是否有使用keras的方法.javascript中的Pad_sequences ?


@keras_export('keras.preprocessing.sequence.pad_sequences')
def pad_sequences(sequences, maxlen=None, dtype='int32',
padding='pre', truncating='pre', value=0.):
return sequence.pad_sequences(
sequences, maxlen=maxlen, dtype=dtype,
padding=padding, truncating=truncating, value=value)

我想把这段代码转换成javascript

它是这样工作的:

sequence = [[1], [2, 3], [4, 5, 6]]
tf.keras.preprocessing.sequence.pad_sequences(sequence, maxlen=2)
array = 
0,1
2,3
5,6

你可以像这样截断和填充你的Javascript序列:

const sequence = [[1], [2, 3], [4, 5, 6]];
var new_sequence = sequence.map(function(e) {
const max_length = 2;
const row_length = e.length 
if (row_length > max_length){ // truncate
return e.slice(row_length - max_length, row_length)
}
else if (row_length < max_length){ // pad
return Array(max_length - row_length).fill(0).concat(e);
}
return e;
});
console.log('Before truncating and paddig: ',sequence)
console.log('After truncating and paddig: ', new_sequence)
// "Before truncating and paddig: ", [[1], [2, 3], [4, 5, 6]]
// "After truncating and paddig: ", [[0, 1], [2, 3], [5, 6]]

,它相当于下面使用Tensorflow的Python代码:

import tensorflow as tf
def truncate_and_pad(row):
row_length = tf.shape(row)[0]
if tf.greater(row_length, max_length): # truncate
return row[row_length-max_length:]
elif tf.less(row_length, max_length): # pad
padding = tf.constant([[max_length-row_length.numpy(), 0]])
return tf.pad(row, padding, "CONSTANT")
else: return row
max_length = 2
sequence = tf.ragged.constant([[1], [2, 3], [4, 5, 6]])
Y = tf.map_fn(truncate_and_pad, sequence)

,但实际上不需要任何花哨的函数

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