Questions tagged [tensorflow]

Question 1

I am trying to learn Kaggle TPU and I am migrating a Flower Classification notebook from an older TPU v3-8 environment to the new TPU v5e-8 (TPU VM) environment on Kaggle. I was trying to migrate this ...

Question 2

I'm working with a custom YOLO-like architecture implemented in TensorFlow/Keras. While pretraining on the COCO dataset works, I plan to fine-tune the model on a highly imbalanced dataset. ...

Question 3

As the part of my college project on RNN, I'm working on a text classification task using tensorflow module. During training, I used pad_sequences with a max_length of 100, so all training examples ...

Question 4

I am training an DensNet model on medical dataset which has gold standards as per annotation. After training i noticed accuracy is just 60%. Later i performed following changes but still no luck. ...

Question 5

I am trying to train a GNN but am getting a NaN loss function immediately after the first training example. Below I have included all of the pertinent code. My input is 385 points in 3D space confined ...

Question 6

I tried modifying the reconstruction loss such that values that are pushed out of bounds do not contribute to the loss and it works as expected in tensorflow after training an autoencoder. However, ...

Question 7

here is the code from the Distance layer part because site is not allowing me to upload full code. embedding = make_embedding() distance layer ...

Question 8

I'm training a Deep Q-Network (DQN) to trade crypto using historical data. My model keeps outputting NaN values for the Q-values during prediction. I'm using a custom function getState2() to generate ...

Question 9

I'm trying to build a BNN but am encountering the error in the title. I tried to ensure I'm not passing a tuple to .shape.rank by : using the functional API with explicit Input (should make first ...

Question 10

I have found several documentation and tools for converting ONNX model to float16, but none of them supports converting to bfloat16. The model is originally trained using tensorflow and converted to ...

Question 11

I’ve made a couple of neural networks that predict separate target features form the same dataset. All these networks have different hyperparameters and different function transforms for example (log) ...

Question 12

I have collection of TEC data.My data sample for example the day1,day2,day3,day4. Case1: I have the following task to do: Training by the consecutive 3 days to predict the each 4th day. Each day data ...

Question 13

I have a feature dataframe that has a shape of (100,18). 18 features for 100 different points. One of those features is time. The model will then output an array with shape of (100,16). The model has ...

Question 14

I need to collect information from 5 websites say once a week and then keep only the relevant info in a formatted manner. relevance here means relevant to my topics. I intend to automate this -from ...

Question 15

I am attempting to subsample a timeseries dataset to reduce training time. Because I am using a mapping / window generator I want to apply this subsampling / dropping after the data samples are ...

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Questions tagged [tensorflow]

Kaggle TPUv5e8 7 times slower than v3

What loss functions are suitable for a YOLO-like architecture in TensorFlow/Keras, especially for fine-tuning on an imbalanced dataset?

Variable Length Input: How to handle longer input sequences during model testing

DensNet169 model accuracy not increasing on medical classification dataset

GNN Loss NaN after first training example?

Custom loss function not behaving as expected in PyTorch but does in TensorFlow

Getting ValueError: Unexpected object from deserialization, expected a layer or operation, got a <class 'main.L1Dist'> while reloading the model

Q-values output is NaN in DQN model - input state is normalized and padded

tuple has no attribute "rank" error when trying to build bayesian neural net

ONNX - How do I convert ONNX float32 model to bfloat16?

Multinodal vs modular neural network

Time series predictions with LSTM

Tensorflow tape.gradient to calculate a 2d array with respect to a single column of the 2d array input

Need to automate collecting relevant information from websites and creating valuable insights

Tensorflow "your input ran out of data" warning despite using .repeat()

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