我正在尝试实现 overlap-add在 Tensorflow 中,但我正在努力将 numpy output_seq[start:end] += chunk
转换为 Tensorflow。现在我是 output_seq = output_seq + tf.pad(chunk, [[start, length - end]])
但这在长序列上真的很慢。
我也有一种预感,你可能可以通过聚集/分散来实现一些技巧,但我不太明白。以下是我的暴力尝试:
import tensorflow as tf
input = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
def overlap_add(overlap):
with tf.Graph().as_default(), tf.Session() as sess:
x = tf.constant(input)
num_chunks = tf.shape(x)[0]
chunk_size = tf.shape(x)[1]
hop_length = chunk_size - overlap
out_len = chunk_size + hop_length * (num_chunks - 1)
y = tf.zeros((out_len,), dtype=tf.int32)
def body(i, y):
j = i * hop_length
padding = [[j, out_len - (j + chunk_size)]]
chunk = x[i]
y = y + tf.pad(chunk, padding)
return (i + 1, y)
i = tf.constant(0)
i, y = tf.while_loop(
cond=lambda i, _: tf.less(i, num_chunks),
body=body,
loop_vars=[i, y])
return sess.run(y)
for i in range(4):
print 'overlap_add(%d): %s' % (i, overlap_add(i))
# overlap_add(0): [ 1 2 3 4 5 6 7 8 9 10 11 12]
# overlap_add(1): [ 1 2 3 9 6 7 17 10 11 12]
# overlap_add(2): [ 1 2 8 10 16 18 11 12]
# overlap_add(3): [ 1 7 18 21 19 12]
最佳答案
更新:现在有一个overlap_and_add
Tensorflow 本身具有函数。
旧答案:
浏览文档并发现 unsorted_segment_sum
:
import tensorflow as tf
input = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
def tf_repeat(a, repeats):
return tf.reshape(tf.tile(tf.reshape(a, [-1, 1]),
[1, repeats]), [-1])
def overlap_add(overlap):
with tf.Graph().as_default(), tf.Session() as sess:
x = tf.constant(input)
x_flat = tf.reshape(x, [-1])
num_chunks = tf.shape(x)[0]
chunk_size = tf.shape(x)[1]
hop_len = chunk_size - overlap
flat_len = num_chunks * chunk_size
out_len = chunk_size + hop_len * (num_chunks - 1)
# e.g. [0,1,2,3, 2,3,4,5, 4,5,6,7] for overlap == 2
indexes = tf.range(flat_len) - tf_repeat(tf.range(num_chunks), chunk_size) * overlap
return sess.run(tf.unsorted_segment_sum(x_flat, indexes, out_len))
for i in range(4):
print 'overlap_add(%d): %s' % (i, overlap_add(i))
# overlap_add(0): [ 1 2 3 4 5 6 7 8 9 10 11 12]
# overlap_add(1): [ 1 2 3 9 6 7 17 10 11 12]
# overlap_add(2): [ 1 2 8 10 16 18 11 12]
# overlap_add(3): [ 1 7 18 21 19 12]
关于python - Tensorflow高效重叠相加,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/44724384/