tiny_shakespeare

  • Deskripsi :

40.000 baris Shakespeare dari berbagai drama Shakespeare. Ditampilkan dalam posting blog Andrej Karpathy 'The Unreasonable Effectiveness of Recurrent Neural Networks': http://karpathy.github.io/2015/05/21/rnn-effectiveness/

Untuk digunakan misalnya untuk pemodelan karakter:

d = tfds.load(name='tiny_shakespeare')['train']
d = d.map(lambda x: tf.strings.unicode_split(x['text'], 'UTF-8'))
# train split includes vocabulary for other splits
vocabulary = sorted(set(next(iter(d)).numpy()))
d = d.map(lambda x: {'cur_char': x[:-1], 'next_char': x[1:]})
d = d.unbatch()
seq_len = 100
batch_size = 2
d = d.batch(seq_len)
d = d.batch(batch_size)
Membelah Contoh
'test' 1
'train' 1
'validation' 1
  • Struktur fitur :
FeaturesDict({
    'text': Text(shape=(), dtype=string),
})
  • Dokumentasi fitur :
Fitur Kelas Membentuk Dtype Keterangan
fiturDict
teks Teks rangkaian
  • Kutipan :
@misc{
  author={Karpathy, Andrej},
  title={char-rnn},
  year={2015},
  howpublished={\url{https://github.com/karpathy/char-rnn} }
}
,

  • Deskripsi :

40.000 baris Shakespeare dari berbagai drama Shakespeare. Ditampilkan dalam posting blog Andrej Karpathy 'The Unreasonable Effectiveness of Recurrent Neural Networks': http://karpathy.github.io/2015/05/21/rnn-effectiveness/

Untuk digunakan misalnya untuk pemodelan karakter:

d = tfds.load(name='tiny_shakespeare')['train']
d = d.map(lambda x: tf.strings.unicode_split(x['text'], 'UTF-8'))
# train split includes vocabulary for other splits
vocabulary = sorted(set(next(iter(d)).numpy()))
d = d.map(lambda x: {'cur_char': x[:-1], 'next_char': x[1:]})
d = d.unbatch()
seq_len = 100
batch_size = 2
d = d.batch(seq_len)
d = d.batch(batch_size)
Membelah Contoh
'test' 1
'train' 1
'validation' 1
  • Struktur fitur :
FeaturesDict({
    'text': Text(shape=(), dtype=string),
})
  • Dokumentasi fitur :
Fitur Kelas Membentuk Dtype Keterangan
fiturDict
teks Teks rangkaian
  • Kutipan :
@misc{
  author={Karpathy, Andrej},
  title={char-rnn},
  year={2015},
  howpublished={\url{https://github.com/karpathy/char-rnn} }
}