Tensorflow ctc loss nan
Web9 Apr 2024 · Thanks for your reply. I re-ran my codes and found the 'nan' loss occurred on epoch 345. Please change the line model.fit(x1, y1, batch_size = 896, epochs = 200, shuffle = True) to model.fit(x1, y1, batch_size = 896, epochs = 400, shuffle = True) and the 'nan' loss should occur when the loss is reduced to around 0.0178.
Tensorflow ctc loss nan
Did you know?
Web28 Jan 2024 · Loss function not implemented properly Numerical instability in the Deep learning framework You can check whether it always becomes nan when fed with a particular input or is it completely random. Usual practice is to reduce the learning rate in step manner after every few iterations. Share Cite Improve this answer Follow Web3 Jul 2024 · Tour Start here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site
Web19 Sep 2016 · I want to bulid a CNN+LSTM+CTC model by tensorflow ,but I always get NAN value during training ,how to avoid that?Dose INPUT need to be handle specially？ on the … Web5 Oct 2024 · Getting NaN for loss. i have used the tensorflow book example, but concatenated version of NN fron two different input is output NaN. There is second …
Web12 Feb 2024 · TensorFlow backend (yes / no): yes TensorFlow version: 2.1.0 Keras version: 2.3.1 Python version: 3.7.3 CUDA/cuDNN version: N/A GPU model and memory: N/A … WebLoss function returns nan on time series dataset using tensorflow Ask Question Asked 4 years, 5 months ago Modified 4 years, 5 months ago Viewed 3k times 0 This was the follow up question of Prediction on timeseries data using tensorflow. I have an input and output of below format. (X) = [ [ 0 1 2] [ 1 2 3]] y = [ 3 4 ] Its a timeseries data.
Web25 Aug 2024 · I am getting (loss: nan - accuracy: 0.0000e+00) for all epochs after training the model Ask Question Asked 1 year, 7 months ago Modified 11 months ago Viewed 4k times 0 I made a simple model to train my data set which consists of (210 samples and each sample consists of a numpy array of 22 values) and x_trian and y_trian look like:
Web24 Oct 2024 · To try make things a bit easier I’ve made a script that uses the builtin ctc loss function and replicates the warp-ctc tests. Seem to give the same results when you run pytest -s test_gpu.py and pytest -s test_pytorch.py but does not test the above issue where we have two difference sequence lengths in the batch. is a town like alice based on a true storyWebI will say though that nan losses are very often due to exploding gradients. A common mistake is to for example not having scaled everything properly. But generally, start with … isa town post codeWeb24 Oct 2024 · But just before it NaN-ed out, the model reached a 75% accuracy. That’s awfully promising. But this NaN thing is getting to be super annoying. The funny thing is that just before it “diverges” with loss = NaN, the model hasn’t been diverging at all, the loss has been going down: once lightly brain teaserWeb18 Oct 2024 · Note that the gradient of this will be NaN for the inputs in question, maybe it would be good to optionally clip that to zero (which you could do with a backward hook on the inputs now). Best regards. ... directly on the CTC loss, i.e. the gradient_out of loss is 1, which is the same as not reducing and using loss.backward(torch.ones_like(loss)). onceler youngWebtry to use a different loss than categorical crossentropy, e.g. MSE Xception classifier from Keras/Applications Adding l2 weights regularizer to convolutional layers (as described in … once-ler x tedWeb22 Nov 2024 · A loss function is a function that maps a set of predicted values to a real-valued loss. In machine learning, loss functions are used to measure how well a model is … isa town marketWeb22 Jul 2024 · TensorFlow version (use command below): 2.2.0 (v2.2.0-0-g2b96f3662b) Python version: 3.6.9; GPU model and memory: Google Colab TPU; I've found that … is a town rural or urban