Module ImportFrom alias ImportFrom alias alias alias ImportFrom alias ImportFrom alias alias alias ImportFrom alias ImportFrom alias alias alias ImportFrom alias ImportFrom alias FunctionDef arguments args defaults body Expr Str Assign TupleStore TupleStore NameStore NameStore TupleStore NameStore NameStore Call AttributeLoad NameLoad attr Assign NameStore Call AttributeLoad NameLoad attr Num Num Assign NameStore Call AttributeLoad NameLoad attr Num Num Assign NameStore Call AttributeLoad NameLoad attr Str Assign NameStore Call AttributeLoad NameLoad attr Str AugAssignDiv NameStore Num AugAssignDiv NameStore Num Assign NameStore Num Assign NameStore Call AttributeLoad NameLoad attr NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad NameLoad Return TupleLoad NameLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults body Expr Str Assign NameStore Call NameLoad Expr Call AttributeLoad NameLoad attr Call NameLoad Num keyword TupleLoad Num Expr Call AttributeLoad NameLoad attr Call NameLoad Str Expr Call AttributeLoad NameLoad attr Call NameLoad Set Set Call NameLoad Num Num Expr Call AttributeLoad NameLoad attr Call NameLoad Set Set Call NameLoad ListLoad Num Num Num Expr Call AttributeLoad NameLoad attr Call NameLoad Set Set Call NameLoad ListLoad Str Str Expr Call AttributeLoad NameLoad attr Call NameLoad Set Set Call NameLoad Num Num If CompareEq Call NameLoad Set Set Call NameLoad ListLoad Str Str Str body Expr Call AttributeLoad NameLoad attr Call NameLoad Num Expr Call AttributeLoad NameLoad attr Set Set Call NameLoad ListLoad Call NameLoad Num Call NameLoad Str Expr Call AttributeLoad NameLoad attr Call NameLoad Str Expr Call AttributeLoad NameLoad attr Call NameLoad Num Expr Call AttributeLoad NameLoad attr Call NameLoad Str Expr Call AttributeLoad NameLoad attr keyword Str keyword Set Set Call NameLoad ListLoad Str Str Str keyword ListLoad Str Expr Call AttributeLoad NameLoad attr NameLoad NameLoad keyword Set Set Call NameLoad ListLoad Num Num keyword Num keyword Num keyword TupleLoad NameLoad NameLoad Assign TupleStore NameStore NameStore Call AttributeLoad NameLoad attr NameLoad NameLoad keyword Num Expr Call NameLoad Str NameLoad Return Dict Str Str Str UnaryOpUSub NameLoad NameLoad NameLoad decorator_list If CompareEq NameLoad Str body Assign TupleStore NameStore NameStore Call AttributeLoad NameLoad attr keyword NameLoad keyword NameLoad keyword AttributeLoad NameLoad attr keyword Num keyword Call NameLoad Assign TupleStore NameStore NameStore NameStore NameStore Call NameLoad Expr Call NameLoad Str Expr Call NameLoad Call AttributeLoad NameLoad attr NameLoad NameLoad
N/A __future__ print_function hyperopt Trials STATUS_OK tpe hyperas optim hyperas.distributions choice uniform conditional keras.models Sequential keras.layers.core Dense Dropout Activation keras.datasets mnist keras.utils np_utils data N/A N/A N/A N/A N/A 
    Data providing function:

    This function is separated from model() so that hyperopt
    won't reload data for each evaluation run.
     N/A N/A N/A X_train y_train N/A X_test y_test N/A N/A mnist load_data N/A X_train N/A N/A X_train reshape 60000 784 N/A X_test N/A N/A X_test reshape 10000 784 N/A X_train N/A N/A X_train astype float32 N/A X_test N/A N/A X_test astype float32 N/A X_train 255 N/A X_test 255 N/A nb_classes 10 N/A Y_train N/A N/A np_utils to_categorical y_train nb_classes N/A Y_test N/A N/A np_utils to_categorical y_test nb_classes N/A N/A X_train Y_train X_test Y_test N/A model N/A N/A X_train Y_train X_test Y_test N/A N/A N/A 
    Model providing function:

    Create Keras model with double curly brackets dropped-in as needed.
    Return value has to be a valid python dictionary with two customary keys:
        - loss: Specify a numeric evaluation metric to be minimized
        - status: Just use STATUS_OK and see hyperopt documentation if not feasible
    The last one is optional, though recommended, namely:
        - model: specify the model just created so that we can later use it again.
     N/A model N/A Sequential N/A N/A N/A model add N/A Dense 512 input_shape N/A 784 N/A N/A N/A model add N/A Activation relu N/A N/A N/A model add N/A Dropout N/A N/A N/A uniform 0 1 N/A N/A N/A model add N/A Dense N/A N/A N/A choice N/A 256 512 1024 N/A N/A N/A model add N/A Activation N/A N/A N/A choice N/A relu sigmoid N/A N/A N/A model add N/A Dropout N/A N/A N/A uniform 0 1 N/A N/A N/A conditional N/A N/A N/A choice N/A three four four N/A N/A N/A N/A model add N/A Dense 100 N/A N/A N/A model add N/A N/A N/A choice N/A N/A Dropout 0.5 N/A Activation linear N/A N/A N/A model add N/A Activation relu N/A N/A N/A model add N/A Dense 10 N/A N/A N/A model add N/A Activation softmax N/A N/A N/A model compile loss categorical_crossentropy optimizer N/A N/A N/A choice N/A rmsprop adam sgd metrics N/A accuracy N/A N/A N/A model fit X_train Y_train batch_size N/A N/A N/A choice N/A 64 128 nb_epoch 1 verbose 2 validation_data N/A X_test Y_test N/A N/A score acc N/A N/A model evaluate X_test Y_test verbose 0 N/A N/A print Test accuracy: acc N/A N/A loss status model N/A acc STATUS_OK model N/A N/A N/A __name__ __main__ N/A N/A N/A best_run best_model N/A N/A optim minimize model model data data algo N/A tpe suggest max_evals 5 trials N/A Trials N/A N/A X_train Y_train X_test Y_test N/A data N/A N/A print Evalutation of best performing model: N/A N/A print N/A N/A best_model evaluate X_test Y_test