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Special Forums UNIX and Linux Applications TensorFlow: Open Source Software Library for Machine Intelligence Post 302974824 by Neo on Saturday 4th of June 2016 04:07:54 AM
Old 06-04-2016
TensorFlow: Open Source Software Library for Machine Intelligence

Hi.

Is anyone using TensorFlow ?

Quote:
TensorFlow™ is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well. - Google

Please let us know if you are using or planning to use TensorFlow.

Thanks.
 

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MPSNNDefaultPadding(3)					 MetalPerformanceShaders.framework				    MPSNNDefaultPadding(3)

NAME
MPSNNDefaultPadding SYNOPSIS
#import <MPSNeuralNetworkTypes.h> Inherits NSObject, and <MPSNNPadding>. Instance Methods (NSString *__nonnull) - label Class Methods (instancetype __nonnull) + paddingWithMethod: (instancetype __nonnull) + paddingForTensorflowAveragePooling (instancetype __nonnull) + paddingForTensorflowAveragePoolingValidOnly Method Documentation - (NSString * __nonnull) label Human readable description of what the padding policy does + (instancetype __nonnull) paddingForTensorflowAveragePooling A padding policy that attempts to reproduce TensorFlow behavior for average pooling Most TensorFlow padding is covered by the standard MPSNNPaddingMethod encodings. You can use +paddingWithMethod to get quick access to MPSNNPadding objects, when default filter behavior isn't enough. (It often is.) However, the edging for max pooling in TensorFlow is a bit unusual. This padding method attempts to reproduce TensorFlow padding for average pooling. In addition to setting MPSNNPaddingMethodSizeSame | MPSNNPaddingMethodAlignCentered | MPSNNPaddingMethodAddRemainderToBottomRight, it also configures the filter to run with MPSImageEdgeModeClamp, which (as a special case for average pooling only), normalizes the sum of contributing samples to the area of valid contributing pixels only. // Sample implementation for the tensorflowPoolingPaddingPolicy returned -(MPSNNPaddingMethod) paddingMethod{ return MPSNNPaddingMethodCustom | MPSNNPaddingMethodSizeSame; } -(MPSImageDescriptor * __nonnull) destinationImageDescriptorForSourceImages: (NSArray <MPSImage *> *__nonnull) sourceImages sourceStates: (NSArray <MPSState *> * __nullable) sourceStates forKernel: (MPSKernel * __nonnull) kernel suggestedDescriptor: (MPSImageDescriptor * __nonnull) inDescriptor { ((MPSCNNKernel *)kernel).edgeMode = MPSImageEdgeModeClamp; return inDescriptor; } + (instancetype __nonnull) paddingForTensorflowAveragePoolingValidOnly Typical pooling padding policy for valid only mode + (instancetype __nonnull) paddingWithMethod: (MPSNNPaddingMethod) method Fetch a well known object that implements a non-custom padding method For custom padding methods, you will need to implement an object that conforms to the full MPSNNPadding protocol, including NSSecureCoding. Parameters: method A MPSNNPaddingMethod Returns: An object that implements <MPSNNPadding> for use with MPSNNGraphNodes. Author Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code. Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSNNDefaultPadding(3)
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