Rafal W. kenorb

💭

The Consciousness Has Shifted...The Awakening Has Begun

Asgardian

kenorb / syslog-gdm-errors.log

Created December 18, 2021 13:41

Setting a mode on head 0 failed: Insufficient permissions

	==> auth.log <==
	Dec 18 13:37:48 Ubuntu-ROG polkitd(authority=local): Unregistered Authentication Agent for unix-session:c14 (system bus name :1.628, object path /org/freedesktop/PolicyKit1/AuthenticationAgent, locale en_GB.UTF-8) (disconnected from bus)

	==> gpu-manager-switch.log <==

	==> kern.log <==
	Dec 18 13:37:48 Ubuntu-ROG kernel: [ 7673.827587] [drm:nv_drm_master_set [nvidia_drm]] ERROR [nvidia-drm] [GPU ID 0x0000b400] Failed to grab modeset ownership
	Dec 18 13:37:48 Ubuntu-ROG kernel: [ 7673.827750] [drm:nv_drm_master_set [nvidia_drm]] ERROR [nvidia-drm] [GPU ID 0x00006500] Failed to grab modeset ownership
	Dec 18 13:37:48 Ubuntu-ROG kernel: [ 7673.827848] [drm:nv_drm_master_set [nvidia_drm]] ERROR [nvidia-drm] [GPU ID 0x00001800] Failed to grab modeset ownership
	Dec 18 13:37:48 Ubuntu-ROG kernel: [ 7673.827940] [drm:nv_drm_master_set [nvidia_drm]] ERROR [nvidia-drm] [GPU ID 0x00001700] Failed to grab modeset ownership

kenorb / show_tensor_images.py

Created December 4, 2020 18:07 — forked from mayankgrwl97/show_tensor_images.py

	# Show Tensor Images utility function

	from torchvision.utils import make_grid
	import matplotlib.pyplot as plt

	def show_tensor_images(image_tensor, num_images=25, size=(1, 28, 28)):
	'''
	Function for visualizing images: Given a tensor of images, number of images, and
	size per image, plots and prints the images in a uniform grid.
	'''

kenorb / backward_pass.py

Created December 4, 2020 18:04 — forked from mayankgrwl97/backward_pass.py

	def conv_backward(dH, cache):
	'''
	The backward computation for a convolution function

	Arguments:
	dH -- gradient of the cost with respect to output of the conv layer (H), numpy array of shape (n_H, n_W) assuming channels = 1
	cache -- cache of values needed for the conv_backward(), output of conv_forward()

	Returns:
	dX -- gradient of the cost with respect to input of the conv layer (X), numpy array of shape (n_H_prev, n_W_prev) assuming channels = 1

kenorb / forward_pass.py

Created December 4, 2020 18:04 — forked from mayankgrwl97/forward_pass.py

	def conv_forward(X, W):
	'''
	The forward computation for a convolution function

	Arguments:
	X -- output activations of the previous layer, numpy array of shape (n_H_prev, n_W_prev) assuming input channels = 1
	W -- Weights, numpy array of size (f, f) assuming number of filters = 1

	Returns:
	H -- conv output, numpy array of size (n_H, n_W)

kenorb / forward_pass.py

Created December 4, 2020 18:04 — forked from mayankgrwl97/forward_pass.py

	def conv_forward(X, W):
	'''
	The forward computation for a convolution function

	Arguments:
	X -- output activations of the previous layer, numpy array of shape (n_H_prev, n_W_prev) assuming input channels = 1
	W -- Weights, numpy array of size (f, f) assuming number of filters = 1

	Returns:
	H -- conv output, numpy array of size (n_H, n_W)