autograder | The ag | Email library

As @iz_ suggests, you have an infinite loop in your code. This code:

Your array is a size and count.

Use max and then for tuples zip divided column and convert to list:

As mentioned in the comments, your code has a lot of redundant variables - this is a tidied up version of your code - it should work exactly the same as yours :

I think the biggest issue is that your code prints the count line, and then returns the indices line. If the autograder simply executes your function and ignores the return value it will ignore the indices. Note that the example code you cite prints both lines - and doesn't return anything. This is corrected in the version below.

Note that this code uses enumerate - it is a very good function to get into the habit of using if you need the contents of a list and you need to track the index in the list too.

An unsafe way to do this would be to use eval or look at the globals() dictionary. A slightly safer way would be to create a string-to-function mapping in a dictionary, and look up the function from the mapping.

Your line:

I edited your code like below. I think your task is to find numbers next to X-DSPAM-Confidence:. And i used your code to identify the X-DSPAM-Confidence: line. Then I splitted the string by ':' then I took the 1st index and I converted to float.

Sadly, you can't use if var == "foo" or "bar"; you'd have to write if var == "foo" or var == "bar". For your function, try something like:

PyTorch allows tensor to be a "view" of an existing tensor, such that it shares the same underlying data with its base tensor, thus avoiding explicit data copy to be able to perform fast and memory efficient operations.

As mentioned in the Tensor View docs,

When accessing the contents of a tensor via indexing, PyTorch follows Numpy behaviors that basic indexing returns views, while advanced indexing returns a copy.

In your example, c = a[:, 2:3] is basic indexing, while, c = a[:, [2]] is advanced indexing. That's why a view is created in the first case only. Thus, .storage().data_ptr() gives same result.

You can read about basic and advanced indexing in Numpy indexing docs.

Advanced indexing is triggered when the selection object, obj, is a non-tuple sequence object, an ndarray (of data type integer or bool), or a tuple with at least one sequence object or ndarray (of data type integer or bool).