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//! # Tract
//!
//! Tiny, no-nonsense, self contained, portable TensorFlow and ONNX inference.
//!
//! ## Example
//!
//! ```
//! # extern crate tract_core;
//! # fn main() {
//! use tract_core::internal::*;
//!
//! // build a simple model that just add 3 to each input component
//! let mut model = InferenceModel::default();
//!
//! let input = model.add_source("input", InferenceFact::default()).unwrap();
//! let three = model.add_const("three".to_string(), tensor0(3f32)).unwrap();
//! let add = model.wire_node("add".to_string(),
//!     tract_core::ops::math::add::bin(),
//!     [input, three].as_ref()
//!     ).unwrap();
//!
//! model.auto_outputs().unwrap();
//!
//! // We build an execution plan. Default inputs and outputs are inferred from
//! // the model graph.
//! let plan = SimplePlan::new(&model).unwrap();
//!
//! // run the computation.
//! let input = tensor1(&[1.0f32, 2.5, 5.0]);
//! let mut outputs = plan.run(tvec![input]).unwrap();
//!
//! // take the first and only output tensor
//! let mut tensor = outputs.pop().unwrap();
//!
//! assert_eq!(tensor, rctensor1(&[4.0f32, 5.5, 8.0]));
//! # }
//! ```
//!
//! While creating a model from Rust code is useful for testing the library,
//! real-life use-cases will usually load a TensorFlow or ONNX model using
//! tract-tensorflow or tract-onnx crates.
//!

extern crate bit_set;
#[macro_use]
extern crate derive_new;
#[macro_use]
extern crate downcast_rs;
#[macro_use]
pub extern crate error_chain;
#[allow(unused_imports)]
#[macro_use]
extern crate itertools;
#[allow(unused_imports)]
#[macro_use]
extern crate log;
#[allow(unused_imports)]
#[macro_use]
pub extern crate ndarray;
extern crate num_integer;
extern crate num_traits;
#[macro_use]
extern crate maplit;
#[macro_use]
pub extern crate objekt;
#[cfg(test)]
extern crate env_logger;
#[cfg(test)]
extern crate proptest;
#[cfg(feature = "serialize")]
extern crate serde;
extern crate smallvec;
#[cfg(feature = "serialize")]
#[macro_use]
extern crate serde_derive;

extern crate tract_linalg;

#[macro_use]
pub mod macros;
#[macro_use]
pub mod analyser;
#[macro_use]
pub mod ops;

pub mod broadcast;
pub mod datum;
pub mod dim;
pub mod errors;
pub mod framework;
pub mod model;
mod optim;
pub mod plan;
pub mod pulse;
pub mod tensor;

pub use crate::errors::*;

/// This prelude is meant for code using tract.
pub mod prelude {
    pub use crate::analyser::types::InferenceFact;
    pub use crate::datum::{Datum, DatumType};
    pub use crate::dim::TDim;
    pub use crate::errors::*;
    pub use crate::framework::Framework;
    pub use crate::model::*;
    pub use crate::plan::{SimplePlan, SimpleState};
    pub use crate::tensor::litteral::*;
    pub use crate::tensor::{IntoArcTensor, IntoTensor, Tensor};
    pub use crate::tvec;
    pub use std::sync::Arc;
}

/// This prelude is meant for code extending tract (like implementing new ops).
pub mod internal {
    pub use crate::analyser::rules::expr::{IntoExp, ToDimExp};
    pub use crate::analyser::rules::{InferenceResult, InferenceRulesOp, Solver, TensorProxy};
    pub use crate::analyser::types::TypeFact;
    pub use crate::analyser::types::*;
    pub use crate::datum::FloatLike;
    pub use crate::dim::{DimLike, TDim, ToDim};
    pub use crate::framework::*;
    pub use crate::model::*;
    pub use crate::ops::element_wise::ElementWiseMiniOp;
    pub use crate::ops::{
        check_input_arity, check_output_arity, AxesInfo, AxisInfo, Cost, InferenceOp, Op, OpState,
        PulsedOp, StatefullOp, StatelessOp, Validation,
    };
    pub use crate::plan::SessionState;
    pub use crate::prelude::*;
    pub use crate::pulse::{PulsedFact, PulsedModel, PulsedNode};
    pub use crate::{args_1, args_2, args_3, args_4};
    pub use std::borrow::Cow;
    pub use std::collections::HashMap;
    pub use std::marker::PhantomData;
    pub use tract_linalg::f16::f16;
}

#[cfg(test)]
#[allow(dead_code)]
fn setup_test_logger() {
    let _ =
        env_logger::Builder::from_default_env().filter_level(log::LevelFilter::Trace).try_init();
}