Exception: An exception is a problem that creates during the execution of a program; it offers a method to transfer control from one part to another part of a program. An exception handling is created by using the following three keywords such as try, catch and throw. The “try” block have the program for the basic algorithm that says the computer what to do when all goes well. The “throw” keyword throws an error statement to the “catch” block. The “catch” block will catch the exception or handling the exception. Generally, the compiler executes “try” block. In the “try” block, if the statements cause an exception, it throws an error statement to the “catch” block using the keyword “throw”. The “catch” block then handles the error based upon the type of exception.

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Chapter 16.1, Problem 7STE

Program Plan Intro

Exception:

An exception is a problem that creates during the execution of a program; it offers a method to transfer control from one part to another part of a program.

An exception handling is created by using the following three keywords such as try, catch and throw.

The “try” block have the program for the basic algorithm that says the computer what to do when all goes well.

The “throw” keyword throws an error statement to the “catch” block.

The “catch” block will catch the exception or handling the exception.

Generally, the compiler executes “try” block. In the “try” block, if the statements cause an exception, it throws an error statement to the “catch” block using the keyword “throw”. The “catch” block then handles the error based upon the type of exception.

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Please provide me with the output image of both of them . below are the diagrams code I have two diagram : first diagram code graph LR subgraph Teacher Model (Pretrained) Input_Teacher[Input C (Complete Data)] --> Teacher_Encoder[Transformer Encoder T] Teacher_Encoder --> Teacher_Prediction[Teacher Prediction y_T] Teacher_Encoder --> Teacher_Features[Internal Features F_T] end subgraph Student_A_Model[Student Model A (Handles Missing Values)] Input_Student_A[Input M (Data with Missing Values)] --> Student_A_Encoder[Transformer Encoder E_A] Student_A_Encoder --> Student_A_Prediction[Student A Prediction y_A] Student_A_Encoder --> Student_A_Features[Student A Features F_A] end subgraph Knowledge_Distillation_A [Knowledge Distillation (Student A)] Teacher_Prediction -- Logits Distillation Loss (L_logits_A) --> Total_Loss_A Teacher_Features -- Feature Alignment Loss (L_feature_A) --> Total_Loss_A Ground_Truth_A[Ground Truth y_gt] -- Prediction Loss (L_pred_A)…