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Search results for "dist:AI-MXNet AI"

AI::MXNet - Perl interface to MXNet machine learning library River stage one • 2 direct dependents • 2 total dependents

Perl interface to MXNet machine learning library. MXNet supports the Perl programming language. The MXNet Perl package brings flexible and efficient GPU computing and state-of-art deep learning to Perl. It enables you to write seamless tensor/matrix ...

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::IO - Data loading interface of MXNet River stage one • 2 direct dependents • 2 total dependents

This document summarizes supported data formats and iterator APIs to read the data including mx->io Data iterators for common data formats. mx->recordio Data iterators for the RecordIO data format. mx->image Image Iterators and image augmentation fun...

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::RNN - Functions for constructing recurrent neural networks. River stage one • 2 direct dependents • 2 total dependents

Functions for constructing recurrent neural networks....

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Base - Helper functions River stage one • 2 direct dependents • 2 total dependents

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Gluon - High-level interface for MXNet. River stage one • 2 direct dependents • 2 total dependents

The AI::MXNet::Gluon package is a high-level interface for MXNet designed to be easy to use, while keeping most of the flexibility of a low level API. AI::MXNet::Gluon supports both imperative and symbolic programming, making it easy to train complex...

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Image - Read individual image files and perform augmentations. River stage one • 2 direct dependents • 2 total dependents

Image data iterator with a large number of augumentation choices. Supports reading from both .rec files and raw image files with image list. To load from .rec files, please specify path_imgrec. Also specify path_imgidx to use data partition (for dist...

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Random - Handling of randomization in MXNet. River stage one • 2 direct dependents • 2 total dependents

Handling of randomization in MXNet....

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Symbol - Symbolic interface of MXNet. River stage one • 2 direct dependents • 2 total dependents

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::LinAlg - Linear Algebra routines for NDArray and Symbol. River stage one • 2 direct dependents • 2 total dependents

The Linear Algebra API, provides imperative/symbolic linear algebra tensor operations on CPU/GPU. mx->linalg-><sym|nd>->gemm Performs general matrix multiplication and accumulation. mx->linalg-><sym|nd>->gemm2 Performs general matrix multiplication. ...

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Metric - Evaluation Metric API. River stage one • 2 direct dependents • 2 total dependents

This module hosts all the evaluation metrics available to evaluate the performance of a learned model. Python Docs <https://mxnet.apache.org/api/python/metric/metric.html>...

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Module - FeedForward interface of MXNet. See AI::MXNet::Module::Base for the details. River stage one • 2 direct dependents • 2 total dependents

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Engine - Allows management of properties of the MXNet's engine. River stage one • 2 direct dependents • 2 total dependents

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::KVStore - Key value store interface of MXNet. River stage one • 2 direct dependents • 2 total dependents

Key value store interface of MXNet for parameter synchronization, over multiple devices....

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Monitor - Monitor outputs, weights, and gradients for debugging. River stage one • 2 direct dependents • 2 total dependents

Monitor outputs, weights, and gradients for debugging. Parameters ---------- interval : Int Number of batches between printing. stat_func : CodeRef a function that computes statistics of tensors. Takes a NDArray and returns a NDArray. defaults to mea...

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::NDArray - Multidimensional tensor object of MXNet. River stage one • 2 direct dependents • 2 total dependents

AI::MXNet::NDArray - Imperative tensor operations on CPU/GPU In AI::MXNet, NDArray is the core data structure for all mathematical computations. An NDArray represents a multidimensional, fixed-size homogenous array. If you're familiar with the PDL, y...

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Contrib - An interface to experimental operators defined in C++ space. River stage one • 2 direct dependents • 2 total dependents

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::RNN::IO - Functions for constructing recurrent neural networks. River stage one • 2 direct dependents • 2 total dependents

Functions for constructing recurrent neural networks....

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::Context - A device context. River stage one • 2 direct dependents • 2 total dependents

This class governs the device context of AI::MXNet::NDArray objects....

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::RunTime - Runtime querying of compile time features in the native library. River stage one • 2 direct dependents • 2 total dependents

With this module you can check at runtime which libraries and features were compiled in the library. Example usage: use AI::MXNet qw(mx); my $features = mx->runtime->Features(); print $features->is_enabled("CUDNN"); 0 print $features->is_enabled("CPU...

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC

AI::MXNet::AutoGrad - Autograd for NDArray. River stage one • 2 direct dependents • 2 total dependents

Auto gradients differentiation for dynamic graphs, primarily used with Gluon....

SKOLYCHEV/AI-MXNet-1.6 - 23 Jun 2023 16:35:58 UTC
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