TensorFlow: Blas GEMM launch failed

Question

This worked for me on TensorFlow 2.1.0 (per: https://www.tensorflow.org/api_docs/python/tf/config/experimental/set_memory_growth)

import tensorflow as tf
physical_devices = tf.config.list_physical_devices('GPU') 
for device in physical_devices:
    tf.config.experimental.set_memory_growth(device, True)

It's a simple fix, but it was a nightmare to figure it all out

On Windows I found the Keras install in Anaconda3\Lib\site-packages\keras

sources:

https://www.tensorflow.org/guide/using_gpu

https://github.com/keras-team/keras/blob/master/keras/backend/tensorflow_backend.py

Find the following in your keras/tensorflow_backend.py file you'll add config.gpu_options.allow_growth= True in both places

if _SESSION is None:
            if not os.environ.get('OMP_NUM_THREADS'):
                config = tf.ConfigProto(allow_soft_placement=True)
                config.gpu_options.allow_growth=True
            else:
                num_thread = int(os.environ.get('OMP_NUM_THREADS'))
                config = tf.ConfigProto(intra_op_parallelism_threads=num_thread,
                                        allow_soft_placement=True)
                config.gpu_options.allow_growth=True
            _SESSION = tf.Session(config=config)
        session = _SESSION

Make sure you have no other processes using the GPU running. Run nvidia-smi to check this.

SOURCE: An issue brought up by @reedwm.

Adding the following lines after imports solved the problem:

configuration = tf.compat.v1.ConfigProto()
configuration.gpu_options.allow_growth = True
session = tf.compat.v1.Session(config=configuration)

This Answer is much related to Tensorflow:

Sometimes Tensorflow fails at creation in Windows.

Restarting the notebook using gpu solves it in most cases

If it doesnt then try restarting the notebook after adding these options in your code.

gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.9)

tf.Session(config=tf.ConfigProto(gpu_options=gpu_options,allow_soft_placement=True)

I never had such error while using Keras But try restarting your notebook