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feat: update workspace paths and enhance gitignore

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- Updated stablediffusion crate path from "../stable-diffusion-burn" to "./crates/stable-diffusion-burn" for proper workspace resolution
- Enhanced .gitignore to include generated model files (.mpk, .pt, .bin, .safetensors, .ckpt) and user_data directory
- Added Cargo.lock to gitignore with appropriate comment
- Reorganized IDE files section in gitignore for better clarity
- Added newline at end of file for proper formatting
This commit is contained in:
Ben_Kosytorz
2026-03-05 19:39:14 +01:00
parent 4bb7ca9074
commit 3a67c0979c
1605 changed files with 537032 additions and 2 deletions
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129
crates/stable-diffusion-burn/burn-crates/burn-backend-tests/tests/autodiff/avgpool2d.rs Normal file
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use super::*;
use burn_tensor::module::avg_pool2d;
use burn_tensor::{Shape, Tolerance};
#[test]
fn test_avg_pool2d_simple() {
let test = AvgPool2dTestCase {
batch_size: 1,
channels: 1,
kernel_size_1: 3,
kernel_size_2: 3,
padding_1: 0,
padding_2: 0,
stride_1: 1,
stride_2: 1,
height: 6,
width: 6,
count_include_pad: true,
};
test.assert_output(TestTensor::from_floats(
[[[
[0.11111, 0.22222, 0.33333, 0.33333, 0.22222, 0.11111],
[0.22222, 0.44444, 0.66667, 0.66667, 0.44444, 0.22222],
[0.33333, 0.66667, 1.00000, 1.00000, 0.66667, 0.33333],
[0.33333, 0.66667, 1.00000, 1.00000, 0.66667, 0.33333],
[0.22222, 0.44444, 0.66667, 0.66667, 0.44444, 0.22222],
[0.11111, 0.22222, 0.33333, 0.33333, 0.22222, 0.11111],
]]],
&Default::default(),
));
}
#[test]
fn test_avg_pool2d_complex() {
let test = AvgPool2dTestCase {
batch_size: 1,
channels: 1,
kernel_size_1: 3,
kernel_size_2: 4,
padding_1: 1,
padding_2: 2,
stride_1: 1,
stride_2: 2,
height: 4,
width: 6,
count_include_pad: true,
};
test.assert_output(TestTensor::from_floats(
[[[
[0.33333, 0.33333, 0.33333, 0.33333, 0.33333, 0.33333],
[0.5000, 0.5000, 0.5000, 0.5000, 0.5000, 0.5000],
[0.5000, 0.5000, 0.5000, 0.5000, 0.5000, 0.5000],
[0.33333, 0.33333, 0.33333, 0.33333, 0.33333, 0.33333],
]]],
&Default::default(),
));
}
#[test]
fn test_avg_pool2d_complex_dont_include_pad() {
let test = AvgPool2dTestCase {
batch_size: 1,
channels: 1,
kernel_size_1: 3,
kernel_size_2: 4,
padding_1: 1,
padding_2: 2,
stride_1: 1,
stride_2: 2,
height: 4,
width: 6,
count_include_pad: false,
};
test.assert_output(TestTensor::from_floats(
[[[
[0.6250, 0.6250, 0.41667, 0.41667, 0.6250, 0.6250],
[0.8750, 0.8750, 0.58333, 0.58333, 0.8750, 0.8750],
[0.8750, 0.8750, 0.58333, 0.58333, 0.8750, 0.8750],
[0.6250, 0.6250, 0.41667, 0.41667, 0.6250, 0.6250],
]]],
&Default::default(),
));
}
struct AvgPool2dTestCase {
batch_size: usize,
channels: usize,
kernel_size_1: usize,
kernel_size_2: usize,
padding_1: usize,
padding_2: usize,
stride_1: usize,
stride_2: usize,
height: usize,
width: usize,
count_include_pad: bool,
}
impl AvgPool2dTestCase {
fn assert_output(self, x_grad: TestTensor<4>) {
let shape_x = Shape::new([self.batch_size, self.channels, self.height, self.width]);
let device = Default::default();
let x = TestAutodiffTensor::from_data(
TestTensorInt::arange(0..shape_x.num_elements() as i64, &device)
.reshape::<4, _>(shape_x)
.into_data(),
&device,
)
.require_grad();
let output = avg_pool2d(
x.clone(),
[self.kernel_size_1, self.kernel_size_2],
[self.stride_1, self.stride_2],
[self.padding_1, self.padding_2],
self.count_include_pad,
false,
);
let grads = output.backward();
let x_grad_actual = x.grad(&grads).unwrap();
x_grad.to_data().assert_approx_eq::<FloatElem>(
&x_grad_actual.into_data(),
Tolerance::default().set_half_precision_relative(1e-3),
);
}
}