我正在尝试使用:train = optimizer.minimize(loss)
,但是标准优化器不能使用tf.float64
。因此,我想将我的loss
从tf.float64
截断为仅tf.float32
。
Traceback (most recent call last):
File "q4.py", line 85, in <module>
train = optimizer.minimize(loss)
File "/Library/Python/2.7/site-packages/tensorflow/python/training/optimizer.py", line 190, in minimize
colocate_gradients_with_ops=colocate_gradients_with_ops)
File "/Library/Python/2.7/site-packages/tensorflow/python/training/optimizer.py", line 229, in compute_gradients
self._assert_valid_dtypes([loss])
File "/Library/Python/2.7/site-packages/tensorflow/python/training/optimizer.py", line 354, in _assert_valid_dtypes
dtype, t.name, [v for v in valid_dtypes]))
ValueError: Invalid type tf.float64 for Add_1:0, expected: [tf.float32].
简而言之,您可以使用^{} 操作将张量从
tf.float64
转换为tf.float32
:更长的答案是,这并不能解决优化器的所有问题。(缺少对
tf.float64
的支持是一个known issue)优化器要求您试图优化的所有对象也必须具有类型tf.float32
。相关问题 更多 >
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