Language Model Analysis

In [1]:

    

report_file = 'reports/encdec_200_512_2.json'
log_file = 'logs/encdec_200_512_logs.json'

import json
import matplotlib.pyplot as plt
with open(report_file) as f:
    report = json.loads(f.read())
with open(log_file) as f:
    logs = json.loads(f.read())
print'Architecture: \n\n', report['architecture'],


    

    




Architecture: 

{u'encoder': u'nn.Sequential {\n  [input -> (1) -> (2) -> output]\n  (1): nn.LookupTable\n  (2): nn.LSTM(200 -> 512)\n}', u'decoder': u'nn.gModule'}

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print('Train Perplexity: ', report['train_perplexity'])
print('Valid Perplexity: ', report['valid_perplexity'])
print('Test Perplexity: ', report['test_perplexity'])


    

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%matplotlib inline
for k in logs.keys():
    plt.plot(logs[k][0], logs[k][1], label=str(k) + ' (train)')
    plt.plot(logs[k][0], logs[k][2], label=str(k) + ' (valid)')
plt.title('Loss v. Epoch')
plt.xlabel('Epoch')
plt.ylabel('Loss')
plt.legend()
plt.show()


    

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%matplotlib inline
for k in logs.keys():
    plt.plot(logs[k][0], logs[k][3], label=str(k) + ' (train)')
    plt.plot(logs[k][0], logs[k][4], label=str(k) + ' (valid)')
plt.title('Perplexity v. Epoch')
plt.xlabel('Epoch')
plt.ylabel('Perplexity')
plt.legend()
plt.show()


    

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def print_sample(sample):
    enc_input = ' '.join([w for w in sample['encoder_input'].split(' ') if w != '<pad>'])
    gold = ' '.join([w for w in sample['gold'].split(' ') if w != '<mask>'])
    print('Input: '+ enc_input + '\n')
    print('Gend: ' + sample['generated'] + '\n')
    print('True: ' + gold + '\n')
    print('\n')


    

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for sample in report['train_samples']:
    print_sample(sample)


    

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for sample in report['valid_samples']:
    print_sample(sample)


    

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for sample in report['test_samples']:
    print_sample(sample)