00:02.0 VGA compatible controller: Intel Corporation Device 9bc4 (rev 05)01:00.0 VGA compatible controller: NVIDIA Corporation Device 1f15 (rev a1)

sudo apt-get --purge remove nvidia*sudo apt autoremove

#define CUDNN_MAJOR 7#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)

import tensorflow as tftf.test.is_gpu_available()

import tensorflow as tfimport numpy as np
x_data = np.random.rand(100).astype(np.float32)y_data = x_data * 0.1 + 0.3
Weights = tf.Variable(tf.random_uniform([1], -1.0, 1.0))biases = tf.Variable(tf.zeros([1]))
y = Weights * x_data + biases
loss = tf.reduce_mean(tf.square(y - y_data))
optimizer = tf.train.GradientDescentOptimizer(0.5) train = optimizer.minimize(loss)
init = tf.global_variables_initializer()
with tf.Session() as sess:    sess.run(init)    for step in range(201):        sess.run(train)        if step % 20 == 0:            print(step, sess.run(Weights), sess.run(biases))

2022-04-02 14:20:48.529672: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.72022-04-02 14:20:48.841323: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR2022-04-02 14:20:48.845187: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR.........tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.  (0) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.   [[{{node conv2d_1/convolution}}]]   [[metrics/ppv/Mean/_625]]  (1) Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.   [[{{node conv2d_1/convolution}}]]0 successful operations.0 derived errors ignored.

import tensorflow as tf[tf.config.experimental.set_memory_growth(gpu, True) for gpu in tf.config.experimental.list_physical_devices('GPU')]tf.config.experimental.list_logical_devices('GPU')