Deep Learning

early stopping tensorflow pytorch

How to implement early stopping in Tensorflow, Keras and Pytorch.

When experimenting with various parameters in a model like changing the number of layers, activation function, or neurons, sometimes the model doesn’t perform well while training. We can save training time and other resources by stopping the model when its performance on the validation dataset deteriorates. The process is called early stopping in machine learning. […]

How to implement early stopping in Tensorflow, Keras and Pytorch. Read More »

error cuda kernal image

Fixed runtimeerror: cuda error: no kernel image is available for execution on the device

Summary The blog has been written by a machine learning practitioner. He has practical experience in solving CUDA and GPU issues of compatibility in production environments using PyTorch and TensorFlow. The solution shared here is based on troubleshooting of NVIDIA GPUs across multiple CUDA versions, driver configurations, and compute architectures The reason for getting RuntimeError:

Fixed runtimeerror: cuda error: no kernel image is available for execution on the device Read More »

CUDA Error

Fixing the RuntimeError: cuda error: cublas_status_not_initialized in PyTorch

When we are working with GPU accelerated frameworks like PyTorch we tend to face errors related to CUDA which can be a frustrating experience. One such error is RuntimeError: cuda error: cublas_status_not_initialized when calling cublascreate(handle). Knowing the exact cause of error is quite difficult but we can narrow it down to places where we can

Fixing the RuntimeError: cuda error: cublas_status_not_initialized in PyTorch Read More »