First, sorry for me English. I'm new here. I need help.
I'm from Poland and I write MA thesis about Linux courses in Europe and USA. Please write name company (and www. if You know) in ours country how offer training from Linux, no matter authorized or not (e.g. RH or Debian) . I want to make combination how many trainings are in another country, what they learning and how (good or bad), in which level (e.g. for beginner).
Hello Team,
I am on last semestr on my studies. I have a problem with choosing right thesis topic. Do You have maybe any ideas for thesis related to Linux area? I really need your help - the most important thing is that there should be research element in the topic because of master degree... (3 Replies)
Hi Friends !
I'm sorry if this not right place to ask questions like this.
I'm working as a Linux system administrator in one of the Indian hosting company that provides tech support to various UK and US based clients. I have now total 3+ years of web hosting technology experience and good... (2 Replies)
Dear all,
I am preparing the RHCE Linux certification and I need to practise, practise and practise linux administration ...I wold be very pleasen if somebody lists here online training resources that can be used in order to prepare any kind of Linux Certification..
Actualy I am following the... (1 Reply)
I have been working linux administration for 2.5 years. I would like to have a certification in this. Yes RHCE is an option. I think already know most of the RHCE stuff.
But I would like to have some thing advanced. I ready to for a full time course as I not getting the exposure in my current... (2 Replies)
Hey All
i want to be able to run command line commands in a java program, ive heard about java runtime, am i on the right track?
Cheers for the help (4 Replies)
MPSCNNBatchNormalizationNode(3) MetalPerformanceShaders.framework MPSCNNBatchNormalizationNode(3)NAME
MPSCNNBatchNormalizationNode
SYNOPSIS
#import <MPSNNGraphNodes.h>
Inherits MPSNNFilterNode.
Instance Methods
(nonnull instancetype) - initWithSource:dataSource:
Class Methods
(nonnull instancetype) + nodeWithSource:dataSource:
Properties
MPSCNNBatchNormalizationFlags flags
Detailed Description
A node representing batch normalization for inference or training Batch normalization operates differently for inference and training. For
inference, the normalization is done according to a static statistical representation of data saved during training. For training, this
representation is ever evolving. In the low level MPS batch normalization interface, during training, the batch normalization is broken up
into two steps: calculation of the statistical representation of input data, followed by normalization once the statistics are known for
the entire batch. These are MPSCNNBatchNormalizationStatistics and MPSCNNBatchNormalization, respectively.
When this node appears in a graph and is not required to produce a MPSCNNBatchNormalizationState -- that is,
MPSCNNBatchNormalizationNode.resultState is not used within the graph -- then it operates in inference mode and new batch-only statistics
are not calculated. When this state node is consumed, then the node is assumed to be in training mode and new statistics will be calculated
and written to the MPSCNNBatchNormalizationState and passed along to the MPSCNNBatchNormalizationGradient and
MPSCNNBatchNormalizationStatisticsGradient as necessary. This should allow you to construct an identical sequence of nodes for inference
and training and expect the to right thing happen.
Method Documentation
- (nonnull instancetype) initWithSource: (MPSNNImageNode *__nonnull) source(nonnull id< MPSCNNBatchNormalizationDataSource >) dataSource
+ (nonnull instancetype) nodeWithSource: (MPSNNImageNode *__nonnull) source(nonnull id< MPSCNNBatchNormalizationDataSource >) dataSource
Property Documentation
- (MPSCNNBatchNormalizationFlags) flags [read], [write], [nonatomic], [assign]
Options controlling how batch normalization is calculated Default: MPSCNNBatchNormalizationFlagsDefault
Author
Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code.
Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSCNNBatchNormalizationNode(3)