I got the same error today. In previous version of tf, I need to install a Nvidia toolkit to get the file. Here is the right toolkit for the cudart64_110.dll file: https://developer.nvidia.com/cuda-11.3.0-download-archive Then just follow the installation guide. If you need more help or it doesnt work, just write it. solved tensorflow: Could not load … Read more
If you want to increment only the (33*n)th rows, you can do this. awk ‘!(NR%33){$6+=++p} 1’ line 33 will be incremented by 1, line 66 by 2, etc. solved Increment every 33 line of 6 column by 1 [closed]
As you guessed correctly, this has to do with capturing groups. According to the documentation for re.findall: If one or more groups are present in the pattern, return a list of groups Therefore, you need to make all your groups () non-capturing using the (?:) specifier. If there are no captured groups, it will return … Read more
First, do you know about the csv module? If not, read the introduction and examples to the point where you know how to get an iterable of rows. Print each one out, and they’ll look something like this: [‘AVNIVGYSNAQGVDY’, ‘123431’, ‘27.0’, ‘Tetramer’] Or, if you use a DictReader: {‘Epitope’: ‘AVNIVGYSNAQGVDY’, ‘ID’: ‘123431’, ‘Frequency’: ‘27.0’, ‘Assay’: … Read more
Update: Now the situation looks a bit different as you updated the question. Here’s a quick snippet thrown together using pandas and numpy (for the sake of simplicity we replace missing ratings with zero): import numpy as np importport pandas as pd from itertools import combinations df = pd.DataFrame(critics).T.fillna(0) distances = [] for critic1, critic2 … Read more
A minimalist approach: In [1]: l=[[‘a1′,’a2′,’a3’],[‘a4′,’a5′,’a6’],[‘a7′,’a8′,’a9′]] In [2]: from __future__ import print_function In [3]: print(*l,sep=’\n’) [‘a1’, ‘a2’, ‘a3’] [‘a4’, ‘a5’, ‘a6’] [‘a7’, ‘a8’, ‘a9’] solved What is the best way to print this matrix without a for loop [closed]
Sure, you can do: def italic(predecessor): x = predecessor def successor(): return “<italic/>” + x() + “</italic>” return successor Just like you can do: def italic(predecessor): x = predecessor x2 = x def successor(): return “<italic/>” + x2() + “</italic>” return successor or def italic(predecessor): x = predecessor x2 = x x3 = x2 def … Read more
The problem is str function must have been overloaded. Input: X=5 print(“X value is:”+str(X)) Output: X value is:5 Input: X=5 str = “98897” print(“X value is:”+str(X)) Output: TypeError Traceback (most recent call last) in () —-> 1 print(“X value is:”+str(X)) TypeError: ‘str’ object is not callable 1 solved ‘str’ object is not callable – CAUTION: … Read more
generate_data should receive the bound method, not the result of calling the method, as an argument, then call the received argument inside the function: def generate_data(faker_function): return [faker_function() for _ in range(5)] generate_data(Faker().credit_card_number) 4 solved Creating a function that takes another function as an argument
I added empty __init__.py files to Main/, A/, B/, and C/. I also put the following function in each of the .py files just so we had something to call: def f(): print __name__ In main.py, the significant function is get_module, which calls import_module from importlib. import errno from importlib import import_module import os from … Read more
You can use zip with a nested list comprehension: values = [10.5,20.2, 50.0] occ = [3,5,1] result = [x for x, y in zip(values, occ) for _ in range(y)] Alternatively, without using range: result = [elem for x, y in zip(values, occ) for elem in [x] * y] Output: [10.5, 10.5, 10.5, 20.2, 20.2, 20.2, … Read more
As both sets of your data start the same place the following works for idx,i in enumerate(range(4,len(grades_list))): This should fulfill all requirements that Im aware of up to this point def class_avg(open_file): ”'(file) -> list of float Return a list of assignment averages for the entire class given the open class file. The returned list … Read more
As I can see in this page, you need to interact with java script that is invoked by button Go or Next Page button. For Go button you need to fill the textbox each time. You can use different approaches to work around this: 1) Selenium – Web Browser Automation 2) spynner – Programmatic web … Read more
You can define the bins and cuts as follows: bins = [9 * i for i in range(0, df[‘age’].max() // 9 + 2)] cuts = pd.cut(df[‘age’], bins, right=False) print(cuts) 0 [18, 27) 1 [18, 27) 2 [54, 63) 3 [27, 36) 4 [45, 54) Name: age, dtype: category Categories (7, interval[int64, left]): [[0, 9) < … Read more
string= “machine learning”.split() doc_vector = model.infer_vector(string) out= model.docvecs.most_similar([doc_vector]) I’m not sure 100% since I’m using a more recent release, but I think that the issue is connected to the fact that the most_similar function is expecting a string mapped in the feature space and not the raw string. 2 solved Gensim example, TypeError:between str and … Read more