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Function parseArgs

lstm-text-generation/train_node.js:31–116  ·  view source on GitHub ↗
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29import {createModel, compileModel, fitModel, generateText} from './model';
30
31function parseArgs() {
32 const parser = argparse.ArgumentParser({
33 description: 'Train an lstm-text-generation model.'
34 });
35 parser.addArgument('textDatasetNameOrPath', {
36 type: 'string',
37 help: 'Name of the text dataset (one of ' +
38 Object.keys(TEXT_DATA_URLS).join(', ') +
39 ') or the path to a text file containing a custom dataset'
40 });
41 parser.addArgument('--gpu', {
42 action: 'storeTrue',
43 help: 'Use CUDA GPU for training.'
44 });
45 parser.addArgument('--sampleLen', {
46 type: 'int',
47 defaultValue: 60,
48 help: 'Sample length: Length of each input sequence to the model, in ' +
49 'number of characters.'
50 });
51 parser.addArgument('--sampleStep', {
52 type: 'int',
53 defaultValue: 3,
54 help: 'Step length: how many characters to skip between one example ' +
55 'extracted from the text data to the next.'
56 });
57 parser.addArgument('--learningRate', {
58 type: 'float',
59 defaultValue: 1e-2,
60 help: 'Learning rate to be used during training'
61 });
62 parser.addArgument('--epochs', {
63 type: 'int',
64 defaultValue: 150,
65 help: 'Number of training epochs'
66 });
67 parser.addArgument('--examplesPerEpoch', {
68 type: 'int',
69 defaultValue: 10000,
70 help: 'Number of examples to sample from the text in each training epoch.'
71 });
72 parser.addArgument('--batchSize', {
73 type: 'int',
74 defaultValue: 128,
75 help: 'Batch size for training.'
76 });
77 parser.addArgument('--validationSplit', {
78 type: 'float',
79 defaultValue: 0.0625,
80 help: 'Validation split for training.'
81 });
82 parser.addArgument('--displayLength', {
83 type: 'int',
84 defaultValue: 120,
85 help: 'Length of the sampled text to display after each epoch of training.'
86 });
87 parser.addArgument('--savePath', {
88 type: 'string',

Callers 1

mainFunction · 0.70

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