Sponsored Content
Full Discussion: Programming using sklearn
Top Forums Shell Programming and Scripting Programming using sklearn Post 303021186 by chercheur111 on Monday 6th of August 2018 03:55:42 AM
Old 08-06-2018
Yes, using sklearn library (like tensorflow).
 

10 More Discussions You Might Find Interesting

1. Programming

c programming on vi

i am new in linux environment .I have used vi editor of Unix to get a programe compiled through "gcc ".kindly give me the options to get a program compiled & executed written in c on vi editor. I want the command to compile a file and the command to get that compiled file executed with any... (2 Replies)
Discussion started by: Rajraius
2 Replies

2. Programming

c programming or unix programming!?

i would like advice on the usbject of c programming (in the middle of reading a book on C). could i benefit more if i apply that knowledge in the unix format if i were able to, or would that take the point out of learning C, basically I want to stay away from strying too far away from unix and use... (1 Reply)
Discussion started by: moxxx68
1 Replies

3. Shell Programming and Scripting

Unix Systems Programming Vs Unix Programming

Several months ago I found a link that explained the difference between how a Unix Systems Admin would do scripting compared to what a Unix Programmer would do. It showed a basic script and then show several iterations that explained how the Systems Admin would change it to make it better. I was... (0 Replies)
Discussion started by: BCarlson
0 Replies

4. Programming

C++ programming

Sorry to ask this question here... where can I find a C++ programming thread? Thanks guys! (7 Replies)
Discussion started by: nadiamihu
7 Replies

5. Shell Programming and Scripting

New To Programming

Hello all!! I am new to programming, and to this forum. :D I am having sort of a problem. Me and my coworker are working on a code, both of us are stumped on a few things. One is we have a whole log file, i have found how to extract by column, but not by row. I need to extract by both.:confused:... (7 Replies)
Discussion started by: xkayla06
7 Replies

6. UNIX for Dummies Questions & Answers

Carreer:Networking Programming in Unix (C programming Language)

Hello, I am trying to learn Networking Programming in C in unix enviorment. I want to know how good it is to become a network programmer. i am crazy about Network programming but i also want to opt for the best carreer options. Anybody experienced Network Programmer, please tell me is my... (5 Replies)
Discussion started by: vibhory2j
5 Replies

7. Programming

C Programming - Hardware Programming

Can someone help me on suggesting some ways to access the memory content in RAM directly from C/C++ source code. Please provide me any book name or any URL so that I can get an exhaustive knowledge over it. If possible please give me some tips on interacting with hardwares directly through... (3 Replies)
Discussion started by: nandumishra
3 Replies

8. Shell Programming and Scripting

Sh programming

I have started writing one script. It is not taking the if block. Here is the script: #!/bin/sh set USER='/usr/ucb/whoami' ####################################################################### #Killing Process #######################################################################... (6 Replies)
Discussion started by: amarpreetka
6 Replies

9. UNIX for Dummies Questions & Answers

How does unix system administration, unix programming, unix network programming differ?

How does unix system administration, unix programming, unix network programming differ? Please help. (0 Replies)
Discussion started by: thulasidharan2k
0 Replies

10. UNIX for Dummies Questions & Answers

From iOS programming to Linux system programming

Hello. I like Linux and C programming language. Allways wanted to understand kernel and become a Linux system programmer. And I also like Objective-C and iOS. These two programming areas have relations: 1. Linux and iOS are UNIX-like systems, POSIX compliant. 2. It is useful to know C language... (2 Replies)
Discussion started by: Rockatansky
2 Replies
MPSNNNeuronDescriptor(3)				 MetalPerformanceShaders.framework				  MPSNNNeuronDescriptor(3)

NAME
MPSNNNeuronDescriptor SYNOPSIS
#import <MPSCNNNeuron.h> Inherits NSObject, and <NSCopying>. Instance Methods (nonnull instancetype) - init Class Methods (nonnull MPSNNNeuronDescriptor *) + cnnNeuronDescriptorWithType: (nonnull MPSNNNeuronDescriptor *) + cnnNeuronDescriptorWithType:a: (nonnull MPSNNNeuronDescriptor *) + cnnNeuronDescriptorWithType:a:b: (nonnull MPSNNNeuronDescriptor *) + cnnNeuronDescriptorWithType:a:b:c: (nonnull MPSNNNeuronDescriptor *) + cnnNeuronPReLUDescriptorWithData:noCopy: Properties MPSCNNNeuronType neuronType float a float b float c NSData * data Detailed Description This depends on Metal.framework The MPSNNNeuronDescriptor specifies a neuron descriptor. Supported neuron types: Neuron type 'none': f(x) = x Parameters: none ReLU neuron filter: f(x) = x >= 0 ? x : a * x This is called Leaky ReLU in literature. Some literature defines classical ReLU as max(0, x). If you want this behavior, simply pass a = 0. Parameters: a For default behavior, set the value of a to 0.0f. Linear neuron filter: f(x) = a * x + b Parameters: a, b For default behavior, set the value of a to 1.0f and the value of b to 0.0f. Sigmoid neuron filter: f(x) = 1 / (1 + e^-x) Parameters: none Hard Sigmoid filter: f(x) = clamp((x * a) + b, 0, 1) Parameters: a, b For default behavior, set the value of a to 0.2f and the value of b to 0.5f. Hyperbolic tangent (TanH) neuron filter: f(x) = a * tanh(b * x) Parameters: a, b For default behavior, set the value of a to 1.0f and the value of b to 1.0f. Absolute neuron filter: f(x) = fabs(x) Parameters: none Parametric Soft Plus neuron filter: f(x) = a * log(1 + e^(b * x)) Parameters: a, b For default behavior, set the value of a to 1.0f and the value of b to 1.0f. Parametric Soft Sign neuron filter: f(x) = x / (1 + abs(x)) Parameters: none Parametric ELU neuron filter: f(x) = x >= 0 ? x : a * (exp(x) - 1) Parameters: a For default behavior, set the value of a to 1.0f. Parametric ReLU (PReLU) neuron filter: Same as ReLU, except parameter aArray is per channel. For each pixel, applies the following function: f(x_i) = x_i, if x_i >= 0 = a_i * x_i if x_i < 0 i in [0...channels-1] i.e. parameters a_i are learned and applied to each channel separately. Compare this to ReLu where parameter a is shared across all channels. See https://arxiv.org/pdf/1502.01852.pdf for details. Parameters: aArray - Array of floats containing per channel value of PReLu parameter count - Number of float values in array aArray. ReLUN neuron filter: f(x) = min((x >= 0 ? x : a * x), b) Parameters: a, b As an example, the TensorFlow Relu6 activation layer can be implemented by setting the parameter b to 6.0f: https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/relu6. For default behavior, set the value of a to 1.0f and the value of b to 6.0f. Method Documentation + (nonnull MPSNNNeuronDescriptor*) cnnNeuronDescriptorWithType: (MPSCNNNeuronType) neuronType Make a descriptor for a MPSCNNNeuron object. Parameters: neuronType The type of a neuron filter. Returns: A valid MPSNNNeuronDescriptor object or nil, if failure. + (nonnull MPSNNNeuronDescriptor*) cnnNeuronDescriptorWithType: (MPSCNNNeuronType) neuronType(float) a Make a descriptor for a MPSCNNNeuron object. Parameters: neuronType The type of a neuron filter. a Parameter 'a'. Returns: A valid MPSNNNeuronDescriptor object or nil, if failure. + (nonnull MPSNNNeuronDescriptor*) cnnNeuronDescriptorWithType: (MPSCNNNeuronType) neuronType(float) a(float) b Initialize the neuron descriptor. Parameters: neuronType The type of a neuron filter. a Parameter 'a'. b Parameter 'b'. Returns: A valid MPSNNNeuronDescriptor object or nil, if failure. + (nonnull MPSNNNeuronDescriptor*) cnnNeuronDescriptorWithType: (MPSCNNNeuronType) neuronType(float) a(float) b(float) c Make a descriptor for a MPSCNNNeuron object. Parameters: neuronType The type of a neuron filter. a Parameter 'a'. b Parameter 'b'. c Parameter 'c'. Returns: A valid MPSNNNeuronDescriptor object or nil, if failure. + (nonnull MPSNNNeuronDescriptor*) cnnNeuronPReLUDescriptorWithData: (NSData *_Nonnull) data(bool) noCopy Make a descriptor for a neuron of type MPSCNNNeuronTypePReLU. The PReLU neuron is the same as a ReLU neuron, except parameter 'a' is per feature channel. Parameters: data A NSData containing a float array with the per feature channel value of PReLu parameter. The number of float values in this array usually corresponds to number of output channels in a convolution layer. The descriptor retains the NSData object. noCopy An optimization flag that tells us whether the NSData allocation is suitable for use directly with no copying of the data into internal storage. This allocation has to match the same restrictions as listed for the newBufferWithBytesNoCopy:length:options:deallocator: method of MTLBuffer. Returns: A valid MPSNNNeuronDescriptor object for a neuron of type MPSCNNNeuronTypePReLU or nil, if failure - (nonnull instancetype) init You must use one of the interfaces below instead. Property Documentation - (float) a [read], [write], [nonatomic], [assign] - (float) b [read], [write], [nonatomic], [assign] - (float) c [read], [write], [nonatomic], [assign] - (NSData*) data [read], [write], [nonatomic], [retain] - (MPSCNNNeuronType) neuronType [read], [write], [nonatomic], [assign] Author Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code. Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSNNNeuronDescriptor(3)
All times are GMT -4. The time now is 05:28 AM.
Unix & Linux Forums Content Copyright 1993-2022. All Rights Reserved.
Privacy Policy