Here is the full code. This currently works just fine on my M1 MacBook running Monterey and Tensorflow-Metal. However, when I export the dataset and code to my laptop with an RTX 3060 Laptop GPU with Pop_OS! that is when I start getting the [UNK] characters generated and "NaN" loss.
24.01.2020 · System information Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Mac OS Catalina (Version: 10.15.2 (19C57)) TensorFlow install...
Aug 28, 2021 · Hi everyone, I am training an RNN and have come across the following error 247 input = cast(Tensor, input) 248 batch_sizes = None -->; 249 max_batch_size = input.size ...
Feb 13, 2019 · AttributeError: 'Tensor' object has no attribute 'numpy' in image_captioning_with_attention.ipynb #25731 DecentGradient opened this issue Feb 13, 2019 · 9 comments Assignees
The output of tf.nn.softmax_cross_entropy_with_logits on a shape [2,5] tensor is of shape ... in <module> AttributeError: "MyNT" object has no attribute "quux"
13.03.2019 · 1 Answer1. Show activity on this post. the row rewards.append (reward) causes the error, an it is because your rewards variable is a Tensor, as you defined it in rewards = tf.placeholder ('float32',shape= [None]) and you can not append values to tensor like that. You probably wanted to call rewards_list.append (reward).
Mar 06, 2021 · I got the error: AttributeError: 'NoneType' object has no attribute 'logits' I'm wondering where my code applying tutorial is wrong so that model can't be created. Addition Information
12.07.2019 · The issue tracker should only be used to report bugs or feature requests. If you are looking for support from other library users, please ask a question on StackOverflow. Hi, I am trying to train a DQN model based on RL-attack examples u...
AttributeError: 'list' object has no attribute 'size' with HuggingFace model ... input_ids object into pt (PyTorch Tensors), tf (TensorFlow Tensors) or np ...
Dec 09, 2021 · Show activity on this post. I am trying to train a neural network to do multiclass classification on each character of supplied text. This is the code I am using: xtrain = tf.ragged.constant (list (training ['encoded_text']), dtype=tf.int64) ytrain = tf.ragged.constant (list (training ['labels']), dtype=tf.bool) model = tf.keras.Sequential ...
In this setting there is no need to use variable sharing since the variables are kept as attributes of the model object. Also, after calling the training ...