2 repository-uri
Awesome GitHub RepositoriesFramework Abstraction Layers
Interfaces that allow graph logic to be executed across different deep learning backends.
Distinct from Tensor Computation Backends: Distinct from Tensor Computation Backends by focusing on the abstraction layer that enables cross-framework compatibility rather than the execution engine itself.
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Framework Abstraction Layers. Refine with filters or upvote what's useful.
Awesome Framework Abstraction Layers GitHub Repositories
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- dmlc/dgl
dmlc/dgl
14,283Vezi pe GitHubDGL is a Python library for building and training graph neural networks. It functions as a graph message passing framework and a geometric deep learning tool, enabling the development of models that analyze graph-structured data. The library is designed for large-scale graph processing, utilizing distributed training and neighbor sampling to handle datasets with billions of edges. It provides specialized support for heterogeneous graph modeling, allowing for the representation of complex real-world entities with multiple node and edge types. Its capabilities cover a wide range of graph tasks
Provides a backend-agnostic tensor interface to ensure graph logic runs across different deep learning frameworks.
Pythondeep-learninggraph-neural-networks - tensorlayer/tensorlayer
tensorlayer/TensorLayer
7,384Vezi pe GitHubTensorLayer is a backend-agnostic tensor library and deep learning framework designed for building neural network architectures. It provides a neural network abstraction layer that allows model logic to run across different deep learning engines using high-level layers and model components. The project serves as a deep reinforcement learning toolkit for implementing policy-based, value-based, and actor-critic agents. It includes specialized tools for managing experience replay and gradient-based policy optimization to handle both discrete and continuous action spaces. To support reinforcemen
Implements a framework abstraction layer that allows the same model logic to run across different deep learning backends.
Python
