ceshine

class STLR(torch.optim.lr_scheduler._LRScheduler):
    def __init__(self, optimizer, max_mul, ratio, steps_per_cycle, decay=1, last_epoch=-1):
        self.max_mul = max_mul - 1
        self.turning_point = steps_per_cycle // (ratio + 1)
        self.steps_per_cycle = steps_per_cycle
        self.decay = decay
        super().__init__(optimizer, last_epoch)

    def get_lr(self):
        residual = self.last_epoch % self.steps_per_cycle

harveyslash

class ContrastiveLoss(torch.nn.Module):
    """
    Contrastive loss function.
    Based on: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf
    """

    def __init__(self, margin=2.0):
        super(ContrastiveLoss, self).__init__()
        self.margin = margin

cachapa

#!/bin/bash
# Based on http://blog.pkh.me/p/21-high-quality-gif-with-ffmpeg.html
# Requires ffmpeg

filename="${1%.*}"
palette="/tmp/palette.png"
filters="scale=320:-1:flags=lanczos"

ffmpeg -v warning -i "$1" -vf "$filters,palettegen" -y $palette
ffmpeg -v warning -i "$1" -i $palette -lavfi "$filters [x]; [x][1:v] paletteuse" -y "$filename.gif"

frankrowe

 import shapefile
   # read the shapefile
   reader = shapefile.Reader("my.shp")
   fields = reader.fields[1:]
   field_names = [field[0] for field in fields]
   buffer = []
   for sr in reader.shapeRecords():
       atr = dict(zip(field_names, sr.record))
       geom = sr.shape.__geo_interface__
       buffer.append(dict(type="Feature", \