<s> from blocks . bricks import Tanh <EOL> from blocks . algorithms import BasicMomentum , AdaDelta , RMSProp , Adam , CompositeRule , StepClipping , Momentum <EOL> from blocks . initialization import IsotropicGaussian , Constant <EOL> from model . attentive_reader import Model <EOL> batch_size = <NUM_LIT:32> <EOL> sort_batch_count = <NUM_LIT:20> <EOL> shuffle_questions = True <EOL> concat_ctx_and_question = False <EOL> n_entities = <NUM_LIT> <EOL> embed_size = <NUM_LIT:200> <EOL> ctx_lstm_size = [ <NUM_LIT> ] <EOL> ctx_skip_connections = True <EOL> question_lstm_size = [ <NUM_LIT> ] <EOL> question_skip_connections = True <EOL> attention_mlp_hidden = [ <NUM_LIT:100> ] <EOL> attention_mlp_activations = [ Tanh ( ) ] <EOL> out_mlp_hidden = [ ] <EOL> out_mlp_activations = [ ] <EOL> step_rule = CompositeRule ( [ RMSProp ( decay_rate = <NUM_LIT> , learning_rate = <NUM_LIT> ) , <EOL> BasicMomentum ( momentum = <NUM_LIT> ) ] ) <EOL> dropout = <NUM_LIT> <EOL> w_noise = <NUM_LIT:0.> <EOL> valid_freq = <NUM_LIT:1000> <EOL> save_freq = <NUM_LIT:1000> <EOL> print_freq = <NUM_LIT:100> <EOL> weights_init = IsotropicGaussian ( <NUM_LIT> ) <EOL> biases_init = Constant ( <NUM_LIT:0.> ) </s>
