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authorAlex Auvolat <alex@adnab.me>2016-03-29 12:27:35 +0200
committerAlex Auvolat <alex@adnab.me>2016-03-29 12:27:35 +0200
commit30faf44a08edcc2075362c4633f6b1d291944cd3 (patch)
treebb4a53766d87fc3437999631eb08158a4a26e812 /config/hpc-lstm-0.py
parent62c05c06013e7204c1e7681a7e2ac7541f2acbcb (diff)
downloadtext-rnn-30faf44a08edcc2075362c4633f6b1d291944cd3.tar.gz
text-rnn-30faf44a08edcc2075362c4633f6b1d291944cd3.zip
This HPC stuff doesn't work very well.
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+import numpy
+from numpy.random import RandomState
+
+from blocks.algorithms import AdaDelta, Momentum
+from blocks.bricks import Tanh, Rectifier
+
+from model.hpc_lstm import Model
+
+dataset = 'data/logcompil-2016-03-07.txt'
+
+io_dim = 256
+repr_dim = 256
+embedding_matrix = numpy.eye(io_dim)
+
+# An epoch will be composed of 'num_seqs' sequences of len 'seq_len'
+# divided in chunks of lengh 'seq_div_size'
+num_seqs = 100
+seq_len = 2000
+seq_div_size = 100
+
+hidden_dims = [128, 128, 256, 512]
+cost_factors = [1., 1., 1., 1.]
+hidden_q = [0.1, 0.15, 0.22, 0.33]
+activation_function = Tanh()
+
+out_hidden = [512]
+out_hidden_act = [Rectifier]
+
+step_rule = AdaDelta()
+#step_rule = Momentum(learning_rate=0.0001, momentum=0.99)
+
+# parameter saving freq (number of batches)
+monitor_freq = 10
+save_freq = 100
+
+# used for sample generation and IRC mode
+sample_temperature = 0.7 #0.5
+
+# do we want to generate samples at times during training?
+sample_len = 1000
+sample_freq = 100
+sample_init = '\nalex\ttu crois?\n'
+