Homework 1 PyTorch

BME646 and ECE60146: Homework 1
1 Introduction
The goal of this homework is to improve your understanding of the Python
Object-Oriented (OO) code in general, especially with regard to how it is
used in PyTorch. This is the only homework you will get on general Python
OO programming. Future homework assignments will be specific to using
PyTorch classes directly or your own extensions of those classes for creating
your DL solutions.
Note that you should use Python 3.x and not Python 2.x for this and
all future programming assignments. For the Python-related knowledge required in this homework, refer to Prof. Kak’s tutorial on OO Python [1].
2 Programming Tasks
1. Create a class named Sequence with an instance variable named array
as shown below:
1 class Sequence ( object ):
2 def __init__ ( self , array ):
3 self . array = array
The input parameter array is expected to be a list of numbers, e.g.
[ 0, 1, 2]. This class will serve as the base class for the subclasses
later in this assignment.
2. Now, extend your Sequence class into a subclass called Fibonacci,
with its __init__ method taking in two input parameters: first_value
and second_value. These two values will serve as the first two numbers in your Fibonacci sequence.
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3. Further expand your Fibonacci class to make its instances callable.
More specifically, after calling an instance of the Fibonacci class with
an input parameter length, the instance variable array should store
a Fibonacci sequence of that length and with the two aforementioned
starting numbers. In addition, calling the instance should cause the
computed Fibonacci sequence to be printed. Shown below is a demonstration of the expected behaviour described so far:
1 FS = Fibonacci ( first_value =1 , second_value =2 )
2 FS ( length =5 ) # [1, 2, 3, 5, 8]
4. Modify your class definitions so that your Sequence instance can be
used as an iterator. For example, when iterating through an instance
of Fibonacci, the Fibonacci numbers should be returned one-by-one.
The snippet below illustrates the expected behavior:
1 FS = Fibonacci ( first_value =1 , second_value =2 )
2 FS ( length =5 ) # [1, 2, 3, 5, 8]
3 print (len( FS ) ) # 5
4 print ([n for n in FS]) # [1, 2, 3, 5, 8]
5. Make another subclass of the Sequence class named Prime. As the
name suggests, the new class is identical to Fibonacci except that
the array now stores consecutive prime numbers. Modify the class
definition so that its instance is callable and can be used as an iterator.
What is shown below illustrates the expected behavior:
1 PS = Prime ()
2 PS ( length =8 ) # [2, 3, 5, 7, 11 , 13 , 17 , 19]
3 print (len( PS ) ) # 8
4 print ([n for n in PS]) # [2, 3, 5, 7, 11 , 13 , 17 , 19]
6. Finally, modify the base class Sequence such that two sequence instances of the same length can be compared by the operator > . Invoking (A > B) should compare element-wise the two arrays and return
the number of elements in A that are greater than the corresponding
elements in B. If the two arrays are not of the same size, your code
should throw a ValueError exception. Shown below is an example:
1 FS = Fibonacci ( first_value =1 , second_value =2 )
2 FS ( length =8 ) # [1, 2, 3, 5, 8, 13 , 21 , 34]
3 PS = Prime ()
4 PS ( length =8 ) # [2, 3, 5, 7, 11 , 13 , 17 , 19]
5 print ( FS > PS ) # 2
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7 PS ( length =5 ) # [2, 3, 5, 7, 11]
8 print ( FS > PS ) # will raise an error
9 # Traceback ( most recent call last ):
10 # ...
11 # ValueError : Two arrays are not equal in length !
3 Submission Instructions
Include a typed report explaining how did you solve the given programming
tasks.
1. Turn in a zipped file, it should include (a) a typed self-contained pdf
report with source code and results and (b) source code files (only .py
files are accepted). Rename your .zip file as hw1 <First Name><Last
Name>.zip and follow the same file naming convention for your pdf
report too.
2. For this homework, you are encouraged to use .ipynb for development
and the report. If you use .ipynb, please convert it to .py and submit
that as source code.
3. You can resubmit a homework assignment as many times as you want
up to the deadline. Each submission will overwrite any previous
submission. If you are submitting late, do it only once on
BrightSpace. Otherwise, we cannot guarantee that your latest submission will be pulled for grading and will not accept related regrade
requests.
4. The sample solutions from previous years are for reference only. Your
code and final report must be your own work.
5. Your pdf must include a description of
• Reproductions of the outputs for each of the provided snippets
above with the given parameters.
• Correct outputs for each of the provided snippets above with
input parameters of your choice.
• Your source code. Make sure that your source code files are
adequately commented and cleaned up.
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References
[1] Python OO for DL. URL https://engineering.purdue.edu/
DeepLearn/pdf-kak/PythonOO.pdf.
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