torsh-python 0.1.1

Python bindings for ToRSh - PyTorch-compatible deep learning in Rust
Documentation 
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[package]
name = "torsh-python"
version.workspace = true
edition.workspace = true
authors.workspace = true
license.workspace = true
repository.workspace = true
homepage.workspace = true
rust-version.workspace = true
description = "Python bindings for ToRSh - PyTorch-compatible deep learning in Rust"
readme = "README.md"
documentation = "https://docs.rs/torsh-python"
keywords = ["deep-learning", "python", "pyo3", "machine-learning", "bindings"]
categories = ["science", "api-bindings"]

[lints]
workspace = true

[lib]
name = "rstorch_python"
crate-type = ["cdylib"]
# Disable Rust test harness for cdylib - use pytest instead
test = false

[dependencies]
# PyO3 for Python bindings
pyo3 = { workspace = true, features = ["extension-module", "abi3-py38"] }
numpy = { workspace = true }

# ToRSh crates
torsh-core = { workspace = true }
torsh-tensor = { workspace = true }
torsh-nn = { workspace = true }
torsh-optim = { workspace = true }
# torsh-data = { workspace = true }  # Temporarily disabled due to compilation errors
# torsh-autograd = { workspace = true }  # Temporarily disabled due to scirs2 API incompatibilities
# torsh-distributed = { workspace = true }  # Temporarily disabled due to compilation errors

# ✅ SciRS2 POLICY: Use scirs2-core for all scientific computing needs
scirs2-core = { workspace = true }

# Error handling
thiserror = { workspace = true }
anyhow = { workspace = true }

# Utilities
parking_lot = { workspace = true }

[features]
default = []
extension-module = ["pyo3/extension-module"]

[package.metadata.maturin]
python-source = "python"
module-name = "rstorch"
bindings = "pyo3"