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Updated example config files.
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mckinziebrandon committed May 17, 2017
1 parent 77c7f8a commit 171182f
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20 changes: 0 additions & 20 deletions configs/cornell_basic.yml

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13 changes: 5 additions & 8 deletions configs/example_cornell.yml
@@ -1,16 +1,13 @@
model: DynamicBot
dataset: Cornell
model_params:
attention_size: 256 # (optional even with AttentionDecoder)
batch_size: 128
base_cell: GRUCell
encoder.class: BidirectionalEncoder
base_cell: LSTMCell
num_layers: 2
attention_mechanism: LuongAttention
decoder.class: AttentionDecoder
num_layers: 1
ckpt_dir: out/cornell/bi_attn
steps_per_ckpt: 250
encoder.class: BidirectionalEncoder
ckpt_dir: out/cornell
dataset_params:
data_dir: /home/brandon/Datasets/cornell # The only truly 'mandatory' parameter.
vocab_size: 52000 # Approximately the true number of unique words in the dataset.
max_seq_len: 20
optimize_params: True
17 changes: 8 additions & 9 deletions configs/example_reddit.yml
@@ -1,16 +1,15 @@
dataset: data.Reddit
dataset_params:
config_path: configs/example_reddit.yml
data_dir: /home/brandon/Datasets/reddit
max_seq_len: 25
vocab_size: 80000
model: DynamicBot
dataset: Reddit
model_params:
base_cell: GRUCell
batch_size: 64
ckpt_dir: out/reddit/talkativeAttention
decoder.class: AttentionDecoder
batch_size: 128
embed_size: 128
num_layers: 1
reset_model: true
steps_per_ckpt: 200
ckpt_dir: out/reddit/basicReddit
dataset_params:
data_dir: /home/brandon/Datasets/reddit
max_seq_len: 15
vocab_size: 80000 # HUGE dataset = huge vocabulary.

13 changes: 13 additions & 0 deletions configs/example_ubuntu.yml
@@ -0,0 +1,13 @@
model: DynamicBot
dataset: Ubuntu
model_params:
base_cell: GRUCell
ckpt_dir: out/ubuntu
decoder.class: BasicDecoder
encoder.class: BasicEncoder
num_layers: 2
state_size: 512
dataset_params:
data_dir: /home/brandon/Datasets/ubuntu
vocab_size: 60000 # Should probably be higher. Ubuntu is noisy.
max_seq_len: 12 # Any longer, and output quality is a challenge.

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