teeny_core/nn/
conv3d.rs

1/*
2 * Copyright (c) 2026 Teenygrad.
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 *   http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17use core::marker::PhantomData;
18
19use crate::{
20    dtype::{Dtype, EagerTensor, Tensor},
21    nn::Layer,
22};
23
24/// 3-D convolution layer: `output = conv3d(input, weight) [+ b]`
25///
26/// Input shape:  `[N, C_in,  D_in,  H_in,  W_in ]`
27/// Output shape: `[N, C_out, D_out, H_out, W_out]`
28pub struct Conv3d<D: Dtype, IT, OT, const RANK: usize> {
29    /// Number of input channels.
30    pub in_channels: usize,
31    /// Number of output channels.
32    pub out_channels: usize,
33    /// Convolution kernel depth.
34    pub kernel_d: usize,
35    /// Convolution kernel height.
36    pub kernel_h: usize,
37    /// Convolution kernel width.
38    pub kernel_w: usize,
39    /// Stride along the depth dimension.
40    pub stride_d: usize,
41    /// Stride along the height dimension.
42    pub stride_h: usize,
43    /// Stride along the width dimension.
44    pub stride_w: usize,
45    /// Zero-padding along the depth dimension.
46    pub padding_d: usize,
47    /// Zero-padding along the height dimension.
48    pub padding_h: usize,
49    /// Zero-padding along the width dimension.
50    pub padding_w: usize,
51    /// Whether to add a learned bias.
52    pub has_bias: bool,
53    _pd: PhantomData<(D, IT, OT)>,
54}
55
56impl<D: Dtype, IT, OT, const RANK: usize> Conv3d<D, IT, OT, RANK> {
57    /// Creates a new `Conv3d` layer.
58    pub fn new(
59        in_channels: usize,
60        out_channels: usize,
61        kernel_size: (usize, usize, usize),
62        stride: (usize, usize, usize),
63        padding: (usize, usize, usize),
64        has_bias: bool,
65    ) -> Self {
66        Self {
67            in_channels,
68            out_channels,
69            kernel_d: kernel_size.0,
70            kernel_h: kernel_size.1,
71            kernel_w: kernel_size.2,
72            stride_d: stride.0,
73            stride_h: stride.1,
74            stride_w: stride.2,
75            padding_d: padding.0,
76            padding_h: padding.1,
77            padding_w: padding.2,
78            has_bias,
79            _pd: PhantomData,
80        }
81    }
82}
83
84impl<D: Dtype, IT: Tensor<D, RANK> + EagerTensor, OT: Tensor<D, RANK>, const RANK: usize> Layer<IT>
85    for Conv3d<D, IT, OT, RANK>
86{
87    type Output = OT;
88    fn call(&self, _input: IT) -> Self::Output {
89        todo!()
90    }
91}
teeny_core/nn/conv3d.rs

teeny_core/nn/
conv3d.rs
