Microsoft Visual C#
7th Edition
ISBN: 9781337102100
Author: Joyce, Farrell.
Publisher: Cengage Learning,
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Chapter 9, Problem 2CP
Program Plan Intro
Program Plan:
- The class Mural is defined which has a data type custName of type string, code of type char, descrp of type string and two static arrays muralCode and muralDescription.
- Inside MarshallRevenue programfollowing functions are used:
- getMonth(), getMural(), and getRevenue()to get month, number of murals and revenue generated from all murals.
- Inside main method of MarshallRevenue program following variables are used:
- month, exteriorMurals, andinteriorMuralstostore the month and number of interior and exterior murals.
- An array of object of class Mural is declared of size equal to number of total exterior and interior murals.
- A for loop is used to set code and custName property of each array object.
- A for loop is used to read and display the customers names belonging to each mural category.
Program Description:
The main purpose of the program is to implement the mural class and use this class inside the MarshallRevenue program.
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Here are two diagrams. Make them very explicit, similar to Example Diagram 3 (the Architecture of MSCTNN).
graph LR subgraph Teacher_Model_B [Teacher Model (Pretrained)] Input_Teacher_B[Input C (Complete Data)] --> Teacher_Encoder_B[Transformer Encoder T] Teacher_Encoder_B --> Teacher_Prediction_B[Teacher Prediction y_T] Teacher_Encoder_B --> Teacher_Features_B[Internal Features F_T] end subgraph Student_B_Model [Student Model B (Handles Missing Labels)] Input_Student_B[Input C (Complete Data)] --> Student_B_Encoder[Transformer Encoder E_B] Student_B_Encoder --> Student_B_Prediction[Student B Prediction y_B] end subgraph Knowledge_Distillation_B [Knowledge Distillation (Student B)] Teacher_Prediction_B -- Logits Distillation Loss (L_logits_B) --> Total_Loss_B Teacher_Features_B -- Feature Alignment Loss (L_feature_B) --> Total_Loss_B Partial_Labels_B[Partial Labels y_p] -- Prediction Loss (L_pred_B) --> Total_Loss_B Total_Loss_B -- Backpropagation -->…
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)…
Chapter 9 Solutions
Microsoft Visual C#
Ch. 9 - Assume that you have created a class named...Ch. 9 - Prob. 9RQCh. 9 - Assume that you have created a class named...Ch. 9 - Create an application named SalesTransactionDemo...Ch. 9 - Create an application named CarDemo that declares...Ch. 9 - Create a program named SalesTaxDemo that declares...Ch. 9 - Prob. 8ECh. 9 - Write a program named DemoJobs for Harolds Home...Ch. 9 - a. Write a FractionDemo program that instantiates...Ch. 9 - Prob. 1DE
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