iterator

return next(self._sampler_iter) # may raise StopIteration Question: Instead of using enumerate(data loader) for some reason, I am creating iterator for the data loader. In the while loop shown below, it gives me StopIteration error. Minimalistic code that depicts the cause: loader = DataLoader(dataset, batch_size=args.batch_size) dataloader_iter = iter(loader) while(dataloader_iter): X, y = next(dataloader_iter) … What would …

Does next() eliminate values from a generator? Question: I’ve written a generator that does nothing more or less than store a range from 0 to 10: result = (num for num in range(11)) When I want to print values, I can use next(): print(next(result)) [Out]: 0 print(next(result)) [Out]: 1 print(next(result)) [Out]: 2 print(next(result)) [Out]: 3 …

What does next() and iter() do in PyTorch's DataLoader() Question: I have the following code: import torch import numpy as np import pandas as pd from torch.utils.data import TensorDataset, DataLoader # Load dataset df = pd.read_csv(r’../iris.csv’) # Extract features and target data = df.drop(‘target’,axis=1).values labels = df[‘target’].values # Create tensor dataset iris = TensorDataset(torch.FloatTensor(data),torch.LongTensor(labels)) # …

Why iterators and generators are hashable? Question: As title. I mean, you can invoke next(obj) and point to the next element. So the internal state of the iterable or generator will change. Why they are hashable? Asked By: Marco Sulla || Source Answers: While the internal state of the generator can change, the generator as …

Inspecting zipped data seems to erase it Question: When I inspect my zipped data, it acts as if it has been erased. First, create zip object: numbers = [1, 2, 3] letters = [‘a’, ‘b’, ‘c’] numbers_letters = zip(numbers, letters) print(list(numbers_letters)) As expected you see the list containing the tuples: [(1, ‘a’), (2, ‘b’), (3, …

Using iterator for slicing an array Question: I was looking at this python code that I need some explanation with: arr = [0, 0, 0, 0, 1, 2, 3, 4,5] arr = arr[next((i for i, x in enumerate(arr) if x != 0), len(arr)):] This code would remove the leading zeroes from the array, I am …

retrieving the next element from tf.data.Dataset in tensorflow 2.0 beta Question: Before tensorflow 2.0-beta, to retrieve the first element from tf.data.Dataset, we may use a iterator as shown below: #!/usr/bin/python import tensorflow as tf train_dataset = tf.data.Dataset.from_tensor_slices([1.0, 2.0, 3.0, 4.0]) iterator = train_dataset.make_one_shot_iterator() with tf.Session() as sess: # 1.0 will be printed. print (sess.run(iterator.get_next())) In …

Why can you not create a dictionary from an enumerated data set after you print it? Question: I was practising with enumerate() and dictionaries in python. When I do not print out the enumerated data I am able to create a dictionary from the enumerated data. But when I do print out the enumerated data, …

How to turn a list of iterators into all possible lists using those iterators Question: I have a list of iterators, such as l = [range(1), range(2), range(3)] and each iterator iterates over the possibilities that could be in that slot. However, I don’t know how long the list is going to be. In this …

map in Python 3 vs Python 2 Question: I’m a Python newbie reading an old Python book. It’s based on Python 2, so sometimes I got little confused about detail. There is a code L=map(lambda x:2**x, range(7)) so it doesn’t return the list in python 3, and I googled it and found that list(L) works. …