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PaddleSpeech
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Update default hyper-params of scorer in python scripts

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pull/68/head
Yibing Liu 7 years ago
parent f9ebff7e4d
commit b8d1e70549
3 changed files with 6 additions and 6 deletions
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4
deploy/demo_server.py
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@ -23,8 +23,8 @@ add_arg('beam_size', int, 500, "Beam search width.")
add_arg('num_conv_layers', int, 2, "# of convolution layers.") add_arg('num_conv_layers', int, 2, "# of convolution layers.")
add_arg('num_rnn_layers', int, 3, "# of recurrent layers.") add_arg('num_rnn_layers', int, 3, "# of recurrent layers.")
add_arg('rnn_layer_size', int, 2048, "# of recurrent cells per layer.") add_arg('rnn_layer_size', int, 2048, "# of recurrent cells per layer.")
add_arg('alpha', float, 2.15, "Coef of LM for beam search.") add_arg('alpha', float, 2.5, "Coef of LM for beam search.")
add_arg('beta', float, 0.35, "Coef of WC for beam search.") add_arg('beta', float, 0.3, "Coef of WC for beam search.")
add_arg('cutoff_prob', float, 1.0, "Cutoff probability for pruning.") add_arg('cutoff_prob', float, 1.0, "Cutoff probability for pruning.")
add_arg('cutoff_top_n', int, 40, "Cutoff number for pruning.") add_arg('cutoff_top_n', int, 40, "Cutoff number for pruning.")
add_arg('use_gru', bool, False, "Use GRUs instead of simple RNNs.") add_arg('use_gru', bool, False, "Use GRUs instead of simple RNNs.")

4
infer.py
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@ -21,8 +21,8 @@ add_arg('num_proc_bsearch', int, 8, "# of CPUs for beam search.")
add_arg('num_conv_layers', int, 2, "# of convolution layers.") add_arg('num_conv_layers', int, 2, "# of convolution layers.")
add_arg('num_rnn_layers', int, 3, "# of recurrent layers.") add_arg('num_rnn_layers', int, 3, "# of recurrent layers.")
add_arg('rnn_layer_size', int, 2048, "# of recurrent cells per layer.") add_arg('rnn_layer_size', int, 2048, "# of recurrent cells per layer.")
add_arg('alpha', float, 2.15, "Coef of LM for beam search.") add_arg('alpha', float, 2.5, "Coef of LM for beam search.")
add_arg('beta', float, 0.35, "Coef of WC for beam search.") add_arg('beta', float, 0.3, "Coef of WC for beam search.")
add_arg('cutoff_prob', float, 1.0, "Cutoff probability for pruning.") add_arg('cutoff_prob', float, 1.0, "Cutoff probability for pruning.")
add_arg('cutoff_top_n', int, 40, "Cutoff number for pruning.") add_arg('cutoff_top_n', int, 40, "Cutoff number for pruning.")
add_arg('use_gru', bool, False, "Use GRUs instead of simple RNNs.") add_arg('use_gru', bool, False, "Use GRUs instead of simple RNNs.")

4
test.py
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@ -22,8 +22,8 @@ add_arg('num_proc_data', int, 8, "# of CPUs for data preprocessing.")
add_arg('num_conv_layers', int, 2, "# of convolution layers.") add_arg('num_conv_layers', int, 2, "# of convolution layers.")
add_arg('num_rnn_layers', int, 3, "# of recurrent layers.") add_arg('num_rnn_layers', int, 3, "# of recurrent layers.")
add_arg('rnn_layer_size', int, 2048, "# of recurrent cells per layer.") add_arg('rnn_layer_size', int, 2048, "# of recurrent cells per layer.")
add_arg('alpha', float, 2.15, "Coef of LM for beam search.") add_arg('alpha', float, 2.5, "Coef of LM for beam search.")
add_arg('beta', float, 0.35, "Coef of WC for beam search.") add_arg('beta', float, 0.3, "Coef of WC for beam search.")
add_arg('cutoff_prob', float, 1.0, "Cutoff probability for pruning.") add_arg('cutoff_prob', float, 1.0, "Cutoff probability for pruning.")
add_arg('cutoff_top_n', int, 40, "Cutoff number for pruning.") add_arg('cutoff_top_n', int, 40, "Cutoff number for pruning.")
add_arg('use_gru', bool, False, "Use GRUs instead of simple RNNs.") add_arg('use_gru', bool, False, "Use GRUs instead of simple RNNs.")

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