train-station 0.3.0

A high-performance, PyTorch inspired, zero dependency Rust machine learning library
Documentation 
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[build-dependencies]

[dependencies]

[[example]]
name = "adam_configurations"
path = "examples/optimizers/adam_configurations.rs"

[[example]]
name = "advanced_patterns"
path = "examples/iterators/advanced_patterns.rs"

[[example]]
name = "basic_decoder"
path = "examples/neural_networks/basic_decoder.rs"

[[example]]
name = "basic_encoder"
path = "examples/neural_networks/basic_encoder.rs"

[[example]]
name = "basic_linear_layer"
path = "examples/neural_networks/basic_linear_layer.rs"

[[example]]
name = "basic_structs"
path = "examples/serialization/basic_structs.rs"

[[example]]
name = "basic_transformer"
path = "examples/neural_networks/basic_transformer.rs"

[[example]]
name = "dqn"
path = "examples/RL_training/dqn.rs"

[[example]]
name = "element_iteration"
path = "examples/iterators/element_iteration.rs"

[[example]]
name = "error_handling"
path = "examples/serialization/error_handling.rs"

[[example]]
name = "feedforward_network"
path = "examples/neural_networks/feedforward_network.rs"

[[example]]
name = "json_vs_binary"
path = "examples/serialization/json_vs_binary.rs"

[[example]]
name = "learning_rate_scheduling"
path = "examples/optimizers/learning_rate_scheduling.rs"

[[example]]
name = "multi_head_attention"
path = "examples/neural_networks/multi_head_attention.rs"

[[example]]
name = "nested_structures"
path = "examples/serialization/nested_structures.rs"

[[example]]
name = "optimizer_basics"
path = "examples/getting_started/optimizer_basics.rs"

[[example]]
name = "performance_optimization"
path = "examples/iterators/performance_optimization.rs"

[[example]]
name = "ppo_continuous"
path = "examples/RL_training/ppo_continuous.rs"

[[example]]
name = "ppo_discrete"
path = "examples/RL_training/ppo_discrete.rs"

[[example]]
name = "serialization_basics"
path = "examples/getting_started/serialization_basics.rs"

[[example]]
name = "supervised_bce"
path = "examples/supervised_training/supervised_bce.rs"

[[example]]
name = "supervised_classification"
path = "examples/supervised_training/supervised_classification.rs"

[[example]]
name = "supervised_regression"
path = "examples/supervised_training/supervised_regression.rs"

[[example]]
name = "td3"
path = "examples/RL_training/td3.rs"

[[example]]
name = "tensor_basics"
path = "examples/getting_started/tensor_basics.rs"

[[example]]
name = "tensor_operators"
path = "examples/getting_started/tensor_operators.rs"

[features]
cuda = []
default = []

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

[package]
authors = ["Evan Whinery <evan.whinery@gmail.com>"]
autobenches = false
autobins = false
autoexamples = false
autolib = false
autotests = false
build = "build.rs"
categories = ["science", "algorithms", "data-structures", "mathematics", "development-tools"]
description = "A high-performance, PyTorch inspired, zero dependency Rust machine learning library"
documentation = "https://docs.rs/train-station"
edition = "2021"
homepage = "https://github.com/ewhinery8/train-station"
keywords = ["machine-learning", "autodiff", "neural-networks", "tensors", "zero-dependency"]
license = "MIT OR Apache-2.0"
name = "train-station"
readme = "README.md"
repository = "https://github.com/ewhinery8/train-station"
rust-version = "1.89"
version = "0.3.0"