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
40 lines
1.2 KiB
Rust
40 lines
1.2 KiB
Rust
use super::*;
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use burn_tensor::TensorData;
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#[test]
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fn should_diff_expand() {
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// Python code to generate the test case values
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// import torch
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// x1 = torch.tensor([4.0, 7.0, 2.0, 3.0], requires_grad=True)
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// x2 = torch.tensor([2.0, 4.5, 7.0, 3.0], requires_grad=True)
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// y = x1.expand(4, 4)
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// z = (x2 * y).sum()
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// z.backward()
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// print("x1", x1.grad)
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// print("x2", x2.grad)
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let device = Default::default();
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let data_1 = TensorData::from([4.0, 7.0, 2.0, 3.0]);
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let tensor_1 = TestAutodiffTensor::<1>::from_data(data_1, &device).require_grad();
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let data_2 = TensorData::from([2.0, 4.5, 7.0, 3.0]);
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let tensor_2 = TestAutodiffTensor::<1>::from_data(data_2, &device).require_grad();
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let tensor_3 = tensor_1.clone().expand([4, 4]);
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// Use unsqueeze to make tensor_2 have the same shape as tensor_3
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let tensor_4 = tensor_2.clone().unsqueeze().mul(tensor_3).sum();
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let grads = tensor_4.backward();
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let grad_1 = tensor_1.grad(&grads).unwrap();
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let grad_2 = tensor_2.grad(&grads).unwrap();
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grad_1
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.to_data()
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.assert_eq(&TensorData::from([8., 18., 28., 12.]), false);
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grad_2
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.to_data()
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.assert_eq(&TensorData::from([16., 28., 8., 12.]), false);
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}
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