This creates an anonymous subclass of HashMap, whose instance initializer puts these values. (By the way, a map can't contain twice the same value, your second put will overwrite the first one. I'll use different values for the next examples.) The normal way would be this (for a ...
Easy to learn. Python’s readability makes it relatively easy for beginners to pick up the language and understand what the code is doing. Versatility. Python is not limited to one type of task; you can use it in many fields. Whether you're interested in web development, automating tasks,...
Figure 1. Satellite imagery to map translation using Pix2Pix In this guide, we will focus on Pix2Pix [1], which is one of the famous and sucessful deep learning models used for paired image translation. In geospatial sciences, this approach could help in wide range of applications tradition...
roles can be quite varied. Not only that, but you also could use Python as a back-end web developer, data scientist, quality assurance engineer or systems engineer. Each of these jobs requires different knowledge on how to use Python and common tooling to fulfill the responsibilities of the ...
9. Use Absolute Path If the alias still doesn’t work, you can use the absolute path to thepython3executable. Find it using which python3, and then set the alias with that path: aliaspython='/absolute/path/to/python3'
Python’s readability makes it relatively easy for beginners to pick up the language and understand what the code is doing. Versatility. Python is not limited to one type of task; you can use it in many fields. Whether you're interested in web development, automating tasks, or diving into...
Upsampling in CNN might be new to those of you who are used to classification and object detection architecture, but the idea is fairly simple. The intuition is that we would like to restore the condensed feature map to the original size of the input image, therefore we expand the feature ...
To get the most out of this tutorial, you should have a basic understanding of Python dictionaries, know how to use Python for loops, and be familiar with comprehensions. Knowing other tools like the built-in map() and filter() functions, as well as the itertools and collections modules, ...
Then I want to use data parallelism and do not use model parallelism, just like DDP. The load_in_8bit option in .from_pretrained() requires setting device_map option. With device_map='auto', it seems that the model is loaded on several gpus, as in naive model parallelism, which ...
UPDATE: In Python 3, there is no iteritems. You can replace encode with this: def encode(self, o): result = super(NoIndentEncoder, self).encode(o) for k, v in iter(self._replacement_map.items()): result = result.replace('"@@%s@@"' % (k,), v) return result S...