All Questions
Tagged with tf.keras loss-function
27
questions
8
votes
1
answer
3k
views
Can SigmoidFocalCrossEntropy in Tensorflow (tf-addons) be used in Multiclass Classification? ( What is the right way)?
Focal Loss given in Tensorflow is used for class imbalance. For Binary class classification, there are a lots of codes available but for Multiclass classification, a very little help is there. I ran ...
- 3,862
8
votes
1
answer
6k
views
Tensorflow Keras RMSE metric returns different results than my own built RMSE loss function
This is a regression problem
My custom RMSE loss:
def root_mean_squared_error_loss(y_true, y_pred):
return tf.keras.backend.sqrt(tf.keras.losses.MSE(y_true, y_pred))
Training code sample, ...
- 370
2
votes
1
answer
451
views
How many times the loss function is triggered from .fit() method in Keras
I am trying to do some custom calculations in the custom loss function. But when I log the statements from the custom loss function, it seems that custom loss function is only called once (in the ...
- 47
2
votes
1
answer
535
views
Tensorflow 2.X : Understanding hinge loss
I am learning Tensorflow 2.X. I am following this page to understand hinge loss.
I went through the standalone usage code.
Code is below -
y_true = [[0., 1.], [0., 0.]]
y_pred = [[0.6, 0.4], [0.4, 0....
2
votes
0
answers
82
views
Negative loss values for adaptive loss in tensorflow
I have used adaptive loss implementation on a neural network, however after training a model long enough, I am getting negative loss values. Any help/suggestion would be highly appreciated! Please let ...
- 21
1
vote
1
answer
988
views
Keras custom loss with dynamic global variable
So, I am trying to write a custom loss function for my keras model. The loss function needs a global variable which changes after every epoch to calculate the loss, But I am not able to get the ...
1
vote
2
answers
131
views
2 outputs in Keras model but only one with missing value?
I'd like to model two variables simultaneously using the same features at the input layer (a feed-forward network), but there are missing values in one of them. I'm wondering if there is a way to mask ...
- 336
1
vote
0
answers
74
views
Same Accuarcy and Loss values over the epochs
I'm working on a project to classify the hand gestures of the "rock, paper, and scissors" game. I know there's already the "rps dataset" provided by tensorflow, but due to its ...
1
vote
1
answer
773
views
Weights were not updated using Gradient Tape and apply_gradients()
I am building a DNN with a custom loss function and I am training this DNN using Gradient Tape in TensorFlow.kerasenter code here. The code runs without any errors, however, as far as I can check the ...
- 13
1
vote
0
answers
393
views
Tensorflow custom loss function - can't get samples of y_pred and y_true in loss function
I'm running an LSTM network that works fine (TF 2.0). My problem starts when trying to modify the loss function.
I planed to adjust some data manipulation over 'y_true' and 'y_pred' but since TF force ...
- 11
1
vote
0
answers
591
views
Custom loss calculation causes RuntimeError: Attempting to capture an EagerTensor without building a function
Environment: tensorflow 2.2 on Windows 10 x64 in CPU only mode. Using tf.keras.
I want to build a simple model for image to text recognition (sometimes called OCR).
For this I use CRNN model ...
- 1,817
1
vote
0
answers
330
views
How to define a custom loss function for a multi-dimensional target
I'm working with Tensorflow 2.0 and I'm using a normal sequential layer.
I'm trying to define a custom loss functions which does the following:
takes some elements of the input
computes their sum ...
- 181
1
vote
2
answers
612
views
tf.keras two losses, with intermediate layers as input to of one of them error:Inputs to eager execution function cannot be Keras symbolic tensors
I want to have two losses in my tensorflow keras model and one of them takes an intermediate layer as input.
This code works when I use keras but when it comes to tensorflow.keras I face the ...
- 49
1
vote
0
answers
100
views
How to write a custom loss function for mulitple output keras model?
I have a multiple output keras model and currently I pass loss like this
model.compile(optimizer='adam', loss=['mse', 'binary_crossentropy'], metrics = ['accuracy'])
Instead of using two separate ...
- 14.6k
0
votes
1
answer
605
views
Loss function and batch size in Keras
For classification task there are several loss-function we can use.
If I simply use something like
model.compile{ loss=keras.losses.categorical_crossentropy, ....
Does this mean loss is normalized in ...
0
votes
1
answer
811
views
Tensorflow 2.5.0 - TypeError: An op outside of the function building code is being passed a "Graph" tensor
I am training a convolutional Bayesian Neural network where I use tfp.layers.Convolution3DFlipout layers. My loss function is as follows:
from tensorflow.keras.losses import binary_crossentropy
def ...
- 151
0
votes
1
answer
416
views
In model.fit in tf.keras, is there a way to pass each sample in a batch n times?
I am trying to write a custom loss function for a model that utilizes Monte Carlo (MC) dropout. I want the model to run through each sample in a batch n times before feeding the predictions to the ...
- 525
0
votes
1
answer
100
views
Customized keras loss function using min_g(g, g*)
I am dealing with a regression problem where given an image, I want to predict the value of 3 parameters (cartesian coordinates) . For the same image I can have several acceptable coordinates. To do ...
0
votes
0
answers
21
views
Passing a group id to custom loss function in Keras R
I was hoping that someone might be able to give me a hand.
I've been using keras to model a disease risk factor in 11 different populations and am trying to create a custom loss function that is aware ...
- 1
0
votes
1
answer
300
views
constrained optimization, adding an additional term in a custom loss function in a NN
I am struggling to add an additional constraint into my loss function (Keras, tensorflow)
My original loss function is:
self.__loss_fn = tf.reduce_mean(
tf.square( self.__psiNNy
...
- 5
0
votes
1
answer
37
views
Should I use reguaization with Loss function or NN layer?
I'm confused regarding the place of using regularization. In the theory, I saw regularization has been used with the Loss function.
But in the time implementation in Keras, I saw regularization has ...
- 155
0
votes
1
answer
764
views
How is MSE calculated for multi-output regression in keras?
I have a Keras deep learning model that outputs 6 variables.
model = Sequential()
model.add(Dense(32, input_dim=12, kernel_initializer='he_uniform', activation='relu'))
model.add(Dense(256, activation=...
- 39
0
votes
1
answer
730
views
Custom loss function and fit data for multiple inputs and outputs in tf.Keras
I am working around with a DNN in tf.Keras, which looks like as follows:
# Construct the DNN model with 2 inputs, 2 outputs and 3 hidden layers
c0_input = Input(shape=(1,), name="c0")
...
- 13
0
votes
1
answer
558
views
Custom Loss involving multivariate normal in keras
I need to implement a loss function whereby it takes in some true y that is a 4 dimensional vector and computes the probability of this vector under some normal distribution. I tried to build the ...
- 93
-1
votes
1
answer
215
views
why did i got 2 different losses for sparse_categorical_crossentropy and categorical_crossentropy?
I trained a model for multiclass classification. There were three classes. In the first approach, I trained a model by converting the classes into one-hot vectors and training a model with loss ...
-1
votes
1
answer
179
views
Why model's loss is always revolving around 1 in every epoch?
During training, loss of my model is revolving around "1". It is not converging.
I tried various optimizer but it still showing the same pattern. I am using keras with tensorflow backend. What could ...
- 437
-2
votes
2
answers
366
views
how to design a custom loss function to add two loss
I am using CNN to solve a regression problem in a supervised manner. i have input data(X_train) and the target data(y_train).
- 471