Stuff.

3 files changed, 138 insertions, 0 deletions

diff --git a/config/condlstm.py b/config/condlstm.py
new file mode 100644
index 0000000..f846972
--- /dev/null
+++ b/config/condlstm.py
@@ -0,0 +1,85 @@
+from blocks.algorithms import AdaDelta
+from blocks.bricks import Tanh
+from blocks.initialization import IsotropicGaussian, Constant
+
+from model.condlstm import Model
+
+dataset = 'data/logcompil.txt'
+io_dim = 256
+
+# An epoch will be composed of 'num_seqs' sequences of len 'seq_len'
+# divided in chunks of lengh 'seq_div_size'
+num_seqs = 50
+seq_len = 5000
+seq_div_size = 200
+
+layers = [
+	# Slowlier
+	{'dim':			128,
+	 'reset_after': ' \t\n,.:;/!?()[]{}<>\\\'"*+-^_|#~&`@$%',
+	},
+	{'dim':			128,
+	 'run_on':		' \t\n,.:;/!?()[]{}<>\\\'"*+-^_|#~&`@$%',
+	 'reset_after': ' \t\n',
+	},
+	{'dim':			128,
+	 'run_on':		' \t\n',
+	 'reset_after': '\t\n',
+	},
+	{'dim':			256,
+	 'run_on':		' \t\n',
+	 'reset_after': '\n',
+	},
+	{'dim':			512,
+	 'run_on':		'\t\n',
+	},
+	# Slowest
+	{'dim':			512,
+	 'run_on':		'\n',
+	},
+	# Fastlier
+	{'dim':			512,
+	 'run_on':		'\t\n',
+	},
+	{'dim':			256,
+	 'run_on':		' \t\n',
+	 'reset_before':'\n',
+	},
+	{'dim':			128,
+	 'run_on':		' \t\n',
+	 'reset_before': '\t\n',
+	},
+	{'dim':			128,
+	 'run_on':		' \t\n,.:;/!?()[]{}<>\\\'"*+-^_|#~&`@$%',
+	 'reset_before': ' \t\n',
+	},
+	{'dim':			128,
+	 'reset_before': ' \t\n,.:;/!?()[]{}<>\\\'"*+-^_|#~&`@$%',
+	},
+]
+activation_function = Tanh()
+
+w_noise_std = 0
+i_dropout = 0
+
+l1_reg = 0
+l1_reg_weight = 0
+
+step_rule = AdaDelta()
+
+weights_init = IsotropicGaussian(0.01)
+biases_init = Constant(0.)
+
+# parameter saving freq (number of batches)
+monitor_freq = 100
+save_freq = 100
+
+# used for sample generation and IRC mode
+#sample_temperature = 0.7 #0.5
+sample_temperature = 0.9 #0.5
+
+# do we want to generate samples at times during training?
+sample_len = 500
+sample_freq = 100
+sample_init = '\nalex\ttu crois?\n'
+
diff --git a/config/lstm-deep-l1.py b/config/lstm-deep-l1.py
new file mode 100644
index 0000000..fd330c7
--- /dev/null
+++ b/config/lstm-deep-l1.py
@@ -0,0 +1,52 @@
+from blocks.algorithms import AdaDelta
+from blocks.bricks import Tanh
+
+from model.lstm import Model
+
+dataset = 'data/logcompil.txt'
+io_dim = 256
+
+# 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 = 5000
+seq_div_size = 200
+
+layers = [
+	{'dim':		512},
+	{'dim':		512},
+	{'dim':		512},
+	{'dim':		512},
+	{'dim':		512},
+	{'dim':		512},
+	{'dim':		512},
+	{'dim':		512},
+	{'dim':		512},
+	{'dim':		512},
+]
+activation_function = Tanh()
+
+i2h_all = True             # input to all hidden layers or only first layer
+h2o_all = True             # all hiden layers to output or only last layer
+
+w_noise_std = 0
+i_dropout = 0
+
+l1_reg = 0
+l1_reg_weight = 0.05
+
+step_rule = AdaDelta()
+
+# parameter saving freq (number of batches)
+monitor_freq = 100
+save_freq = 100
+
+# used for sample generation and IRC mode
+#sample_temperature = 0.7 #0.5
+sample_temperature = 0.9 #0.5
+
+# do we want to generate samples at times during training?
+sample_len = 1000
+sample_freq = 100
+sample_init = '\nalex\ttu crois?\n'
+
diff --git a/config/lstm-frigo-irc.py b/config/lstm-frigo-irc.py
index 04468c9..38f0766 100644
--- a/config/lstm-frigo-irc.py
+++ b/config/lstm-frigo-irc.py
@@ -26,6 +26,7 @@ w_noise_std = 0.02
 i_dropout = 0.5
 
 l1_reg = 0
+l1_reg_weight = 0
 
 step_rule = AdaDelta()