logo
down
shadow

TENSORFLOW QUESTIONS

Regression accuracy with neural network in low density regions
Regression accuracy with neural network in low density regions
hop of those help? You could assign the observations to deciles, turn it into a classification problem and either assign a greater weight to the ranges you care about in the loss or just simply oversample them during training. By default, I'd go with
TAG : tensorflow
Date : January 12 2021, 01:40 AM , By : Yolanda N. Ceron
Keras backend mean function: " 'float' object has no attribute 'dtype' "?
Keras backend mean function: " 'float' object has no attribute 'dtype' "?
To fix this issue I am trying to introduce a new kernel regularize for a network using Keras. But, it gives me the error: 'float' object has no attribute 'dtype' How can I fix it? , You should change your KL divergence regularizer to:
TAG : tensorflow
Date : January 11 2021, 03:28 PM , By : Alex Sadzawka
What is the difference between conv1d with kernel_size=1 and dense layer?
What is the difference between conv1d with kernel_size=1 and dense layer?
With these it helps Yes, since Dense layer is applied on the last dimension of its input (see this answer), Dense(units=N) and Conv1D(filters=N, kernel_size=1) (or Dense(units=N) and Conv2D(filters=N, kernel_size=1)) are basically equivalent to each
TAG : tensorflow
Date : January 11 2021, 11:39 AM , By : fayoh
Adding Dropout to MobileNet with TensorFlow 2
Adding Dropout to MobileNet with TensorFlow 2
I hope this helps . I'm using MobileNet and TensorFlow 2 to distinguish between 4 fairly similar toys. I have exactly 750 images for each toy and one label that contains 750 'negative' images, without any of the toys. , Since the Model is Over fittin
TAG : tensorflow
Date : January 09 2021, 02:14 PM , By : user92243
Tensorflow Fit exits with code 1 without any error message
Tensorflow Fit exits with code 1 without any error message
To fix the issue you can do A couple of things to tweak.Firstly, I don't think the data is the shape that you think it is. You have:
TAG : tensorflow
Date : January 07 2021, 07:50 AM , By : KS9
LSTM 'recurrent_dropout' with 'relu' yields NaNs
LSTM 'recurrent_dropout' with 'relu' yields NaNs
I hope this helps you . Studying LSTM formulae deeper and digging into the source code, everything's come crystal clear - and if it isn't to you just from reading the question, then you have something to learn from this answer.Verdict: recurrent_drop
TAG : tensorflow
Date : January 06 2021, 03:27 AM , By : George H.
How can I deploy a model that i trained on amazon sagemaker locally?
How can I deploy a model that i trained on amazon sagemaker locally?
hope this fix your issue SageMaker BlazingText comes in 2 flavors: a supervised version, that learns to classify variable-length token sequences and an unsupervised version, that learns token embeddings.
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Blight
how to properly saving loaded h5 model to pb with TF2
how to properly saving loaded h5 model to pb with TF2
this will help I load a saved h5 model and want to save the model as pb. The model is saved during training with the tf.keras.callbacks.ModelCheckpoint callback function. , I do save the model to pb from h5 model:
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : user182548
Convert a TensorFlow model in a format that can be served
Convert a TensorFlow model in a format that can be served
around this issue There is multiple ways of doing this, and other methods could be required for more complex models. I am currently using the method described here, which works great for tf.keras.models.Model and tf.keras.Sequential models (not sure
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Genipro
Tensorflow tf.data AUTOTUNE
Tensorflow tf.data AUTOTUNE
it should still fix some issue tf.data builds a performance model of the input pipeline and runs an optimization algorithm to find a good allocation of its CPU budget across all tunable operations. While the input pipeline is running, tf.data tracks
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Terrence Poon
Partitioned matrix multiplication in tensorflow or pytorch
Partitioned matrix multiplication in tensorflow or pytorch
it fixes the issue You can think of representing your large block matrix in a more efficient way.For instance, a block matrix
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Lathentar
What is a fused kernel (or fused layer) in deep learning?
What is a fused kernel (or fused layer) in deep learning?
I hope this helps . "Kernel" here is for computation kernels: https://en.wikipedia.org/wiki/Compute_kernel Operations like convolution are often implemented using compute kernels for better efficiency. Compute kernels can be written using C, CUDA, Op
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : usingtechnology
Tesorflow Custom Layer in High level API: throws object has no attribute '_expects_mask_arg' error
Tesorflow Custom Layer in High level API: throws object has no attribute '_expects_mask_arg' error
I wish this helpful for you I just had the same error and it was due to me forgetting to call .__init__() after super(). You did it, but this make me think that this error is due to wrong initialization of the base layer you are deriving from. I noti
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Fahad
How to decode float32 encoded png to tensor?
How to decode float32 encoded png to tensor?
I wish this help you The .png format stores the channel values as uint8.To convert to float32 between 0 and 1 we can just cast then divide by 255 (the max value of uint8).
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : eataix
Converting Python Keras NLP Model to Tensorflowjs
Converting Python Keras NLP Model to Tensorflowjs
may help you . Actually, I ran into the same problem while classifying text on Android. I had the model ( tflite ) ready to use, but how can I tokenize the sentences just as Keras did in Python. I found a simple solution which I have discussed here (
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : ponchopilate
Is it possible to use Keras to optimize the coefficients of a mathematical function?
Is it possible to use Keras to optimize the coefficients of a mathematical function?
I hope this helps . If you are asking how to do polynomial regression using neural networks, here's the recipe.Your dataset consists of points (x, y). Design your network to be a fully connected network (dense network) with 1 input layer and 1 output
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Gerhard Miller
how to see tensor value of a layer output in keras
how to see tensor value of a layer output in keras
I think the issue was by ths following , I have a Seq2Seq model. I am interested to print out the matrix value of the output of the encoder per iteration. , Very simple way to print a tensor :
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Val
How to extract data/labels back from TensorFlow dataset
How to extract data/labels back from TensorFlow dataset
I wish this helpful for you Supposing our tf.data.Dataset is called train_dataset , with eager_execution on, you can retrieve images and labels like this:
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Sandeep Arneja
Reduce console verbosity
Reduce console verbosity
With these it helps EDIT: As (the vastly more qualified to talk about this topic than me) Jim Cownie points out, this output appears to be due to having KMP_AFFINITY defined with the attribute verbose. See The KMP_AFFINITY Environment Variable and se
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : phil
Can I aggregate over gradients in tensorflow-federated?
Can I aggregate over gradients in tensorflow-federated?
This might help you As of release 0.2.0, TensorFlow Federated includes an implementation of FedSGD (tff.learning.build_federated_sgd_process()), as described by the paper:Communication-Efficient Learning of Deep Networks from Decentralized Data H. Br
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Richard
AttributeError: module 'tensorflow' has no attribute 'ConfigProto'
AttributeError: module 'tensorflow' has no attribute 'ConfigProto'
like below fixes the issue I'm working in Pytorch. I can import tensorflow (version 1.13.1) and need ConfigProto: , ConfigProto disappeared in tf 2.0, so an elegant solution is:
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Richard
How to deploy cnn file
How to deploy cnn file
this one helps. Concerning the first error, I the problem is that the flask app tries to load the complete model (i.e. with configuration):
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Ram
How to find bounding boxes coordinates in Tensorflow Object Detection API
How to find bounding boxes coordinates in Tensorflow Object Detection API
wish help you to fix your issue The values in output_dict['detection_boxes'] are indeed in normalized format. By checking the values in the array you provided, those values are all between 0 and 1, therefore they are reasonable.There are 100 boxes be
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Alan Little
How does BERT utilize TPU memories?
How does BERT utilize TPU memories?
hope this fix your issue This is probably due to the advanced compiler that comes with TPU and optimized for tensorflow ops. As the readme - out-of-memory issues in BERT says,
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : S Hall
SSD mobilenet model does not detect objects at longer distances
SSD mobilenet model does not detect objects at longer distances
To fix the issue you can do Changing aspect ratios and scales won't help improve the detection accuracy of small objects (since the original scale is already small enough, e.g. min_scale = 0.2). The most important parameter you need to change is feat
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : wiznick
Fine tuning last x layers of BERT
Fine tuning last x layers of BERT
it helps some times You can set it manually in the trainable variables list. The following is my implementation of Bert layer in tensorflow-keras-
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Erwin
How to use the PASCAL VOC dataset in the xml format to build the model in tensorflow
How to use the PASCAL VOC dataset in the xml format to build the model in tensorflow
should help you out The Tensorflow Object Detection API provides a tool for it, you can run the following command:
TAG : tensorflow
Date : January 02 2021, 06:48 AM , By : Ben Humphrys
I am creating a CNN function with TensorFlow, but I get a Shape related error
I am creating a CNN function with TensorFlow, but I get a Shape related error
Hope that helps As per the official documentation here, input tensor should be of shape [batch, in_height, in_width, in_channels] and a filter / kernel tensor should be of shape [filter_height, filter_width, in_channels, out_channels].Try by changing
TAG : tensorflow
Date : January 02 2021, 05:18 AM , By : user182548
Is dropout layer still active in a freezed Keras model (i.e. trainable=False)?
Is dropout layer still active in a freezed Keras model (i.e. trainable=False)?
This might help you Short answer: The dropout layers will continue dropping neurons during training, even if you set their trainable property to False.Long answer: There are two distinct notions in Keras:
TAG : tensorflow
Date : January 01 2021, 06:10 PM , By : cmhudson
Custom layer updates
Custom layer updates
wish help you to fix your issue There are two types of weights: Trainable = Updated automatically by the optimizer with backpropagation Untrainable = Not updated by backpropagation
TAG : tensorflow
Date : January 01 2021, 06:44 AM , By : Scott Everts
Universal sentence encoding embedding digits very similar
Universal sentence encoding embedding digits very similar
hope this fix your issue If your sentence embedding are produced using the embeddings of individual words (or tokens), then a hack could be the following: to add dimensions to the word embedding. These dimensions would be set to zero for all non-nume
TAG : tensorflow
Date : December 31 2020, 03:06 AM , By : Amin Amini
tf.nn.softmax behaving strangely
tf.nn.softmax behaving strangely
around this issue If you are using tf.nn.softmax(), and you don't specify the axis, it defaults to tf.nn.softmax(logits ,axis=1) hence giving a tensor ouput where all values are 1s . In my case I was getting wrong values just because of not providing
TAG : tensorflow
Date : December 31 2020, 03:06 AM , By : ChristianM
Session graph is empty although graph is set as default
Session graph is empty although graph is set as default
wish of those help A couple of errors: You are instantiating a model model = load_vgg_model("imagenet-vgg-verydeep-19.mat") then reseting the default graph tf.reset_default_graph() → it should be the other way around. You have one tf.InteractiveSessi
TAG : tensorflow
Date : December 30 2020, 04:10 PM , By : user149634
How to serialize data in example-in-example format for tensorflow-ranking?
How to serialize data in example-in-example format for tensorflow-ranking?
this one helps. The context is a map from feature name to tf.train.Feature. The examples list is a list of maps from feature name to tf.train.Feature. Once you have these, the following code will create an "example-in-example":
TAG : tensorflow
Date : December 28 2020, 02:06 PM , By : eusden
Could I use BERT to Cluster phrases with pre-trained model
Could I use BERT to Cluster phrases with pre-trained model
wish helps you You can feed a phrase into the pretrained BERT model and get an embedding, i.e. a fixed-dimension vector. So BERT can embed your phrases in a space. Then you can use a clustering algorithm (such as k-means) to cluster the phrases. The
TAG : tensorflow
Date : December 27 2020, 04:54 PM , By : vdavidovski
How does Tensorflow 1.x traverse the computation graph given a Tensor?
How does Tensorflow 1.x traverse the computation graph given a Tensor?
I think the issue was by ths following , That's the whole point of Tensorflow's static computational graph. When you build the graph, Tensorflow implicitly builds a static graph in the background. Then, when you execute a node in the graph, Tensorflo
TAG : tensorflow
Date : December 27 2020, 04:28 PM , By : Kubla Khan
decode_png returns shape of 3 dimensions of question marks
decode_png returns shape of 3 dimensions of question marks
this will help Nothing wrong with your code, you just need to execute the operation with a tf.Session(). This works for me:
TAG : tensorflow
Date : December 27 2020, 04:18 PM , By : OllieDoodle
Accuracy on test set does not increase
Accuracy on test set does not increase
help you fix your problem Your loss is going to 'nan', this is happening because your loss function is not robust, i.e. when Y_pred_prob is zero it goes to -inf. You can change it like this:
TAG : tensorflow
Date : December 26 2020, 02:30 AM , By : afds
Tensorflow/Keras - how to expose relations between categories?
Tensorflow/Keras - how to expose relations between categories?
Does that help One-Hot Encoding is common for multi-class classification problems. In your case, a category 3 event label would be encoded as [0, 0, 1, 0, 0]. You would create a model with a dense output layer with softmax activations, then to get a
TAG : tensorflow
Date : December 26 2020, 12:01 AM , By : Gazza
how to set steps_per_epoch in varibale input length in fit_generator keras
how to set steps_per_epoch in varibale input length in fit_generator keras
To fix this issue What you can do is first make a function that pre-computes the value of steps_per_epoch by iterating on the dataset and computing this value, and then pass it to fit_generator. Something like:
TAG : tensorflow
Date : December 25 2020, 10:01 PM , By : leorick
keras split Input for multiple "mini-units"
keras split Input for multiple "mini-units"
I wish this help you Trying to implement this article.
TAG : tensorflow
Date : December 25 2020, 05:02 PM , By : 22.
"Could not compute output" error using tf.keras merge layers in Tensorflow 2
"Could not compute output" error using tf.keras merge layers in Tensorflow 2
hop of those help? Ok well the error message was not helpful but I eventually stumbled upon the solution: the input to model needs to be an iterable of tensors, i.e.
TAG : tensorflow
Date : December 25 2020, 04:30 PM , By : bjorngylling
Flag for training and test for custom layer in Keras
Flag for training and test for custom layer in Keras
To fix this issue There are some issues and misconceptions here. First you are mixing imports between keras and tf.keras imports, you should use only one of them. Second the parameter for call is called training, not is_training.I think the issue is
TAG : tensorflow
Date : December 25 2020, 02:01 PM , By : semicolonth
Restarting learning process from scratch for best results?
Restarting learning process from scratch for best results?
it fixes the issue It is pretty normal to see a small amount of variance in different runs no matter how long a model is trained for, though not at the magnitude you are seeing.Is the decrease in loss actually reflected in the test set accuracy? Loss
TAG : tensorflow
Date : December 25 2020, 11:01 AM , By : Brian
Training custom tf.keras.model with model.fit() InvalidArgumentError
Training custom tf.keras.model with model.fit() InvalidArgumentError
may help you . The problem seems to be with x_train and y_train shapes. It expected to be (n_samples, 1). try out:
TAG : tensorflow
Date : December 25 2020, 11:01 AM , By : mlapida
GAN generator loss goes to zero
GAN generator loss goes to zero
wish of those help In the blogpost comments people argues about the GAN's collapse problem, here you have a comment:
TAG : tensorflow
Date : December 25 2020, 09:30 AM , By : inquiringmind
Meaning of tf.keras.layers.LSTM parameters
Meaning of tf.keras.layers.LSTM parameters
hop of those help? activation vs recurrent_activation If you look at the LSTM equations. activation (defaults to sigmoid) refers to the activations used for the gates (i.e. input/forget/output), and recurrent_activation (defaults to tanh) refers to t
TAG : tensorflow
Date : December 25 2020, 09:19 AM , By : user171555
Implement custom loss function in Tensorflow 2.0
Implement custom loss function in Tensorflow 2.0
this will help You can pass the class weights directly to the model.fit function.
TAG : tensorflow
Date : December 25 2020, 09:19 AM , By : sadboy
Tensorflow 2 Hub: How can I obtain the output of an intermediate layer?
Tensorflow 2 Hub: How can I obtain the output of an intermediate layer?
it helps some times I am trying to implement following network Fots for Text detection using the new tensorflow 2. The authors use the resnet as the backbone of their network, so my first thought was to use the tensoflow hub resnet for loading a pret
TAG : tensorflow
Date : December 25 2020, 07:30 AM , By : Thx1138.6
How to find stride/padding information of a specific layer in h5 model of tensorflow or keras
How to find stride/padding information of a specific layer in h5 model of tensorflow or keras
this one helps. The model configuration is stored as a JSON inside the HDF5 file as an attribute of the root dataset, you can get it with this code:
TAG : tensorflow
Date : December 25 2020, 07:01 AM , By : user185751
Can someone give me an explanation for Multibox loss function?
Can someone give me an explanation for Multibox loss function?
it fixes the issue SSD Multibox (short for Single Shot Multibox Detector) is a neural network that can detect and locate objects in an image in a single forward pass. The network is trained in a supervised manner on a dataset of images where a boundi
TAG : tensorflow
Date : December 25 2020, 06:47 AM , By : tayles
ImportError: cannot import name 'abs' from tensorflow.python.keras._impl.keras.backend
ImportError: cannot import name 'abs' from tensorflow.python.keras._impl.keras.backend
wish of those help Hi,I was able to resolve this issue by removing all the tensorFlow and keras python3 packages from dist-packages dir itself , uninstalling using pip3 and then again installing tensorflow==1.8.0
TAG : tensorflow
Date : December 25 2020, 06:47 AM , By : Jorge Palacio
How do you feed one tf keras layer an already defined weight matrix?
How do you feed one tf keras layer an already defined weight matrix?
hope this fix your issue The tf.keras.Layer.set_weights() should do the trick for you.
TAG : tensorflow
Date : December 24 2020, 08:01 PM , By : alexmajy
SageMaker and TensorFlow 2.0
SageMaker and TensorFlow 2.0
Any of those help Here is an example Dockerfile that uses the underlying SageMaker Containers library (this is what is used in the official pre-built Docker images):
TAG : tensorflow
Date : December 24 2020, 06:01 PM , By : user107506
How do I prune over the highest weights in tensorflow layer? tfmot.sparsity.keras.prune_low_magnitude
How do I prune over the highest weights in tensorflow layer? tfmot.sparsity.keras.prune_low_magnitude
this one helps. Assuming that w is the weight matrix of the layer you want to prune, and k is the percentage of weights that should be pruned, this should do the trick for you:
TAG : tensorflow
Date : December 24 2020, 05:01 PM , By : Andrew
module 'tensorflow' has no attribute 'get_default_graph'
module 'tensorflow' has no attribute 'get_default_graph'
wish help you to fix your issue I am trying to build a deep learning model but I am getting an error using tensorflow and I am failing to fix this issue. , You are mixing the keras and tf.keras packages in your imports:
TAG : tensorflow
Date : December 24 2020, 12:01 PM , By : fayoh
How to choose units for dense in TensorFlow - keras?
How to choose units for dense in TensorFlow - keras?
fixed the issue. Will look into that further Those are called hyperparameters and should be tuned on a validation/test set to tweak your model to get an higher accuracy.Tuning just means trying different combinations of parameters and keep the one wi
TAG : tensorflow
Date : December 24 2020, 08:30 AM , By : Wilfred Knigge
MatMul wasn't able to infer shape because input dimensions are not compatible
MatMul wasn't able to infer shape because input dimensions are not compatible
wish help you to fix your issue Excact input shape is required for the mo_tf to work i.e. input_shape = [1, 10, 50]. Using -1, 0 or skiping the 1st dimension will raise the error.
TAG : tensorflow
Date : December 24 2020, 04:30 AM , By : Sebastian Gift
Tensorflow 2.0 beta GPU running in jupyter notebook, but not in google colab
Tensorflow 2.0 beta GPU running in jupyter notebook, but not in google colab
it fixes the issue If you can get it running on your own Jupyter server then you can point colab to that local server.Full instructions here: https://research.google.com/colaboratory/local-runtimes.html but edited highlights are:
TAG : tensorflow
Date : December 24 2020, 12:01 AM , By : Gerhard Miller
Expected a callable, found non-callable tensorflow_federated.python.learning.model_utils.EnhancedTrainableModel
Expected a callable, found non-callable tensorflow_federated.python.learning.model_utils.EnhancedTrainableModel
should help you out The argument to build_federated_averaging_process should be the model_fn function, not the return value from invoking it.Try changing this line:
TAG : tensorflow
Date : December 24 2020, 12:01 AM , By : Kyle

shadow
Privacy Policy - Terms - Contact Us © scrbit.com