tsai 0.1.2

Time series deep learning in Rust - a feature-parity port of Python tsai
Documentation 
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[[bench]]
harness = false
name = "training_bench"
path = "benches/training_bench.rs"

[dependencies.burn]
version = "0.16"

[dependencies.burn-mlx]
optional = true
version = "0.1.2"

[dependencies.burn-wgpu]
optional = true
version = "0.16"

[dependencies.tsai_analysis]
version = "0.1.2"

[dependencies.tsai_core]
version = "0.1.2"

[dependencies.tsai_data]
version = "0.1.2"

[dependencies.tsai_explain]
version = "0.1.2"

[dependencies.tsai_models]
version = "0.1.2"

[dependencies.tsai_train]
version = "0.1.2"

[dependencies.tsai_transforms]
version = "0.1.2"

[dev-dependencies.anyhow]
version = "1.0"

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

[dev-dependencies.burn-autodiff]
version = "0.16"

[dev-dependencies.burn-ndarray]
version = "0.16"

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

[dev-dependencies.ndarray]
features = ["serde"]
version = "0.16"

[dev-dependencies.rand]
version = "0.8"

[dev-dependencies.rand_chacha]
version = "0.3"

[features]
backend-mlx = ["burn-mlx"]
backend-ndarray = ["tsai_core/backend-ndarray", "tsai_data/backend-ndarray", "tsai_transforms/backend-ndarray", "tsai_models/backend-ndarray", "tsai_train/backend-ndarray", "tsai_analysis/backend-ndarray", "tsai_explain/backend-ndarray"]
backend-tch = ["tsai_core/backend-tch", "tsai_data/backend-tch", "tsai_transforms/backend-tch", "tsai_models/backend-tch", "tsai_train/backend-tch", "tsai_analysis/backend-tch", "tsai_explain/backend-tch"]
backend-wgpu = ["tsai_core/backend-wgpu", "tsai_data/backend-wgpu", "tsai_transforms/backend-wgpu", "tsai_models/backend-wgpu", "tsai_train/backend-wgpu", "tsai_analysis/backend-wgpu", "tsai_explain/backend-wgpu", "burn-wgpu"]
default = ["backend-ndarray"]
wandb = ["tsai_train/wandb"]

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

[package]
authors = ["tsai-rs contributors"]
autobenches = false
autobins = false
autoexamples = false
autolib = false
autotests = false
build = false
categories = ["science"]
description = "Time series deep learning in Rust - a feature-parity port of Python tsai"
documentation = "https://docs.rs/tsai"
edition = "2021"
homepage = "https://github.com/TuringWorks/tsai-rs"
keywords = ["time-series", "deep-learning", "machine-learning", "neural-network"]
license = "Apache-2.0"
name = "tsai"
readme = "README.md"
repository = "https://github.com/TuringWorks/tsai-rs"
version = "0.1.2"

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