import tensorflow as tf
import numpy as np
t=4*64*20
feats = np.ones((t)).reshape((4,64,20))
g = tf.Graph()
device_t='/gpu:0'
soft_config = tf.compat.v1.ConfigProto(allow_soft_placement=True)
soft_config.gpu_options.allow_growth = True
with g.as_default(), g.device(device_t), \
tf.compat.v1.Session(config=soft_config) as sess:
feats_T = tf.transpose(a=feats, perm=[0,2,1])
print(feats_T.shape)
print(feats.shape)
grams = tf.matmul(feats_T, feats)
print(grams.shape)
(4, 20, 64)
(4, 64, 20)
(4, 20, 20)
import tensorflow as tf
import numpy as np
t=4*64*20*16
t1 = 64*20
feats = np.ones((t)).reshape((4,t1,16))
g = tf.Graph()
device_t='/gpu:0'
soft_config = tf.compat.v1.ConfigProto(allow_soft_placement=True)
soft_config.gpu_options.allow_growth = True
with g.as_default(), g.device(device_t), \
tf.compat.v1.Session(config=soft_config) as sess:
feats_T = tf.transpose(a=feats, perm=[0,2,1])
print(feats_T.shape)
print(feats.shape)
grams = tf.matmul(feats_T, feats)
print(grams.shape)
(4, 16, 1280)
(4, 1280, 16)
(4, 16, 16)
grams = np.ones((4*16*16)).reshape((4,16,16))
grams_1 = np.ones((16*16)).reshape((16,16))
g = tf.Graph()
device_t='/gpu:0'
soft_config = tf.compat.v1.ConfigProto(allow_soft_placement=True)
soft_config.gpu_options.allow_growth = True
with g.as_default(), g.device(device_t), \
tf.compat.v1.Session(config=soft_config) as sess:
grams = tf.reshape(grams,(4,16,16))
loss = grams - grams_1
loss1 = tf.nn.l2_loss(grams - grams_1)
print(loss.shape)
print(sess.run(loss))
print(sess.run(loss1))
[[[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
...
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]]
[[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
...
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]]
[[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
...
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]]
[[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
...
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]
[0. 0. 0. ... 0. 0. 0.]]]
0.0
可见上面计算发生了广播。
grams = np.ones((4*16*16)).reshape((4,16,16))
grams_1 = np.ones((4*16*16)).reshape((4,16,16))
g = tf.Graph()
device_t='/gpu:0'
soft_config = tf.compat.v1.ConfigProto(allow_soft_placement=True)
soft_config.gpu_options.allow_growth = True
with g.as_default(), g.device(device_t), \
tf.compat.v1.Session(config=soft_config) as sess:
grams = tf.reshape(grams,(4,16,16))
loss = grams - grams_1
loss1 = tf.nn.l2_loss(grams - grams_1)
print(loss.shape)
print(sess.run(loss))
print(sess.run(loss1))
计算结果一样。