23.01.2018 · AttributeError: 'Tensor' object has no attribute 'exp' Ask Question Asked 3 years, 11 months ago. Active 2 years, 6 months ago. Viewed 3k times 0 I am trying to train a LSTM NN using Keras on a self-defined evaluation_metric that I …
The problem in your code is that you cannot use .numpy() inside functions that are mapped onto tf.data.Datasets, because .numpy() is Python code not pure TensorFlow code.. When you use a function like my_dataset.map(my_function), you can only use tf.* functions inside your my_function function.. This is not a bug of TensorFlow 2.x versions, but rather on how static …
31.05.2021 · Since the accepted answer did not solve the problem for me so I thought it might be helpful for some people who face the problem and that already have tensorflow version >= 2.2.0 and eager execution enabled.
device contains a device type ( 'cpu' or 'cuda' ) and optional device ordinal for the device type. If the device ordinal is not present, this object will always ...
22.11.2017 · e 3691, in transpose. ret = DimShuffle (x.broadcastable, axes) (x) AttributeError: 'Tensor' object has no attribute 'broadcastable'. The text was updated successfully, but these errors were encountered: Copy link.
27.04.2017 · We don't have much experience with Zeppelin so it is tough to support this. Perhaps your problem is your are trying to graph unevaluated Tensors.
19.11.2021 · UPDATE: Note that eager execution is enabled by default in TensorFlow 2.0. So the answer above applies only to TensorFlow 1.x. Solution 2. This can also happen in TF2.0 if your code is wrapped in a @tf.function or inside a Keras layer.
Probably there's something wrong with the input values for X and/or T. The function from the question works ok: import numpy as np from math import e def ...
31.03.2020 · 在8.5节的循环神经⽹络的从零开始实现中 这个地方封装进行one_hot编码时候会报错- ‘Tensor’ object has no attribute ‘T’ 应该是笔误或者版本迭代的问题，实际上pytorch并不支持直接用.T进行张量的转置，常用的方法有 tensor.t() or tensor.transpose(dim1,dim2) 更改后的整个RNN的从零实现的完整代码： import math import ...
How can I fix this error I downloaded this code from GitHub.predicted_id = tf.multinomial(tf.exp(predictions), num_samples=1)[0][0].numpy() throws the error ...