tensor_frame 0.0.3-alpha

A PyTorch-like tensor library for Rust with CPU, WGPU, and CUDA backends
Documentation 
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[dependencies.bytemuck]
optional = true
version = "1.19.0"

[dependencies.cudarc]
features = ["cuda-version-from-build-system"]
optional = true
version = "0.16"

[dependencies.futures]
optional = true
version = "0.3.31"

[dependencies.once_cell]
version = "1.21"

[dependencies.rayon]
optional = true
version = "1.10"

[dependencies.tokio]
features = ["rt", "rt-multi-thread"]
optional = true
version = "1.45"

[dependencies.wgpu]
optional = true
version = "25.0"

[dev-dependencies.criterion]
version = "0.5"

[[example]]
name = "backend_selection"
path = "examples/backend_selection.rs"

[[example]]
name = "basic_operations"
path = "examples/basic_operations.rs"

[[example]]
name = "broadcasting"
path = "examples/broadcasting.rs"

[[example]]
name = "new_operations"
path = "examples/new_operations.rs"

[features]
cpu = ["rayon"]
cuda = ["dep:cudarc"]
debug = []
default = ["cpu"]
wgpu = ["dep:wgpu", "dep:bytemuck", "dep:futures", "dep:tokio"]

[lib]
name = "tensor_frame"
path = "src/lib.rs"

[package]
authors = ["FizzWizzleDazzle"]
autobenches = false
autobins = false
autoexamples = false
autolib = false
autotests = false
build = false
categories = ["science", "mathematics"]
description = "A PyTorch-like tensor library for Rust with CPU, WGPU, and CUDA backends"
edition = "2024"
keywords = ["tensor", "machine-learning", "gpu", "cuda", "wgpu"]
license = "MIT OR Apache-2.0"
name = "tensor_frame"
readme = "README.md"
repository = "https://github.com/TrainPioneers/Tensor-Frame"
version = "0.0.3-alpha"

[[test]]
name = "backend_selection"
path = "tests/backend_selection.rs"

[[test]]
name = "new_operations"
path = "tests/new_operations.rs"