An object … As you have learned in the Python Classes/Objects chapter, all classes have a function called __init__(), which allows you to do some initializing when the object is being created.. A generator object can act like an iterator , and can be used wherever an iterator can be used . What is next to the . Iterator in Python is simply an object that can be iterated upon. The __iter__() function returns an iterator object that goes through the each element of the given object. It is thus not uncommon, to have slightly different results for the same input data. I'm sorry you're having an issue. The underlying C implementation uses a random number generator to select features when fitting the model. however when I try to print a field I get the following error TypeError: 'generator' object has no attribute '__getitem__' Tag: python , python-2.7 , dictionary , yield , yield-return I have written a generating function that should return a dictionary. Create an Iterator. Technically speaking, a Python iterator object must implement two special methods, __iter__() and __next__(), collectively called the iterator protocol. The next element can be accessed through __next__() function. an iterator is created by using the iter function , while a generator object is created by either a generator function or a generator expression . To create an object/class as an iterator you have to implement the methods __iter__() and __next__() to your object. I have no problems running the code on my end. Thomas An object which will return data, one element at a time. The map() function works by calling iter() on its second argument, advancing this iterator with next() until the iterator is exhausted, and applying the function passed to its first argument to the value returned by next() at each step. You can try removing the function threadsafe_generator and remove all of the @threadsafe_generator's and see if this helps, although then your generators won't be threadsafe :) If that happens, try with a smaller tol parameter. model(xb). they're used to gather information about the pages you visit and how many clicks you need to accomplish a task. Iterator vs generator object. ?Probably, your model is on the GPU but the input image is on CPU. The first object used brackets to build a list, while the second created a generator expression by using parentheses. Predict output may not match that of … In any case, the original object is not modified. Analytics cookies. In the case of callable object and sentinel value, the iteration is done until the value is found or the end of elements reached. Profiling Generator Performance. In the above example, len() is called on each element of ['abc', 'de', 'fghi'] to return an iterator over the lengths of each string in the list. There is add_scalar (singular, so no s at the end) that would seem to work roughly like you want (except for the .eval() in there). You are calling add_scalars (plural) which takes name/value pairs in form of a dict if you want to add several.. Best regards. The output confirms that you’ve created a generator object and that it is distinct from a list. We use analytics cookies to understand how you use our websites so we can make them better, e.g. You learned earlier that generators are a great way to optimize memory.