tensorflow.multinomial和pytorch.multinomial，性能差距很大。特别是，我认为tensorflow.multinomial非常有问题。
我编写了以下代码来比较这两个函数，我将第一个数字设置为10，将其他数字设置为0.0001，然后将softmax设置为选择概率。
import torch
import numpy as np
import tensorflow as tf
single_data = np.array([10,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001,0.0001])
single_data = np.expand_dims(single_data, axis=0)
data =np.repeat(single_data, 50, axis=0)
data = tf.nn.softmax(data,axis=-1)
sampled_word = tf.multinomial(data,1)
sample = tf.reshape(sampled_word,[-1])
with tf.Session() as sess:
a_data=sess.run(data)
print("prob:",a_data)
print("tensorflow.multinomial", sess.run(sample))
a_data = torch.from_numpy(a_data)
idx = torch.multinomial(a_data, num_samples=1)
print("tensorflow.multinomial", np.reshape(idx.data.numpy(),[-1]))
prob: [[9.93907740e-01 4.51278541e-05 4.51278541e-05 ... 4.51278541e-05
4.51278541e-05 4.51278541e-05]
[9.93907740e-01 4.51278541e-05 4.51278541e-05 ... 4.51278541e-05
4.51278541e-05 4.51278541e-05]
[9.93907740e-01 4.51278541e-05 4.51278541e-05 ... 4.51278541e-05
4.51278541e-05 4.51278541e-05]
...
[9.93907740e-01 4.51278541e-05 4.51278541e-05 ... 4.51278541e-05
4.51278541e-05 4.51278541e-05]
[9.93907740e-01 4.51278541e-05 4.51278541e-05 ... 4.51278541e-05
4.51278541e-05 4.51278541e-05]
[9.93907740e-01 4.51278541e-05 4.51278541e-05 ... 4.51278541e-05
4.51278541e-05 4.51278541e-05]]
tensorflow.multinomial [121 129 35 104 4 133 60 92 104 129 4 49 35 99 109 111 62 87
23 5 109 63 103 61 78 43 101 85 2 127 0 36 53 0 74 44
64 55 51 59 108 0 112 32 36 24 68 135 72 22]
tensorflow.multinomial [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]
我们发现Tensorflow几乎很难选择数据（99％的时间），而PyTorch则很容易选择。有何评论？