Problem $2(6$ Points$)$:

Train the model on the training data with batch$\_$size$=128$ and epochs$=2$ then return the trained model along with the training accuracy $.$

HINT $1$: To calculate the training accuracy use evaluate function with trainning data.

HINT $2$: Train the model with validation$\_$data$=($testing$\_$data$)$Train the model on the training data with batch$\_$size$=128$ and epochs$=2$ then return the trained model along with the training accuracy $.$ Problem $2(6$ Points$)$:

Train the model on the training data with batch$\_$size$=128$ and epochs$=2$ then return the trained model along with the training accuracy $.$

HINT $1$: To calculate the training accuracy use evaluate function with trainning data.

HINT $2$: Train the model with validation$\_$data$=($testing$\_$data$)$

HINT $1$: To calculate the training accuracy use evaluate function with trainning data.

HINT $2$: Train the model with validation$\_$data$=($testing$\_$data$)$ # Function $2$: Train the model

def train$\_$model$($model$,$ x$\_$train, y$\_$train, x$\_$test, y$\_$test$)$:

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input:

model: a compiled CNN model with input of size $(28,28,1)$ and output of size $10$

x$\_$train: an array of training dataset

y$\_$train: an array of the labels for the inputs in array x$\_$train

x$\_$test: an array of validation dataset. This validation dataset is used during the training of the model

y$\_$test: an array of the labels for the validation dataset in x$\_$test

output:

t$\_$model: a trained verision of the input model that is trained using the given train dataset

train$\_$accuracy: the accuracy of the model with respect to the training dataset $($i$.$e$.$ use the training dataset to evaluate the model and return the accuracy of the model$)$ as a percentage $($i$.$e$.$ between $0$ to $100)$

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### BEGIN SOLUTION

return t$\_$model, train$\_$accuracy # Return trained model and training accuracy as percentage