tensorlogic-train 0.1.0

Training loops, loss composition, and optimization schedules for TensorLogic
Documentation 
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[package]
name = "tensorlogic-train"
version.workspace = true
description = "Training loops, loss composition, and optimization schedules for TensorLogic"
edition.workspace = true
license.workspace = true
homepage.workspace = true
repository.workspace = true
documentation = "https://docs.rs/tensorlogic-train"
readme = "README.md"
keywords = ["tensor", "logic", "training", "optimization", "machine-learning"]
categories = ["science", "algorithms", "mathematics"]

[dependencies]
# Core tensorlogic crates
tensorlogic-ir.workspace = true
tensorlogic-infer.workspace = true
tensorlogic-scirs-backend.workspace = true

# SciRS2 dependencies for training
scirs2-core.workspace = true
scirs2-autograd.workspace = true
scirs2-optimize.workspace = true

# Error handling
thiserror.workspace = true
anyhow.workspace = true

# Data structures
indexmap.workspace = true

# Logging
log.workspace = true
tracing = { workspace = true, optional = true }
tracing-subscriber = { workspace = true, optional = true }

# Serialization (for checkpoints)
serde.workspace = true
serde_json.workspace = true

# Compression for checkpoints
oxiarc-deflate.workspace = true

# Time for TensorBoard timestamps
chrono.workspace = true

# CRC for TensorBoard event format
crc32fast.workspace = true

# Byte order utilities
byteorder.workspace = true

# Hostname for TensorBoard filenames
hostname.workspace = true

[features]
default = []
structured-logging = ["tracing", "tracing-subscriber"]

[dev-dependencies]
criterion.workspace = true
approx.workspace = true

[[bench]]
name = "training_performance"
harness = false

[[bench]]
name = "scheduler_performance"
harness = false

[[bench]]
name = "loss_performance"
harness = false

[[bench]]
name = "callback_overhead"
harness = false

[[bench]]
name = "metrics_performance"
harness = false