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Questions tagged [tensorflow]

TensorFlow is an open source library for machine learning and machine intelligence. TensorFlow uses data flow graphs with tensors flowing along edges. For details, see https://www.tensorflow.org. TensorFlow is released under an Apache 2.0 License.

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Execution time of the same algorithm for different runs

There is this ongoing discussion with me and my advisor. We have a Deep Learning algorithm (does not matter which one it is, I believe, such as CNN, LSTM etc..). We are using 4 GPU Nvidia machine ...
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how to run CNN model traning on one GPU and a validation on another GPU in multiple GPU inviroment using tensorflow?

I am working on a medical image classification using CNN, the data size is large and I need more vram to validate the model, the desktop that I use has two 1080ti ...
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How to integrate google cloud with dropbox and jupyter notebook using tensorflow

So I opened up a google cloud account and have access to global and local (us east 1) resources (Compute Engine API , NVIDIA K80 GPUs) and connected it to my dropbox. Next, I followed this youtube ...
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Clustering text post vectorization by Universal sentence encoder

I have 1000 of datasets within which clustering needs to happen in each of them to find the textual categories. I have vectorized the data using google sentence encoder. What can be the best way to ...
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Approach fpr extracting/cropping features images using deeplearning and no annotations

Let's say I want to have a bunch of images of hats from videos. How would I priniciple build something that would learn to recognize, and crop or bound box hats? I heard you need a dataset with ...
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Different testing and training accuracy values within a NN TensorFlow structure

In order to select the optimum number of my gradient descent algorithm, I had used a for loop of 1500 iterations and each 100 iterations training and testing accuracies are printed. Here everything is ...
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How general are the possible computations of a tensorflow Graph?

Tensorflow works through the creation of computational graphs. I know about tensorflow in the context of machine learning, specifically deep learning. But I know that tensorflow can also be used for ...
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How to add three csv file into one LSTM using python

I have three csv files with same inputs but values are different. I want to add these three csv file into one LSTM model to predict value. Hare I upload the three different csv file and my LSTM code....
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Is it possible to set GPU affinity for a mixed precision NN, with FP32 and FP16 going to different GPUs? [migrated]

I have a GTX 1080 and an RTX 2080. I want to train using both, but since the RTX can handle FP16 twice as fast, I'd like to set it up so that the training is multi-GPU and the RTX handles the FP16 ...
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21 views

How is this tensorflow command interpreted?

I am reading an introductory tutorial on tensorflow here, and I'm confused about the code that defines an input layer for a word2vec embedding: ...
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How to develop custom metric with one class priority Keras

I tried like this. I get InvalidArgumentError, but I assume I am doing this completely wrong, I just don't know how to implement in in Tensorflow. ...
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Neural Network Initialization - Every layer?

Does every layer of a Neural Network require weight initialization or just the first? Does the first layer feed into the next layer and initialize itself? My intuition is that every layer needs its ...
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1answer
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Computing number of batches in one epoch

I have been reading through Stanford's code examples for their Deep Learning course, and I see that they have computed ...
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How to use TF-IDF with tensorflow in Python 3.5? [on hold]

TF-IDF could be implemented with Tensorflow-transform. However, Tensorflow-Transform is not supported in Python 3.5. I know about sklearn's TfidfVectorizer() but I want to utlize GPU for it, hence, ...
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How to shift output of predict values into the x (input) column 0 values using Neural network in python

The inputs here are the 3. The output here (LSTM) is the probabilities that the next x1 input ought to be. Means here I have x,x1,x2 input values. 1st three inputs LSTM output1 and then next if x ...
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How to feed output of predict value back into the input using LSTM in python

The inputs here are the 3. The output here (LSTM) is the probabilities that the next x1 input ought to be. Means here I have x1x2 and x3 input values. 1st three inputs LSTM output1 and then next if x1 ...
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How to get probabilities values with keras?

tensorflow version = '1.12.0' keras version = '2.1.6-tf' I'm using keras with tensorflow backend. I want to get the probabilities values of the prediction. I want the probabilities to sum up to 1. ...
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How to calculate the gradient for nce_loss in tensorflow

I need to calculate the gradient of a tensorflow that is stored. I can restore the graph and weights using: ...
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1answer
35 views

Keras Applications - using images larger than the default size

I would like to use eg Xception network with default input size 299x299, but my images are 450x600. Are there any other options besides cropping and subsampling ?
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How to turn linear regression into logistical regression

I followed these articles to implement logistic regression. I'm confused however because after training the model and getting the weights for my variables I don't now how to use the one-hot vector ...
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Tensorflow Deep learning network not utilizing GPU?

I have a Nvidia GeForce GT 755M (PC), which I heard should be at least functional for running deep learning models. But when I train my model (DCGAN) and check the task manager process info (Win 10) I ...
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1answer
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Recognizing circled numbers on a piece of paper

I've built a handful of CNN using tensorflow, keras, pytorch for recognizing text/number/objects in an image. What I'm trying to figure out how to do now is how to recognize numbers on a piece of ...
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26 views

Calculating saliency maps for text classification

I'm following the text classification with movie reviews TensorFlow tutorial, and wanted to extend the project by looking, for a certain input, which words influenced the classification the most. I ...
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1answer
17 views

Can I use the Softmax function with a binary classification in deep learning?

I want to create a deep learning model (CNN) for binary classification, can I used the softmax function instead of the sigmoid function in binary classification? Adding the classification layer to ...
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1answer
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Do I classify all types if they are mutually exclusive

I am trying to classify an image that can represents 3 states. Up, down or Middle. If the image does NOT represent Up or Down, then it is by default Middle. Should I train my CNN with a dataset ...
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1answer
37 views

Output probabilities for each class on tensorflow sigmoid function

I have a piece of code that uses tf.nn.softmax to predict whether does a image belongs to either class 0, 1, 2... etc. However, I want to edit the code to using sigmoid as the activation function ...
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Passing variable length sentences to Tensorflow LSTM

I have a tensorflow LSTM model for predicting the sentiment. I build the model with the maximum sequence length 150. (Maximum number of words) While making predictions, i have written the code as ...
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82 views

Odd Loss Curves for Object Detection Task

I'm re-training a Single Shot Detector (specifically the ssdlite_mobilenet_v2_coco from the TensorFlow model zoo) to detect some new images. I have about 15k images in the training set and about 4k in ...
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InvalidArgumentError for placeholder

I'm copying an example directly out of a book I am working through, and I currently getting this error: ...
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14 views

Dealing with Error in Neural Network input

When you are building a neural network in which the input values are known to have error is there a way to incorporate this into the network? I.e one value of the input features may have a known small ...
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1answer
35 views

Production: TensorFlow and Keras

I always here about TensorFlow is good because it is used for deploying and production. Does that mean that people don't use Keras for deploying models? If keras is now integrated into TensorFlow, ...
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The Question is about Deep Learning how to skip intro in movies

I want to skip the introduction and post credit scenes (such as..,Namecard scenes )in movies using deep learning.How do do it by using Tensorflow object detection api. Is it possible to do that using ...
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ValueError: Error when checking target: expected dense_3 to have shape (None, 1) but got array with shape (7715, 40000)

I'm trying to train a Keras model with Google Cloud's ML Engine. (Keras version is 2.2.4 and TensorFlow version is 1.12.0) This exact code runs fine on my CPU but when I submit the job to cloud, ...
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static graphs v.s. dynamic graphs

In summary, static graphs are easy to optimize but lack the expressivity found in higher-level languages; dynamic graphs provide this missing expressivity but introduce new compilation and execution ...
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Solving an ODE using neural networks (via Tensorflow)

I'm very new to deep learning (coming from a math PDE background), but I'm trying to solve some ODEs using a neural network (via tensorflow). I've solved some simple ones like $u'(x)+u(x) = f(x)$ with ...
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1answer
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Running Neural Network experiments in loop

I need to run neural network training with different hyper parameters settings like this: ...
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Implementing WARP Loss in Tensorflow

I notice there are attempts to implement WARP loss in Keras such as (https://stackoverflow.com/questions/46299554/implimentation-of-warp-loss-in-keras) But I have not seen any githubs or publications ...
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How to define a multi-dimensional neural network with keras

I have implemented a simple neural network with keras that takes an input of 50 values and returns a classification of '0' or '1'. I believe the model is expecting an input shape of (50, 1). I'd ...
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Determine input array that approximates a target output array from complex numerical simulation?

I believe the following problem is ideally suited to a machine intelligence approach, but am unsure where to start. I've used scikit-learn previously with downloaded datasets, but the following seems ...
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why running inference with tensorflow (object-detection) ssdlite gives only one detection per image?

I trained (using a downloaded checkpoint) the ssdlite v2 pet detection on my custom recorded dataset, while running the inference, it detects only one object per image in best case. Does the fact ...
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3answers
176 views

Deep network not able to learn imbalanced data beyond the dominant class

I have data with 5 output classes. The training data has the following no of samples for these 5 classes: [706326, 32211, 2856, 3050, 901] I am using the following keras (tf.keras) code: <...
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tf.trainable_variables() returns blank list outside model_fn

In a downloaded tensorflow code, when below model_fn_builder is called, then model_fn (down below) loads the ...
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How do you feed a VAE input layer a complex dataset form - an array with multiple sub-arrays?

I am currently trying to to pipe data into a simple VAE using Tensorflow but have encountered an issue. All the literature on VAEs are for images where tensors are typically squashed into 1D. The ...
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1answer
26 views

Feature importance decision algorithms

I have a dataset with 100+ feature columns. My client asked me to choose "the top 10 most important features" from the 100+. From this post, I learnt that Random Forest can help me ranking the ...
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How to inform class weights when using `tensorflow.python.keras.estimator.model_to_estimator` to convert Keras Models to Estimator API?

I'm having some trouble to convert a pure Keras model to TensorFlow Estimator API on an unbalanced dataset. When using pure Keras API, the class_weight parameter ...
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83 views

String Y Variable in TensorFlow

I am new to tensorflow and I am trying to predict tree species from a bunch of point data describing imagery in different ways. I have created a TensorFlow model but I think I am creating my y-data ...
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What is a good way to use time variables in tensorflow LSTM?

I have such variables as day of week and month available. I tried one-hot encoding them and adding to the other 13 variables and model performance became worse. My guess this is due to the curse of ...
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What does initial_state=None do to states in tf.nn.dynamic_rnn?

For some reason, my LSTM works better if I leave initial_state as None in comparison with resetting state at each epoch and each step (for a stateless LSTM) ala https://stackoverflow.com/a/41240243/...
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1answer
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Is it possible to use TensorFlow inside a python script in Azure Machine Learning Studio?

I'm trying to get TensorFlow running inside a python script in Azure Machine Learning Studio. As TensorFlow is not part of Azure Machine Learning Studio, I needed to import it using a zip file. I ...
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1answer
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How to run tensorflow model twice before computing the loss

I want to compute a loss function which uses output of the network twice on different inputs. For example as hypothetically, ...