Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Updated
Jun 12, 2024 - Python
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Read and write Neuroglancer datasets programmatically.
Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
On-device AI across mobile, embedded and edge for PyTorch
Neural Network Creation Library
A deep learning framework in mojo🔥
Julia package for tensor contractions and related operations
💪 Muscles power Tensors 💪
⟨Grassmann-Clifford-Hodge⟩ multilinear differential geometric algebra
An animal can do training and inference every day of its existence until the day of its death. A forward pass is all you need.
Composable Tensor Network library in Julia
Biblioteca para manipulação de modelos de Redes Neurais
Provides compile-time contraction pattern analysis to determine optimal tensor operation to perform.
Tensor Network State Packages
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
Differentiable Tensors based on NumPy Arrays
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