vision-rs 0.1.1

A high-performance computer vision SDK for Rust.
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/*
 * Copyright 2026 Teenygrad
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */


use teeny_core::{dtype::Float, graph::{Op, SymTensor}, name_scope::name_scope};

use super::conv::conv;

// ── Graph helper ──────────────────────────────────────────────────────────────

pub(super) fn elem_add(a: SymTensor, b: SymTensor) -> SymTensor {
    let shape = a.shape.clone();
    let node_id = a.graph.borrow_mut().add_node(
        Op::Add, vec![a.node_id, b.node_id], a.dtype, shape.clone(),
    );
    SymTensor { node_id, graph: a.graph.clone(), dtype: a.dtype, shape }
}

// ── Bottleneck variants ───────────────────────────────────────────────────────

/// `conv(c → c//2, k=3) → conv(c//2 → c, k=3)`.
///
/// Matches `ultralytics.nn.modules.block.Bottleneck(k=(3,3), e=0.5)` defaults.
pub fn bottleneck_std<D: Float + 'static>(c: usize, shortcut: bool) -> impl Fn(SymTensor) -> SymTensor {
    let c_inner = (c as f32 * 0.5) as usize;
    let cv1 = conv::<D>(c, c_inner, 3, 1);
    let cv2 = conv::<D>(c_inner, c, 3, 1);
    move |x: SymTensor| {
        let y = {
            let tmp = { let _g = name_scope("cv1"); cv1(x.clone()) };
            let _g = name_scope("cv2"); cv2(tmp)
        };
        if shortcut { elem_add(x, y) } else { y }
    }
}

/// `conv(c → c, k=3) → conv(c → c, k=3)`.
///
/// Used as the inner bottleneck inside `C3k` blocks (e=1.0).
pub fn bottleneck_3x3<D: Float + 'static>(c: usize, shortcut: bool) -> impl Fn(SymTensor) -> SymTensor {
    let cv1 = conv::<D>(c, c, 3, 1);
    let cv2 = conv::<D>(c, c, 3, 1);
    move |x: SymTensor| {
        let y = {
            let tmp = { let _g = name_scope("cv1"); cv1(x.clone()) };
            let _g = name_scope("cv2"); cv2(tmp)
        };
        if shortcut { elem_add(x, y) } else { y }
    }
}