diff options
Diffstat (limited to 'model')
| -rw-r--r-- | model/dest_simple_mlp.py | 8 | ||||
| -rw-r--r-- | model/dest_simple_mlp_tgtcls.py | 8 | ||||
| -rw-r--r-- | model/dest_simple_mlp_tgtcls_alexandre.py | 75 | ||||
| -rw-r--r-- | model/time_simple_mlp.py | 22 |
4 files changed, 16 insertions, 97 deletions
diff --git a/model/dest_simple_mlp.py b/model/dest_simple_mlp.py index f422f11..a9e97cb 100644 --- a/model/dest_simple_mlp.py +++ b/model/dest_simple_mlp.py @@ -1,8 +1,6 @@ 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 @@ -58,9 +56,9 @@ class Model(object): # Initialization for tbl in embed_tables: - tbl.weights_init = IsotropicGaussian(0.001) - mlp.weights_init = IsotropicGaussian(0.01) - mlp.biases_init = Constant(0.001) + tbl.weights_init = config.embed_weights_init + mlp.weights_init = config.mlp_weights_init + mlp.biases_init = config.mlp_biases_init for tbl in embed_tables: tbl.initialize() diff --git a/model/dest_simple_mlp_tgtcls.py b/model/dest_simple_mlp_tgtcls.py index a7b6f9b..1381d4c 100644 --- a/model/dest_simple_mlp_tgtcls.py +++ b/model/dest_simple_mlp_tgtcls.py @@ -6,8 +6,6 @@ from theano import tensor from blocks.bricks import MLP, Rectifier, Linear, Sigmoid, Identity, Softmax from blocks.bricks.lookup import LookupTable -from blocks.initialization import IsotropicGaussian, Constant - import data import error @@ -60,9 +58,9 @@ class Model(object): # Initialization for tbl in embed_tables: - tbl.weights_init = IsotropicGaussian(0.001) - mlp.weights_init = IsotropicGaussian(0.01) - mlp.biases_init = Constant(0.001) + tbl.weights_init = config.embed_weights_init + mlp.weights_init = config.mlp_weights_init + mlp.biases_init = config.mlp_biases_init for tbl in embed_tables: tbl.initialize() diff --git a/model/dest_simple_mlp_tgtcls_alexandre.py b/model/dest_simple_mlp_tgtcls_alexandre.py deleted file mode 100644 index 825bf80..0000000 --- a/model/dest_simple_mlp_tgtcls_alexandre.py +++ /dev/null @@ -1,75 +0,0 @@ -import numpy - -import theano -from theano import tensor - -from blocks.bricks import MLP, Rectifier, Linear, Sigmoid, Identity, Softmax -from blocks.bricks.lookup import LookupTable - -from blocks.initialization import IsotropicGaussian, Constant - -import data -import error - -class Model(object): - def __init__(self, config): - # The input and the targets - x_firstk_latitude = (tensor.matrix('first_k_latitude') - data.train_gps_mean[0]) / data.train_gps_std[0] - x_firstk_longitude = (tensor.matrix('first_k_longitude') - data.train_gps_mean[1]) / data.train_gps_std[1] - - x_lastk_latitude = (tensor.matrix('last_k_latitude') - data.train_gps_mean[0]) / data.train_gps_std[0] - x_lastk_longitude = (tensor.matrix('last_k_longitude') - data.train_gps_mean[1]) / data.train_gps_std[1] - - input_list = [x_firstk_latitude, x_firstk_longitude, x_lastk_latitude, x_lastk_longitude] - embed_tables = [] - - self.require_inputs = ['first_k_latitude', 'first_k_longitude', 'last_k_latitude', 'last_k_longitude'] - - for (varname, num, dim) in config.dim_embeddings: - self.require_inputs.append(varname) - vardata = tensor.lvector(varname) - tbl = LookupTable(length=num, dim=dim, name='%s_lookup'%varname) - embed_tables.append(tbl) - input_list.append(tbl.apply(vardata)) - - y = tensor.concatenate((tensor.vector('destination_latitude')[:, None], - tensor.vector('destination_longitude')[:, None]), axis=1) - - # Define the model - mlp = MLP(activations=[Rectifier() for _ in config.dim_hidden] + [Softmax()], - dims=[config.dim_input] + config.dim_hidden + [config.dim_output]) - classes = theano.shared(numpy.array(config.tgtcls, dtype=theano.config.floatX), name='classes') - - # Create the Theano variables - inputs = tensor.concatenate(input_list, axis=1) - - # inputs = theano.printing.Print("inputs")(inputs) - cls_probas = mlp.apply(inputs) - outputs = tensor.dot(cls_probas, classes) - - # outputs = theano.printing.Print("outputs")(outputs) - # y = theano.printing.Print("y")(y) - - outputs.name = 'outputs' - - # Calculate the cost - cost = error.erdist(outputs, y).mean() - cost.name = 'cost' - hcost = error.hdist(outputs, y).mean() - hcost.name = 'hcost' - - # Initialization - for tbl in embed_tables: - tbl.weights_init = IsotropicGaussian(0.01) - mlp.weights_init = IsotropicGaussian(0.1) - mlp.biases_init = Constant(0.01) - - for tbl in embed_tables: - tbl.initialize() - mlp.initialize() - - self.cost = cost - self.monitor = [cost, hcost] - self.outputs = outputs - self.pred_vars = ['destination_latitude', 'destination_longitude'] - diff --git a/model/time_simple_mlp.py b/model/time_simple_mlp.py index 1568ed3..9e1b10a 100644 --- a/model/time_simple_mlp.py +++ b/model/time_simple_mlp.py @@ -1,8 +1,6 @@ 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 @@ -11,11 +9,11 @@ import error 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_firstk_latitude = (tensor.matrix('first_k_latitude') - data.train_gps_mean[0]) / data.train_gps_std[0] + x_firstk_longitude = (tensor.matrix('first_k_longitude') - data.train_gps_mean[1]) / data.train_gps_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_lastk_latitude = (tensor.matrix('last_k_latitude') - data.train_gps_mean[0]) / data.train_gps_std[0] + x_lastk_longitude = (tensor.matrix('last_k_longitude') - data.train_gps_mean[1]) / data.train_gps_std[1] input_list = [x_firstk_latitude, x_firstk_longitude, x_lastk_latitude, x_lastk_longitude] embed_tables = [] @@ -29,7 +27,7 @@ class Model(object): embed_tables.append(tbl) input_list.append(tbl.apply(vardata)) - y = tensor.lvector('time') + y = tensor.lvector('travel_time') # Define the model mlp = MLP(activations=[Rectifier() for _ in config.dim_hidden] + [Identity()], @@ -38,7 +36,7 @@ class Model(object): # Create the Theano variables inputs = tensor.concatenate(input_list, axis=1) # inputs = theano.printing.Print("inputs")(inputs) - outputs = tensor.exp(mlp.apply(inputs) + 2) + outputs = config.exp_base ** mlp.apply(inputs) # outputs = theano.printing.Print("outputs")(outputs) # y = theano.printing.Print("y")(y) @@ -51,9 +49,9 @@ class Model(object): # Initialization for tbl in embed_tables: - tbl.weights_init = IsotropicGaussian(0.001) - mlp.weights_init = IsotropicGaussian(0.01) - mlp.biases_init = Constant(0.001) + tbl.weights_init = config.embed_weights_init + mlp.weights_init = config.mlp_weights_init + mlp.biases_init = config.mlp_biases_init for tbl in embed_tables: tbl.initialize() @@ -62,4 +60,4 @@ class Model(object): self.cost = cost self.monitor = [cost] self.outputs = outputs - self.pred_vars = ['time'] + self.pred_vars = ['travel_time'] |