(Written in Python shell) >>> o = object() >>> o.test = 1 Traceback (most recent call last): File "<pyshell#45>", line 1, in <module> o.test = 1 AttributeError: 'object' object has no attribute 'test' >>> class test1: pass >>> t = test1() >>> t.test Traceback (most recent call last): File "<pyshell#50>", line 1, in <module> t.test … Read more
I had a file called example_file.py, which I wanted to use from various other files, so I decided to add example_file.py to sys.path and import this file in another file to use the file. To do so, I ran the following in IPython.
I’m using functions so that my program won’t be a mess but I don’t know how to make a local variable into global. Answers: Thank you for visiting the Q&A section on Magenaut. Please note that all the answers may not help you solve the issue immediately. So please treat them as advisements. If you … Read more
What is the standard way of making a class comparable in Python 3? (For example, by id.)
I want to upload a file and store it in the database. I created a LargeBinary column.
from selenium import webdriver; browser= webdriver.Firefox(); browser.get('http://www.seleniumhq.org'); When I try to run this code, it gives me an error message: Expected browser binary location, but unable to find binary in default location, no 'moz:firefoxOptions.binary' capability provided, and no binary flag set on the command line. Any thoughts-highly appreciated! Answers: Thank you for visiting the Q&A … Read more
I am wondering if there is a way that I can use different learning rate for different layers like what is in Caffe. I am trying to modify a pre-trained model and use it for other tasks. What I want is to speed up the training for new added layers and keep the trained layers at low learning rate in order to prevent them from being distorted. for example, I have a 5-conv-layer pre-trained model. Now I add a new conv layer and fine tune it. The first 5 layers would have learning rate of 0.00001 and the last one would have 0.001. Any idea how to achieve this?
How do I use type hints to annotate a function that returns an Iterable that always yields two values: a bool and a str? The hint Tuple[bool, str] is close, except that it limits the return value type to a tuple, not a generator or other type of iterable.
My views.py has become too big and it’s hard to find the right view.
I’m trying to write a code that converts a user-inputted integer into its Roman numeral equivalent. What I have so far is: