Starting Out with Python (3rd Edition)
3rd Edition
ISBN: 9780133582734
Author: Tony Gaddis
Publisher: PEARSON
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Textbook Question
Chapter 3.4, Problem 13CP
Convert the following code to an if-elif-else statement:
if number == 1:
print('One')
else:
if number == 2:
print('Two')
else:
if number == 3:
print('Three')
else:
print('Unknown')
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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 3 Solutions
Starting Out with Python (3rd Edition)
Ch. 3.1 - What is a control structure?Ch. 3.1 - What is a decision structure?Ch. 3.1 - Prob. 3CPCh. 3.1 - Prob. 4CPCh. 3.1 - What types of relationships between values can you...Ch. 3.1 - Write an if statement that assigns 0 to x if y is...Ch. 3.1 - Write an if statement that assigns 0.2 to...Ch. 3.2 - Prob. 8CPCh. 3.2 - What statement do you use in Python to write a...Ch. 3.2 - When you write an if-else statement, under what...
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