I want the solution in Python language

Part 1: a) Check the code from mnist_mlp,py and run it. b) Leave it with only one hidden layer, remove the dropouts and run it again. c) Change the activation of the hidden layer to a "sigmoi d, the loss function to mse (mean squared error). d) Change the optimization algorithm to "sgd" (Stochastic Gradient Descent). Part 2: a) Check the code from mnist cnn.py and run it. b) Add a Max Poo 11D layer after the first convolutional layer, and a dropout of 25% after it. Also, change the optimization algorithm to "adam". Part 3: a) Check the code from lstm. text generation.py and run it. b) Change the length of the inputs to 80 characters. c) Change the length back to its original size and load the previously trained model, with the following syntax: model. load_weights ('model_latm_text.h.')