Questions tagged [tensorflow]
A Python library for machine learning, in particular for deep learning, originally created by Google.
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Reference for Inception-v2
Cross-posted from Data Science StackExchange.
The "Rethinking" paper doesn't describe the actual implementation of the Inception-v3 model in Tensorflow: an accurate description is written in model....
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BiLSTMs with Attention model for Multi-Label Multi-Class Classification
I am trying the modify the BiLSTM with Attention model he used in Course 5 Neural Machine Translation for predicting grades (ranging from O,A+,A,B+,B,C,D,E,F) for multiple subject (approx 9 subjects ) ...
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How to handle timeseries extremes (sigma > 20) in deep learning?
I'm using 16-channel, 400-Hz, standardized EEG data to train CNN-LSTM for seizure classification. The data contains $O(3)$ sigma > 20 points, rarely thousands in a ...
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Resetting states in tf.kers.layers.RNN to different batchsize [closed]
I am trying to use a stateful RNN in Tensorflow Eager (link). For my validation set, in the end I have leftover sequences which arent a full batch. To reset the state for new sequences, I normally use ...
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Faster R-CNN is slower in Realtime prediction [closed]
I am trying to detect objects using Tensorflow Object Detection API. Have worked on both SSD and Faster R-CNN. SSD is fast when compared to Faster R-CNN. But in SSD I cannot able to detect objects in ...
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Is there a way to implement something like sklearn's GridSearchCV for Tensorflow estimators?
Grid Search CV works fine for sklearn models as well as keras, however do we have any alternative for this specifically for tf estimators? Would be great if someone can guide in right direction
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How to reduce impact of false positive images in Tensorflow Object Detection Framework?
I am training a single object detector(for car) with Faster R-CNN with Inception v2 config file. I started with around 300 examples of images of the object with bounding boxes and trained that, got ...
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Many false positives in a custom SSD model with Tensorflow object detection API
My model has 2 classes (no background class) and is trained using transfer learning with ssd_mobilenet_v2_coco. It detects and classifies well the objects it was trained on. However, on new images it ...
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1answer
22 views
Softmax with Cross Entropy optimization vs Backpropagation
I am following a tutorial from Analytics Vidhya on creating a neural network to recognize handwritten digits (the classic example).
The code from the tutorial states "First we need to define the ...
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19 views
Create TensorFlow Dataset with multiple data sources
I am trying to create a TensorFlow Dataset by joining data from 2 different sources. I am trying to replicate the dataset creation from the following paper:
https://arxiv.org/abs/1809.01984
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Pytorch logging: Native tensorboard support v/s TensorboardX
PyTorch recently released v 1.1.0, which has native support for Tensorboard. How does this compare with TensorboardX? I thought it would be good to list the pros and cons here.
I am new to PyTorch ...
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Reproducible numbers in Keras/TensorFlow
Every time I run a Keras/TensorFlow code gives different results. Can someone suggest how to get reproducible numbers?
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How do I implement masking in TensorFlow eager?
I am training a stateful RNN on variable length sequences (optional: see my previous question for more details).
I padded the sequences to a fixed length with the value -1.
The when batches are ...
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Meaning of kernel size 1 for 1-D convolution in Keras
The kernel size is the window size for 1D convolution. Can anyone explain what is meant by kernel size $1$ in Keras/TensorFlow?
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Replicating partial least squares (NIPALS) results using ordinary least squares regression in Tensorflow?
I have multivariate variables that I want to regress to a single target label. For some reason, using partial least squares regression (projected to a single component) gives much better prediction ...
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1answer
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why the neural network gives me null results? [closed]
I trying to predict some fluid parameters, you will find the data I use in the drive link (24 input and 3 output to predict): DATA. first of all I replaced the null values in the data with the ...
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Holdout loss much worse than training & testing data
I am creating a simple MLP which is to predict a single output based and 9 inputs.
The data is scaled between 0 and 1, and the data is shuffled before training.
The resulting model leads to very low ...
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Custom TF 2.0 training loop performing considerably worse than keras fit_generator - can't understand why
In trying to better understand tensorflow 2.0, I am trying to write a custom training loop to replicate the work of the keras fit_generator function. In my head, I have replicated the steps ...
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What kind of performance boost can you expect by using tflite
I am trying to prepare a tensorflow DNN for production on a linux server, and the inference is quite slow (1.5sec per step on CPU). I know that the theoretical performance increase with tflite 8-bit ...
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Accuracy of RNN getting stuck after 90% [duplicate]
I am using Keras RNN Cell to perform parts of speech tagging. The architecture is as follows(I cannot put the code because of privacy reasons) :
An embedding layer of of 40 units of shape (...
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Deep Learning Model for Complicated Pattern REcognition
I am using transfer learning using ResNet50 for snack packets recognition.
They are one and another similar in dominant color and shape. Those like in images below.
I have about 33 items to ...
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Simple Keras LSTM model does not converge [duplicate]
I try to predict time-series with simple Keras LSTM model:
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1answer
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Training with default BN parameters
Training with default BN parameters in tensorflow I obtain strange loss curve.
For experiment train and val are the same dataset.
Blue is val loss, orange is train loss.
BN with momentum 0.99 (...
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1answer
32 views
Why is there no Target Value function in PPO?
I just implemented the PPO algorithm in tensorflow and strictly followed the algorithm provided in the original PPO paper by Schulman et. al. 2017
Previously I did some experiments with the DDPG ...
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What type of neural network is used for image to restore pictures from pixels
When we have small low resolution, fuzzy image
for example:
and if it to zoom,
an unrelated set of pixels is obtained.
For example
Tell me, please is there the way to train a neural network to ...
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Got very poor accuracy whenever I train any deep neural network [duplicate]
I am trying to train a network on Alabone dataset downloaded from "UCI machine learning repository" site. The dataset is look like:
...
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Efficient way to do Autoencoder on large sparse matrix
I have a large csr_matrix of shape (60,000, 180,000) and about 99.7% sparsity. I was trying to train an autoencoder for this matrix via mini-batch optimization. I tried batch size of 6000 with ...
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190 views
why the accuracy of my CNN decreasing after some epochs?
at high accuracy, after some epochs the accuracy as well as validation accuracy is decreasing and got stuck after few more epochs. i dont understand why this happened. does more epochs at some point ...
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faulty autoencoder [duplicate]
I am developing an autoencoder for CIFA10 dataset, without adding noise at the input (which is 2nd goal).
The Convnet based autoencoder is not converging: Any suggestions
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23 views
Neuronal Network to approximate function from training samples [duplicate]
I'm trying to implement a neuronal network that approximates a certain function, although the term "function" here is mathematically probably imprecise and wrong. Anyway, here's the idea.
I have a ...
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1answer
29 views
What does linear regressor output mean? I am using tensorflow estimator in R
I try the code at tensorflow in R tutorial (https://tensorflow.rstudio.com/tfestimators/) but I cannot understand the output what the code produces.
Code:
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Machine Learning: Model doesn´t recognize letters but has 80% accuracy
I have build a model to classify numbers and characters on Images. I trained it on the Chars74K dataset and in training it has 80% validation accuracy. I just use the number and uppercase characters ...
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1answer
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Creating a neural network that can make a decision with optional arguments
I'm a final year computer science student and for my final year project I have to design a neural network to play a little known board game called 'The Downfall of Pompeii'.
I have to use ...
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1answer
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Catastrophic forgetting: Retraining a trained neural network with small data
I have a fully connected deep neural network with 7 hidden layers, which is trained with around 20000 simulated materials data. And we've got a very small measurement dataset (size<200) which ...
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Confusion with Computing Probabilities of a Normal Distribution without the Integral
How does this code is calculating the probability of Normal distribution without calculating the integral
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retraining an inception model with tensorflow fro image classification returns unusual results
I'm using tensorflow and tensorflow-hub to retrain an image classifier on my own classes following this link from tensorflow and using the retrain script. My dataset contains 348 images divided into 5 ...
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How can we detect People Name and his Designation/Role from a sentence using Deep learning?
Let's say for a paragraph like:
...
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1answer
61 views
Feed Forward Neural Network Time Series Regression
I'm trying to use the Tensorflow regression tutorial (with Keras) to do some regression on a time series with a couple of inputs. I will provide code if asked so.
My inputs are: [Day, Hour, Minute, ...
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3answers
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Why is binary cross entropy (or log loss) used in autoencoders for non-binary data
I am working on an autoencoder for non-binary data ranging in [0,1] and while I was exploring existing solutions I noticed that in many people (e.g., the keras ...
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How to predict similarity of unseen data to the training set?
I have a time series of human pose data which are recorded from real humans.
I want to train the model with unsupervised learning on the training data.
Let's call this the "real" training data.
The ...
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1answer
212 views
Parameters Grid Search for Keras LSTM on Time Series
How do you do grid search for Keras LSTM on time series? I have seen various possible solutions, some recommend to do it manually with for loops, some say to use scikit-learn GridSearchCV. Feedback ...
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1answer
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High AUC and Accuracy but weird output in confusion matrix
I am working on image classification problem to determine gender given a face. The dataset is located here gender face dataset on kaggle (link to my notebook). The class distribution is as follows.
<...
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1answer
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Tensorflow choice of values of variables after training [closed]
I am trying to build a neural network, that is able to perform a linear regression. After for example 1000 epochs, I encountered the situation, where the smallest loss-value was not the last loss-...
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1answer
225 views
Loss during minibatch gradient descent
I have minibatch gradient descent code in Tensorflow for function approximation, but I am unsure when to calculate the loss. First, I create batches for x and y data. Then, I shuffle both these ...
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Is it possible to have a constent accuracy for my tensorflow network whatever is the iterations?
I am runing my tf NN composed by one input, one hidden and one output layers the number of hidden nodes if the half of total features number I have got the next table considering different learning ...
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Is this Tensorflow bias vector shaped correctly?
In the text I read the following:
I’m confused on the dimensions of the bias vector. How can we add a(m,1) vector to a(1, p) ...
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Model Training and test accuracy suddenly dropping for a Mulit Layer Perceptron from 98% to 9% (test)? [duplicate]
I was exploring the tensorflow library and was working on an MLP for the mnist dataset. It is 5 layers MLP trained for 10000 iterations on batches of 100.
After training the model up to 9000 ...
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CTC classification for License Plate with two lines
I have gone through this tutorial and have understanding how CTC works for end to end text recognition.
But for recognition of images with texts in two lines
Would it be able to use CTC for ...
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ML Regressor model performance conclusion RSME vs STD DEV
Perhaps my question is still slightly silly but apparently even though lot of folks talk about how to evaluate the rightness of your model there still blur the right evaluation procedure at least for ...
