The tag should be used for question exclusively related to TensorFlow >= 2.0 versions. There exist a couple of differences between TensorFlow2.X versions and TensorFlow1.X versions; therefore, it is natural that an exact tag distinction exists between those major version differences. Minor versions between TF 2.0(e.g. 2.0 vs 2.1) also bring code/framework differences; thus it will be incorrect to use the tensorflow2.0 tag at every question.
Questions tagged [tensorflow2.x]
252 questions
312
votes
16 answers
How to prevent tensorflow from allocating the totality of a GPU memory?
I work in an environment in which computational resources are shared, i.e., we have a few server machines equipped with a few Nvidia Titan X GPUs each.
For small to moderate size models, the 12 GB of the Titan X is usually enough for 2–3 people to…
Fabien C.
- 3,275
- 3
- 11
- 6
33
votes
2 answers
Custom TensorFlow Keras optimizer
Suppose I want to write a custom optimizer class that conforms to the tf.keras API (using TensorFlow version>=2.0). I am confused about the documented way to do this versus what's done in implementations.
The documentation for…
Artem Mavrin
- 565
- 7
- 13
30
votes
4 answers
Tensorboard not found as magic function in jupyter
I want to run tensorboard in jupyter using the latest tensorflow 2.0.0a0.
With the tensorboard version 1.13.1, and python 3.6.
using
...
%tensorboard --logdir {logs_base_dir}
I get the error :
UsageError: Line magic function %tensorboard not…
Florida Man
- 1,361
- 1
- 16
- 29
19
votes
3 answers
Should I use @tf.function for all functions?
An official tutorial on @tf.function says:
To get peak performance and to make your model deployable anywhere,
use tf.function to make graphs out of your programs. Thanks to
AutoGraph, a surprising amount of Python code just works with
…
problemofficer
- 1,502
- 2
- 16
- 29
9
votes
1 answer
Input pipeline w/ keras.utils.Sequence object or tf.data.Dataset?
I am currently using a tf.keras.utils.Sequence object to generate image batches for a CNN. I am using Tensorflow 2.2 and the Model.fit method for the model. When I fit the model, the following warning is thrown in each epoch when I set…
Connor
- 197
- 1
- 8
9
votes
2 answers
Get length of a dataset in Tensorflow
source_dataset = tf.data.TextLineDataset('primary.csv')
target_dataset = tf.data.TextLineDataset('secondary.csv')
dataset = tf.data.Dataset.zip((source_dataset, target_dataset))
dataset = dataset.shard(10000, 0)
dataset = dataset.map(lambda source,…
Evan Weissburg
- 1,690
- 2
- 11
- 36
5
votes
0 answers
Unexplained RAM usage and potential memory leak when using tf.data.TFRecordDataset
Background
We are relatively new to TensorFlow. We are working on a DL problem involving a video dataset. Due to the volume of data involved, we decided to preprocess the videos and store the frames as jpegs in TFRecord files. We then plan to use…
strider0160
- 369
- 3
- 9
5
votes
1 answer
How to debug out of memory in tensorflow2-gpu
I am using tensorflow-2 gpu with tf.data.Dataset.
Training on small models works.
When training a bigger model, everything works at first : gpu is used, the first epoch works with no trouble (but I am using most of my gpu memory).
At validation…
Wiwi
- 115
- 1
- 5
5
votes
1 answer
Tensorflow 2.1.0 - An op outside of the function building code is being passed a "Graph" tensor
I am trying to implement a recent paper. Part of this implementation involves moving from tf 1.14 to tf 2.1.0. The code was working with tf 1.14 but is no longer working.
NOTE: If I disable eager execution tf.compat.v1.disable_eager_execution()…
Darien Schettler
- 426
- 2
- 11
5
votes
1 answer
AttributeError: 'Tensor' object has no attribute 'numpy' in Tensorflow 2.1
I am trying to convert the shape property of a Tensor in Tensorflow 2.1 and I get this error:
AttributeError: 'Tensor' object has no attribute 'numpy'
I already checked that the output of tf.executing eagerly() is True,
A bit of context: I load a…
Nick Skywalker
- 673
- 6
- 18
5
votes
1 answer
shuffling two tensors in the same order
As above. I tried those to no avail:
tf.random.shuffle( (a,b) )
tf.random.shuffle( zip(a,b) )
I used to concatenate them and do the shuffling, then unconcatenate / unpack. But now I'm in a situation where (a) is 4D rank tensor while (b) is 1D, so,…
Alex Deft
- 1,460
- 8
- 19
5
votes
1 answer
What is the difference between keras.tokenize.text_to_sequences and word embeddings
Difference between tokenize.fit_on_text, tokenize.text_to_sequence and word embeddings?
Tried to search on various platforms but didn't get a suitable answer.
ASingh
- 83
- 4
4
votes
2 answers
AttributeError: module 'tensorflow_core.keras.layers.experimental.preprocessing' has no attribute 'RandomFlip'
I use Tensorflow 2.1.0
In this code
data_augmentation = tf.keras.Sequential([
tf.keras.layers.experimental.preprocessing.RandomFlip('horizontal'),
tf.keras.layers.experimental.preprocessing.RandomRotation(0.3)
])
I find this…
seni
- 439
- 1
- 10
4
votes
0 answers
CUDA_ERROR_NOT_INITIALIZED by model.predict() using tensorflow2.3
I use efficient-net with tensorflow2.3 API (keras==2.4.3)
https://www.tensorflow.org/api_docs/python/tf/keras/applications/efficientnet
I could train and prediction on jupyterlab.
On the other hand, while Flask implementation, model checkpoint could…
Takehiko Esaka
- 55
- 4
4
votes
0 answers
TensorFlowOpLayer messes up the TensorBoard graphs
This question is about TensorFlow (and TensorBoard) version 2.2rc3, but I have experienced the same issue with 2.1. It is a continuation of the question 'Messed up TensorBoard graphs due to Python operations'.
Consider the following code:
from…
Rani Pinchuk
- 51
- 1
- 5