Remote code execution vulnerabilities exist in the way that GDI+ handles: 1) gradient sizes; 2) memory allocation; 3) parses GIF images; 4) allocates memory for WMF image files; and 5) integer calculations The risk is MEDIUM. An attacker who successfully exploited this vulnerability could take complete control of an affected system.
Hi there,
The following openssl package are installed on the machine (openssl-1.0.0-27.el6_4.2.x86_64). It isn't the last version but I need to known if this content Vulnerabilities...
How to check that on RedHat?
Could you please tell me how to find this information??
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Hi Guru
I need to know which version of NTP is install in Solaris 10 box. How can I check it.
IF NTP 3 in implemented then somebody told me implement NTP 4 due to security reasons, for that I have to tell what are the vulnerabilities present in NTP 3 to higher authorities. I could not able... (5 Replies)
MPSCNNSubtractGradient(3) MetalPerformanceShaders.framework MPSCNNSubtractGradient(3)NAME
MPSCNNSubtractGradient
SYNOPSIS
#import <MPSCNNMath.h>
Inherits MPSCNNArithmeticGradient.
Instance Methods
(nonnull instancetype) - initWithDevice:
Additional Inherited Members
Detailed Description
This depends on Metal.framework. Specifies the subtraction gradient operator. This arithmetic gradient filter requires the following
inputs: gradient image from the previous layer (going backwards) and either the primary or the secondary source image from the forward
pass. You will need a separate filter for the primary and secondary source images.
Without broadcasting, the arithmetic subtract gradient operation for the primary source image is a copy operation on the input gradient
image (for x - y, d/dx(x - y) = 1). This copy operation can be optimized away by the graph interface.
For the secondary source image, the result is a negation of the gradient image from the previous layer (for x - y, d/dy(x - y) = -1).
Setting the broadcasting parameters results in a reduction operation (sum) across all of the applicable broadcasting dimensions (rows,
columns, feature channels, or any combination thereof) to produce the destination image of the size that matches the primary/secondary
input images used in the forward pass.
Method Documentation
- (nonnull instancetype) initWithDevice: (nonnull id< MTLDevice >) device
Initialize the subtraction gradient operator.
Parameters:
device The device the filter will run on.
Returns:
A valid MPSCNNSubtractGradient object or nil, if failure.
Reimplemented from MPSCNNArithmeticGradient.
Author
Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code.
Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSCNNSubtractGradient(3)