From c912ef9424be973b11b4c7b7dbb2d32a8f3a9ab9 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Mon, 4 May 2015 16:58:17 -0400 Subject: Restructure model & config --- model/simple_mlp.py | 69 +++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 69 insertions(+) create mode 100644 model/simple_mlp.py (limited to 'model/simple_mlp.py') diff --git a/model/simple_mlp.py b/model/simple_mlp.py new file mode 100644 index 0000000..896ccd3 --- /dev/null +++ b/model/simple_mlp.py @@ -0,0 +1,69 @@ +from blocks.bricks import MLP, Rectifier, Linear, Sigmoid, Identity +from blocks.bricks.lookup import LookupTable + +from blocks.initialization import IsotropicGaussian, Constant + +from theano import tensor + +import data +import hdist + +class Model(object): + def __init__(self, config): + # The input and the targets + x_firstk_latitude = (tensor.matrix('first_k_latitude') - data.porto_center[0]) / data.data_std[0] + x_firstk_longitude = (tensor.matrix('first_k_longitude') - data.porto_center[1]) / data.data_std[1] + + x_lastk_latitude = (tensor.matrix('last_k_latitude') - data.porto_center[0]) / data.data_std[0] + x_lastk_longitude = (tensor.matrix('last_k_longitude') - data.porto_center[1]) / data.data_std[1] + + x_client = tensor.lvector('origin_call') + x_stand = tensor.lvector('origin_stand') + + y = tensor.concatenate((tensor.vector('destination_latitude')[:, None], + tensor.vector('destination_longitude')[:, None]), axis=1) + + # Define the model + client_embed_table = LookupTable(length=data.n_train_clients+1, dim=config.dim_embed, name='client_lookup') + stand_embed_table = LookupTable(length=data.n_stands+1, dim=config.dim_embed, name='stand_lookup') + mlp = MLP(activations=[Rectifier() for _ in config.dim_hidden] + [Identity()], + dims=[config.dim_input] + config.dim_hidden + [config.dim_output]) + + # Create the Theano variables + client_embed = client_embed_table.apply(x_client) + stand_embed = stand_embed_table.apply(x_stand) + inputs = tensor.concatenate([x_firstk_latitude, x_firstk_longitude, + x_lastk_latitude, x_lastk_longitude, + client_embed, stand_embed], + axis=1) + # inputs = theano.printing.Print("inputs")(inputs) + outputs = mlp.apply(inputs) + + # Normalize & Center + # outputs = theano.printing.Print("normal_outputs")(outputs) + outputs = data.data_std * outputs + data.porto_center + + # outputs = theano.printing.Print("outputs")(outputs) + # y = theano.printing.Print("y")(y) + + outputs.name = 'outputs' + + # Calculate the cost + cost = hdist.erdist(outputs, y).mean() + cost.name = 'cost' + hcost = hdist.hdist(outputs, y).mean() + hcost.name = 'hcost' + + # Initialization + client_embed_table.weights_init = IsotropicGaussian(0.001) + stand_embed_table.weights_init = IsotropicGaussian(0.001) + mlp.weights_init = IsotropicGaussian(0.01) + mlp.biases_init = Constant(0.001) + + client_embed_table.initialize() + stand_embed_table.initialize() + mlp.initialize() + + self.cost = cost + self.hcost = hcost + self.outputs = outputs -- cgit v1.2.3