Fix example U Net learning (#209)

* Added

* Fix

* Remove bymistake add

* Fix

* Fixed lint

* Lint

* Added refbackend

* Fix NDFT

* feat: use finufft as ref backend.

* feat(tests): move ndft vs nufft tests to own file.

* \docs_build [docs]

* Added some changes for and some helopful gitignore

---------

Co-authored-by: chaithyagr <[email protected]>
Co-authored-by: Pierre-antoine Comby <[email protected]>

.github/workflows/test-ci.yml

@@ -20,7 +20,7 @@ env:
 jobs:
   test-cpu:
     runs-on: cpu
-    if: ${{ !contains(github.event.head_commit.message, '!style') || github.ref == 'refs/heads/master' }}
+    if: ${{ !contains(github.event.head_commit.message, '[style]') || github.ref == 'refs/heads/master' }}
     strategy:
       matrix:
         backend: [finufft, pynfft, pynufft-cpu, bart, sigpy, torchkbnufft-cpu]
@@ -97,7 +97,7 @@ jobs:
 
   test-gpu:
     runs-on: gpu
-    if: ${{ !contains(github.event.head_commit.message, '!style') || github.ref == 'refs/heads/master' }}
+    if: ${{ !contains(github.event.head_commit.message, '[style]') || github.ref == 'refs/heads/master' }}
     strategy:
       matrix:
         backend: [cufinufft, gpunufft, torchkbnufft-gpu, tensorflow]
@@ -186,7 +186,7 @@ jobs:
   test-examples:
     runs-on: gpu
     needs: get-commit-message
-    if: ${{ !contains(needs.get-commit-message.outputs.message, '!style') || github.ref == 'refs/heads/master' }}
+    if: ${{ !contains(needs.get-commit-message.outputs.message, '[style]') || github.ref == 'refs/heads/master' }}
 
     steps:
       - uses: actions/checkout@v4
@@ -298,7 +298,7 @@ jobs:
     name: Build API Documentation
     runs-on: gpu
     needs: get-commit-message
-    if: ${{ contains(needs.get-commit-message.outputs.message, '!docs_build') || github.ref == 'refs/heads/master' }}
+    if: ${{ contains(needs.get-commit-message.outputs.message, '[docs]') || github.ref == 'refs/heads/master' }}
     steps:
       - name: Checkout
         uses: actions/checkout@v4

.gitignore

@@ -1,4 +1,6 @@
 *.npy
+*.gif
+docs/sg_execution_times.rst
 build/
 dist/
 *.egg-info/

examples/GPU/example_fastMRI_UNet.py

@@ -27,11 +27,8 @@
 
     \mathbf{\hat{x}} = \mathrm{arg} \min_{\mathbf{x}} || \mathcal{U}_\mathbf{\theta}(\mathbf{y}) - \mathbf{x} ||_2^2
 
-where:
-- \( \mathbf{\hat{x}} \) is the reconstructed MRI image,
-- \( \mathbf{x} \) is the ground truth image,
-- \( \mathbf{y} \) is the input MRI image (e.g., k-space data),
-- \( \mathcal{U}_\mathbf{\theta} \) is the U-Net model parameterized by \( \theta \).
+where :math:`\mathbf{\hat{x}}` is the reconstructed MRI image, :math:`\mathbf{x}` is the ground truth image, 
+:math:`\mathbf{y}` is the input MRI image (e.g., k-space data), and :math:`\mathcal{U}_\mathbf{\theta}` is the U-Net model parameterized by :math:`\theta`.
 
 .. warning::
     We train on a single image here. In practice, this should be done on a database like fastMRI [fastmri]_.
@@ -141,13 +138,13 @@ def plot_state(axs, mri_2D, traj, recon, loss=None, save_name=None):
 
 # %%
 # Start training loop
-epoch = 100
+num_epochs = 2
 optimizer = torch.optim.RAdam(model.parameters(), lr=1e-3)
 losses = []  # Store the loss values and create an animation
 image_files = []  # Store the images to create a gif
 model.train()
 
-with tqdm(range(epoch), unit="steps") as tqdms:
+with tqdm(range(num_epochs), unit="steps") as tqdms:
     for i in tqdms:
         out = model(kspace_mri_2D)  # Forward pass
 
@@ -203,10 +200,20 @@ def plot_state(axs, mri_2D, traj, recon, loss=None, save_name=None):
         / "GPU"
         / "images"
     )
-    shutil.copyfile("mrinufft_learn_Unet.gif", final_dir / "mrinufft_learn_Unet.gif")
+    shutil.copyfile("mrinufft_learn_unet.gif", final_dir / "mrinufft_learn_unet.gif")
 except FileNotFoundError:
     pass
+
 # sphinx_gallery_end_ignore
+
+# sphinx_gallery_thumbnail_path = 'generated/autoexamples/GPU/images/mrinufft_learn_unet.gif'
+
+# %%
+# .. image-sg:: /generated/autoexamples/GPU/images/mrinufft_learn_unet.gif
+#    :alt: example learn_samples
+#    :srcset: /generated/autoexamples/GPU/images/mrinufft_learn_unet.gif
+#    :class: sphx-glr-single-img
+
 # %%
 # Reconstruction from partially trained U-Net model
 model.eval()