self.materials is a dict and by default you are iterating over just the keys (which are strings). Since self.materials has more than two keys*, they can’t be unpacked into the tuple “k, m“, hence the ValueError exception is raised. In Python 2.x, to iterate over the keys and the values (the tuple “k, m“), we use self.materials.iteritems(). However, since you’re throwing the key away anyway, you may as … Read more
As the other answer explained, you can’t add hyperlinks in normal messages, but you can in Embeds. I don’t see why you wouldn’t want to use an Embed for an error message, especially considering it adds more functionality, so you should consider using that. Feel free to mess around with the Embed & add some fields, a … Read more
You should use the Post-Redirect-Get pattern. And if you want to pass data to the target function (like that token) you can use the session object to store it So that would break down something like Edit: I haven’t used Flask-JWT before and didn’t know about the post requirement. But you can tell Flask to redirect … Read more
The following worked for me. First install MKL: After this, install pytorch and torchvision:
Here’s a couple of suggestions: Use date_range for the index: Note: we could create an empty DataFrame (with NaNs) simply by writing: To do these type of calculations for the data, use a numpy array: Hence we can create the DataFrame:
As you stated in the comments, some of the values appeared to be floats, not strings. You will need to change it to strings before passing it to re.sub. The simplest way is to change location to str(location) when using re.sub. It wouldn’t hurt to do it anyways even if it’s already a str.
When Python parses the body of a function definition and encounters an assignment such as Python interprets feed as a local variable by default. If you do not wish for it to be a local variable, you must put in the function definition. The global statement does not have to be at the beginning of the function … Read more
As of October 2020: Tensorflow only supports the 64-bit version of Python Tensorflow only supports Python 3.5 to 3.8 So, if you’re using an out-of-range version of Python (older or newer) or a 32-bit version, then you’ll need to use a different version.
It’s likely because there a built-in functions with the same name, abs. The same is true for np.amax, np.amin and np.round_. The aliases for the NumPy functions abs, min, max and round are only defined in the top-level package. So np.abs and np.absolute are completely identical. It doesn’t matter which one you use. There are several advantages to the short names: They are shorter and they are known to Python … Read more