Ben_Kosytorz
3a67c0979c
- 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
36 lines
1.1 KiB
Rust
36 lines
1.1 KiB
Rust
use super::*;
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use burn_tensor::Tolerance;
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use burn_tensor::{TensorData, activation};
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#[test]
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fn should_diff_sigmoid() {
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let data = TensorData::from([0.8762]);
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let device = Default::default();
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let tensor_1 = TestAutodiffTensor::<1>::from_data(data, &device).require_grad();
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let tensor_2 = activation::sigmoid(tensor_1.clone());
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let grads = tensor_2.backward();
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let grad = tensor_1.grad(&grads).unwrap();
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let expected = TensorData::from([0.207549]);
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grad.to_data()
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.assert_approx_eq::<FloatElem>(&expected, Tolerance::default());
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}
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#[test]
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fn small_neg_val_should_not_cause_grad_overflow() {
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let data = TensorData::from([-90.0]);
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let device = Default::default();
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let tensor_1 = TestAutodiffTensor::<1>::from_data(data, &device).require_grad();
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let tensor_2 = activation::sigmoid(tensor_1.clone());
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let grads = tensor_2.backward();
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let grad = tensor_1.grad(&grads).unwrap();
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let expected = TensorData::from([0.0]);
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grad.to_data()
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.assert_approx_eq::<FloatElem>(&expected, Tolerance::default());
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}
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