b0c5161/bin/code-server
==126986== Memcheck, a memory error detector
==126986== Copyright (C) 2002-2017, and GNU GPL'd, by Julian Seward et al.
==126986== Using Valgrind-3.14.0-353a3587bb-20181007X and LibVEX; rerun with -h for copyright info
==126986== Command: /home/users/tbenst/.vscode-server/bin/e8a3071ea4344d9d48ef8a4df2c097372b0c5161/bin/code-server
==126986== 
--126986-- Valgrind options:
--126986--    -v

tbenst

with import <nixpkgs> {};
let
  d = version: "v${lib.concatStringsSep "." (lib.take 2 (lib.splitString "." version))}";
  extraLibs = [
    # IJulia.jl
    mbedtls
    zeromq3
    # ImageMagick.jl
    imagemagickBig
    # HDF5.jl

tbenst

error: while evaluating the attribute 'buildCommand' of the derivation 'home-manager-generation' at /Computer/nixpkgs/pkgs/stdenv/generic/make-derivation.nix:201:11:
while evaluating the attribute 'text' of the derivation 'activation-script' at /Computer/nixpkgs/pkgs/stdenv/generic/make-derivation.nix:201:11:
while evaluating 'mkCmd' at /Computer/home-manager/modules/home-environment.nix:519:17, called from undefined position:
while evaluating the attribute 'data' at /Computer/home-manager/modules/lib/dag.nix:91:37:
while evaluating the attribute 'data' at /Computer/home-manager/modules/lib/dag.nix:85:9:
while evaluating the attribute 'data' at undefined position:
while evaluating 'g' at /Computer/nixpkgs/lib/attrsets.nix:298:19, called from undefined position:
while evaluating anonymous function at /Computer/nixpkgs/lib/modules.nix:140:72, called from /Computer/nixpkgs/lib/attrsets.nix:301:20:
while evaluating the attribute 'value' at /Computer/nixpkgs/lib/modules.nix:525:9:
while evaluating the option `home

tbenst

To whom it may concern,

I wanted to follow up on my previous emails.

My understanding after consulting with others is that what we do in the nixpkgs derivation for CUDA does not preclude binary caching & redistribution, as we only modify the library metadata such as the dynamic section (i.e. DT_RUNPATH, setting interpreter, setting RPATH). As I understand, object code refers to machine code that is executed by the processor, and thus my understanding is that we leave the object code untouched. I previously shared these post-distribution patches on 2/3/2020 for your review.

Furthermore, my understanding under Section 2.3 is that we are ok to redistribute the SDK in full as long as this redistribution only happens under Linux.

Thus, we plan on proceeding with setting up a binary cache for distributing CUDA and packages requiring CUDA using nixpkgs.

tbenst

📂 HDF5.Group: /processing/ophys/ImageSegmentation (file: /scratch/b115/2021-06-08_rsChRmine_h2b6s/fish2/s2p/suite2p/ophys.nwb)
├─ 🏷️ namespace
├─ 🏷️ neurodata_type
├─ 🏷️ object_id
└─ 📂 PlaneSegmentation
   ├─ 🏷️ colnames
   ├─ 🏷️ description
   ├─ 🏷️ namespace
   ├─ 🏷️ neurodata_type
   ├─ 🏷️ object_id

tbenst

Initialized empty Git repository in /tmp/git-checkout-tmp-vaXNThI6/pytorch/.git/
From https://github.com/pytorch/pytorch
 * branch            HEAD       -> FETCH_HEAD
Switched to a new branch 'fetchgit'
Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16'
Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv'
Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK'
Submodule 'third_party/QNNPACK' (https://github.com/pytorch/QNNPACK) registered for path 'third_party/QNNPACK'
Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark'
Submodule 'third-party/cpuinfo' (https://github.com/Maratyszcza/cpuinfo.git) registered for path 'third_party/cpuinfo'