jph00

#!/usr/bin/env bash
###
# NB: You probably don't want this gist any more.
#     Instead, use this version from `fastsetup`:
#     https://github.com/fastai/fastsetup/blob/master/setup-conda.sh
###

set -e

cd

jonashaag

Moved to https://github.com/jonashaag/audio-resampling-in-python

scottire

import numpy as np
import panel as pn
import holoviews as hv 
hv.extension("bokeh")
# hv.extension('matplotlib')
from holoviews.streams import Stream, Params
from scipy.io import wavfile
from scipy.signal import spectrogram

rate, data = wavfile.read('/filepath.wav')

rocking5566

import numpy as np
import tensorflow as tf
from tensorflow.keras.datasets import mnist
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Activation, Conv2D, Flatten
from tensorflow.keras.optimizers import RMSprop

# download the mnist to the path '~/.keras/datasets/' if it is the first time to be called
# X shape (60,000 28x28), y shape (10,000, )

max-mapper

# in zenodo ui create a deposition. get the id

curl -H "Accept: application/json" -H "Authorization: Bearer $TOKEN" "https://www.zenodo.org/api/deposit/depositions/$DEPOSITION"
# get the bucket id from above 

curl --progress-bar -o /dev/null --upload-file ./$FILE https://www.zenodo.org/api/files/$BUCKET/$FILE?access_token=$TOKEN

apaszke

import sys
from collections import OrderedDict

PY2 = sys.version_info[0] == 2
_internal_attrs = {'_backend', '_parameters', '_buffers', '_backward_hooks', '_forward_hooks', '_forward_pre_hooks', '_modules'}


class Scope(object):
    def __init__(self):
        self._modules = OrderedDict()

Mahedi-61

#!/bin/bash

### steps ####
# Verify the system has a cuda-capable gpu
# Download and install the nvidia cuda toolkit and cudnn
# Setup environmental variables
# Verify the installation
###

### to verify your gpu is cuda enable check

f0k

MIT License

Copyright (c) 2017 Jan Schlüter

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

sonots

Usually, located at /usr/local/cuda/bin

Non-Visual Profiler

$ nvprof python train_mnist.py

I prefer to use --print-gpu-trace.

joyrexus

collapsible markdown?

CLICK ME

yes, even hidden code blocks!

print("hello world!")