Keras计算2个粗糙Tensor之间的损失

vjrehmav 于 2023-03-02 发布在其他

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我有2个粗糙Tensor，定义如下

import tensorflow as tf

# Tensor 1
pred_score = tf.ragged.constant([
    [[-0.51760715], [-0.18927467], [-0.10698503]],
    [[-0.58782816], [-0.13076714], [-0.04999146], [-0.1772059], [-0.14299354]]
])
pred_score = tf.squeeze(pred_score, axis=-1)
pred_score_dist = tf.nn.softmax(pred_score, axis=-1)
print(pred_score_dist)
print(pred_score_dist.shape)

>> <tf.RaggedTensor [[0.25664675, 0.35639265, 0.38696054],
                     [0.1358749, 0.21460423, 0.23265839, 0.20486614, 0.21199636]]>
(2, None)

# Tensor 2
actual_score = tf.ragged.constant([
    [3.0, 2.0, 2.0], 
    [3.0, 3.0, 1.0, 1.0, 0.0]
])
actual_score_dist = tf.nn.softmax(actual_score, axis=-1)
print(actual_score_dist)
print(actual_score_dist.shape)

<tf.RaggedTensor [[0.5761169, 0.21194157, 0.21194157],
                  [0.4309495, 0.4309495, 0.05832267, 0.05832267, 0.021455714]]>
(2, None)

我想逐行计算KL散度，最后计算总散度，我试着运行这个程序，但是它给出了错误

loss = tf.keras.losses.KLDivergence()
batch_loss = loss(actual_score_dist, pred_score_dist)

ValueError: TypeError: object of type 'RaggedTensor' has no len()
有人能帮帮我吗

keras

来源：https://stackoverflow.com/questions/75587804/keras-compute-loss-between-2-ragged-tensors

1条答案

按热度按时间

s71maibg1#

这里有一个让它运行的方法，

def custom_kld(y_value, y_pred):
    if isinstance(y_value, tf.RaggedTensor):
        y_value = y_value.to_tensor()

    if isinstance(y_pred, tf.RaggedTensor):   
        y_pred = y_pred.to_tensor()
    
    return tf.keras.losses.KLDivergence()(y_value, y_pred)

custom_kld(actual_score_dist, pred_score_dist)
<tf.Tensor: shape=(), dtype=float32, numpy=0.41143954>

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Keras计算2个粗糙Tensor之间的损失

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