diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 345f6ce9..91d6944a 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -13,6 +13,9 @@ jobs:
     env:
       HF_HOME: ${{ github.workspace }}/.cache/huggingface
       HF_HUB_CACHE: ${{ github.workspace }}/.cache/huggingface/hub
+      HF_HUB_DOWNLOAD_TIMEOUT: "60"
+      HF_HUB_ETAG_TIMEOUT: "30"
+      HF_TOKEN: ${{ secrets.HF_TOKEN }}
 
     strategy:
       matrix:
@@ -36,12 +39,9 @@ jobs:
       - name: Cache huggingface
         uses: actions/cache@v4
         with:
-          path: ~/.cache/huggingface
-          key: ${{ runner.os }}-huggingface
-
-      - name: Ensure Hugging Face cache directories exist
-        run: |
-          mkdir -p "$HF_HUB_CACHE"
+          path: ${{ github.workspace }}/.cache/huggingface
+          key: huggingface-${{ hashFiles('pyproject.toml') }}
+          restore-keys: huggingface-
 
       - name: Ensure Hugging Face cache directories exist
         run: |
diff --git a/DeepSDFStruct/SDF.py b/DeepSDFStruct/SDF.py
index 00d6d670..b11eb2ff 100644
--- a/DeepSDFStruct/SDF.py
+++ b/DeepSDFStruct/SDF.py
@@ -366,6 +366,8 @@ def plot_slice(
         cmap="seismic",
         show_zero_level=True,
         deformation_function=None,
+        xlim=None,
+        ylim=None,
     ):
         """Plot a 2D slice through an SDF as a contour plot.
 
@@ -435,8 +437,15 @@ def plot_slice(
             fig, ax = plt.subplots()
             plt_show = True
         bounds = self._get_domain_bounds()
-        xlim, ylim = project_bounds(origin, normal, bounds=bounds)
-        points = generate_plane_points(origin, normal, res, xlim, ylim)
+
+        if self.geometric_dim == 3:
+            if xlim is None:
+                xlim, ylim = project_bounds(origin, normal, bounds=bounds)
+            points = generate_plane_points(origin, normal, res, xlim, ylim)
+        else:
+            if xlim is None:
+                xlim, ylim = bounds.detach().cpu().numpy().T
+            points = generate_plane_points(origin, normal, res, xlim, ylim)[:, :2]
 
         sdf_device = self.get_device()
         points = torch.from_numpy(points).to(torch.float32).to(sdf_device)
@@ -1636,6 +1645,11 @@ def project_bounds(origin, normal, bounds=None):
 
     if bounds is None:
         bounds = np.array([[0, 0, 0], [1, 1, 1]])
+    elif isinstance(bounds, torch.Tensor):
+        bounds = bounds.detach().cpu().numpy()
+    if bounds.shape[1] == 2:
+        logger.info("cannot project 2D onto 2D, returning input")
+        return bounds[0], bounds[1]
 
     bmin, bmax = bounds
 
diff --git a/DeepSDFStruct/deep_sdf/data.py b/DeepSDFStruct/deep_sdf/data.py
index 0bf31bb0..5cad5a6f 100644
--- a/DeepSDFStruct/deep_sdf/data.py
+++ b/DeepSDFStruct/deep_sdf/data.py
@@ -227,9 +227,9 @@ def __init__(
                         neg_tensor[torch.randperm(neg_tensor.shape[0])],
                     ]
                 )
-                if "E" in npz.keys():
+                if "C" in npz.keys():
                     self.loaded_mat_properties.append(
-                        torch.from_numpy(npz["E.npy"]).to(torch.float32)
+                        torch.from_numpy(npz["C.npy"]).to(torch.float32).reshape(-1)
                     )
                 self.filenames.append(filename)
 
@@ -247,12 +247,12 @@ def __getitem__(self, idx):
         if self.load_ram:
             return (
                 unpack_sdf_samples_from_ram(self.loaded_data[idx], self.subsample),
-                mat_prop,
+                mat_prop.unsqueeze(0).expand(self.subsample, -1),
                 idx,
             )
         else:
             return (
                 unpack_sdf_samples(filename, self.geom_dimension, self.subsample),
-                mat_prop,
+                mat_prop.unsqueeze(0).expand(self.subsample, -1),
                 idx,
             )
diff --git a/DeepSDFStruct/deep_sdf/networks/deep_sdf_decoder.py b/DeepSDFStruct/deep_sdf/networks/deep_sdf_decoder.py
index 5f47c3df..49731230 100644
--- a/DeepSDFStruct/deep_sdf/networks/deep_sdf_decoder.py
+++ b/DeepSDFStruct/deep_sdf/networks/deep_sdf_decoder.py
@@ -42,6 +42,7 @@ def __init__(
         xyz_in_all=None,
         use_tanh=False,
         latent_dropout=False,
+        homogen_predictor_dims=None,
     ):
         super(DeepSDFDecoder, self).__init__()
 
@@ -95,6 +96,20 @@ def make_sequence():
         self.dropout_prob = dropout_prob
         self.dropout = dropout
         self.th = nn.Tanh()
+        if homogen_predictor_dims is not None:
+            hp_dims = [latent_size] + homogen_predictor_dims
+            homogen_layers = []
+
+            for i in range(len(hp_dims) - 1):
+                homogen_layers.append(nn.Linear(hp_dims[i], hp_dims[i + 1]))
+
+                # No activation after final layer
+                if i < len(hp_dims) - 2:
+                    homogen_layers.append(nn.ReLU())
+
+            self.homogen_network = nn.Sequential(*homogen_layers)
+        else:
+            self.homogen_network = None
 
     # input: N x (L+3), or N x (L+geom_dimension)
     def forward(self, input):
@@ -130,3 +145,11 @@ def forward(self, input):
                     x = F.dropout(x, p=self.dropout_prob, training=self.training)
 
         return x
+
+    def predict_C_homogenized(self, latent_vec):
+        if self.homogen_network is not None:
+            return self.homogen_network(latent_vec)
+        else:
+            raise RuntimeError(
+                "Cannot predict homogenized elasticity tensor, because homogenization network is not defined"
+            )
diff --git a/DeepSDFStruct/deep_sdf/training.py b/DeepSDFStruct/deep_sdf/training.py
index a4720ada..5da64c49 100644
--- a/DeepSDFStruct/deep_sdf/training.py
+++ b/DeepSDFStruct/deep_sdf/training.py
@@ -485,6 +485,9 @@ def empirical_stat(latent_vecs, indices):
     )
     loss_fun_spec = get_spec_with_default(specs, "LossFunction", "clampedL1")
     loss_fun = get_loss_function(loss_fun_spec)
+    add_homogeniation = get_spec_with_default(specs, "AddHomogenization", False)
+    if add_homogeniation:
+        logger.info("adding homogenization loss")
 
     optimizer_all = torch.optim.Adam(
         [
@@ -561,7 +564,10 @@ def empirical_stat(latent_vecs, indices):
         for sdf_data, properties, indices in sdf_loader:
             # Process the input data
             sdf_data = sdf_data.reshape(-1, geom_dimension + 1).to(device)
-            properties = properties.to(device)
+            properties_expanded = properties.reshape(-1, properties.shape[-1]).to(
+                device
+            )
+
             indices = indices.to(device)
 
             num_sdf_samples = sdf_data.shape[0]
@@ -581,13 +587,16 @@ def empirical_stat(latent_vecs, indices):
             )
 
             sdf_gt = torch.chunk(sdf_gt, batch_split)
+            properties_chunked = torch.chunk(properties_expanded, batch_split)
 
             batch_loss = 0.0
             batch_reg_loss = 0.0
+            batch_hom_loss = 0.0
             optimizer_all.zero_grad()
 
             for i in range(batch_split):
                 batch_lat_vecs = lat_vecs(indices[i])
+                batch_properties = properties_chunked[i]
 
                 input = torch.cat([batch_lat_vecs, xyz[i]], dim=1)
 
@@ -599,11 +608,22 @@ def empirical_stat(latent_vecs, indices):
 
                 chunk_loss = loss_fun(pred_sdf, sdf_gt[i].to(device))
 
-                l2_size_loss = torch.sum(torch.norm(batch_lat_vecs, dim=1))
-                reg_loss = (code_reg_lambda * min(1, epoch / 100) * l2_size_loss) / (
-                    num_sdf_samples / batch_split
-                )
+                if add_homogeniation:
+                    pred_properties = decoder.predict_C_homogenized(batch_lat_vecs)
+
+                    hom_loss = torch.nn.functional.mse_loss(
+                        pred_properties, batch_properties, reduction="mean"
+                    )
+
+                    chunk_loss += hom_loss.to(device)
+                    batch_hom_loss += hom_loss.item()
 
+                # standard l2 latent vector loss
+                reg_loss = (
+                    code_reg_lambda
+                    * min(1, epoch / 100)
+                    * torch.mean(torch.norm(batch_lat_vecs, dim=1))
+                )
                 chunk_loss = chunk_loss + reg_loss.to(device)
                 batch_reg_loss = batch_reg_loss + reg_loss.to(device)
 
@@ -637,9 +657,18 @@ def empirical_stat(latent_vecs, indices):
                 f"Finished {epoch} ({epoch}/{num_epochs}) [{epoch/num_epochs*100:.2f}%] after {total_time}"
             )
         else:
-            pbar.set_postfix(
-                {"Loss": f"{batch_loss:.4f}", "Reg": f"{batch_reg_loss:.4f}"}
-            )
+            if add_homogeniation:
+                pbar.set_postfix(
+                    {
+                        "Loss": f"{batch_loss:.4f}",
+                        "Reg": f"{batch_reg_loss:.4f}",
+                        "Hom": f"{batch_hom_loss:.4f}",
+                    }
+                )
+            else:
+                pbar.set_postfix(
+                    {"Loss": f"{batch_loss:.4f}", "Reg": f"{batch_reg_loss:.4f}"}
+                )
         seconds_elapsed = end - start
         timing_log.append(seconds_elapsed)
 
diff --git a/DeepSDFStruct/sampling.py b/DeepSDFStruct/sampling.py
index 6f70392b..8bdc2e23 100644
--- a/DeepSDFStruct/sampling.py
+++ b/DeepSDFStruct/sampling.py
@@ -48,6 +48,8 @@
 from functools import partial
 from itertools import starmap
 import multiprocessing
+from dataclasses import dataclass
+
 
 import vtk
 import numpy as np
@@ -114,6 +116,18 @@ class SphereParameters(typing.TypedDict):
     r: float
 
 
+@dataclass
+class GeometryInstance:
+    name: str
+    geom: trimesh.Trimesh
+    C: np.ndarray | None
+
+    def __init__(self, name: str, geom: trimesh.Trimesh, C: np.ndarray | None):
+        self.name = name
+        self.geom = geom
+        self.C = C
+
+
 class SampledSDF:
     """Container for sampled SDF points and their distance values.
 
@@ -229,7 +243,7 @@ def __add__(self, other):
 
 
 def _process_single_geometry_instance(
-    geometry,
+    geom_instance: GeometryInstance,
     file_name: str,
     folder_name: pathlib.Path,
     scale,
@@ -247,16 +261,17 @@ def _process_single_geometry_instance(
         logger.warning(f"File {fname} already exists")
         return
     mesh = None
-    if isinstance(geometry, SDFBase):
-        sdf = geometry
-    elif isinstance(geometry, trimesh.Trimesh):
-        mesh = geometry
+    geom = geom_instance.geom
+    if isinstance(geom, SDFBase):
+        sdf = geom
+    elif isinstance(geom, trimesh.Trimesh):
+        mesh = geom
         sdf = SDFfromMesh(mesh, scale=scale)
         if also_save_mesh:
             mesh.export(fname.with_suffix(".stl"))
     else:
         raise NotImplementedError(
-            f"Geometry must be either trimesh or SDFBase, but not {type(geometry)}."
+            f"Geometry must be either trimesh or SDFBase, but not {type(geom)}."
         )
     sampled_sdf = random_sample_sdf(
         sdf,
@@ -268,7 +283,7 @@ def _process_single_geometry_instance(
         if not isinstance(mesh, trimesh.Trimesh):
             logger.warning(
                 "Add surface samples was specified, but geometry"
-                f"is not given as a mesh but as {type(geometry)}"
+                f"is not given as a mesh but as {type(geom)}"
             )
         else:
             surf_samples = sample_mesh_surface(
@@ -276,8 +291,10 @@ def _process_single_geometry_instance(
             )
             sampled_sdf += surf_samples
     pos, neg = sampled_sdf.split_pos_neg()
-
-    np.savez(fname, neg=neg.stacked, pos=pos.stacked)
+    if geom_instance.C is not None:
+        np.savez(fname, neg=neg.stacked, pos=pos.stacked, C=geom_instance.C)
+    else:
+        np.savez(fname, neg=neg.stacked, pos=pos.stacked)
     if also_save_vtk:
         save_points_to_vtp(fname.with_suffix(".vtp"), neg=neg.stacked, pos=pos.stacked)
 
@@ -294,7 +311,7 @@ def __init__(
         self.outdir = outdir
         self.splitdir = splitdir
         self.dataset_name = dataset_name
-        self.geometries = {}
+        self.geometries: dict[str, dict[str, GeometryInstance]] = {}
         self.stds = stds
         folder_name = pathlib.Path(outdir) / dataset_name
         if os.path.exists(folder_name):
@@ -306,12 +323,22 @@ def __init__(
         else:
             os.makedirs(folder_name)
 
-    def add_class(self, geom_list: list, class_name: str, n_faces=100) -> None:
+    def add_class(
+        self,
+        geom_list: list,
+        class_name: str,
+        n_faces=100,
+        homogenized_c: list[np.ndarray] | None = None,
+    ) -> None:
         """
         Adds a geometry to the sampler object. Tries to transform inputs to
         trimesh data. In case the geometry is a spline object, the n_faces
         parameter determines the accuracy of the extracted mesh
         """
+        if homogenized_c is not None:
+            assert len(geom_list) == len(
+                homogenized_c
+            ), f"Length of geometries ({len(geom_list)}) does not match length of homogenized elasticity tensors ({len(homogenized_c)})"
         instances = {}
         for i, geom in enumerate(geom_list):
             instance_name = f"{class_name}_{i:05}"
@@ -323,7 +350,11 @@ def add_class(self, geom_list: list, class_name: str, n_faces=100) -> None:
             elif isinstance(geom, torchSurfMesh):
                 geom = geom.to_trimesh()
 
-            instances[instance_name] = geom
+            if homogenized_c is not None:
+                C = homogenized_c[i]
+            else:
+                C = None
+            instances[instance_name] = GeometryInstance(instance_name, geom, C)
         self.geometries[class_name] = instances
 
     def process_geometries(
diff --git a/DeepSDFStruct/trained_models/test_experiment/LatentCodes/latent_code_data_map.json b/DeepSDFStruct/trained_models/test_experiment/LatentCodes/latent_code_data_map.json
new file mode 100644
index 00000000..c6014077
--- /dev/null
+++ b/DeepSDFStruct/trained_models/test_experiment/LatentCodes/latent_code_data_map.json
@@ -0,0 +1,106 @@
+{
+    "data_source": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd",
+    "sdf_samples_subdir": "SdfSamples",
+    "latent_codes": [
+        {
+            "latent_index": 0,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00000.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00000.npz"
+        },
+        {
+            "latent_index": 1,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00001.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00001.npz"
+        },
+        {
+            "latent_index": 2,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00002.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00002.npz"
+        },
+        {
+            "latent_index": 3,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00003.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00003.npz"
+        },
+        {
+            "latent_index": 4,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00004.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00004.npz"
+        },
+        {
+            "latent_index": 5,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00005.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00005.npz"
+        },
+        {
+            "latent_index": 6,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00006.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00006.npz"
+        },
+        {
+            "latent_index": 7,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00007.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00007.npz"
+        },
+        {
+            "latent_index": 8,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00008.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00008.npz"
+        },
+        {
+            "latent_index": 9,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00009.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00009.npz"
+        },
+        {
+            "latent_index": 10,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00010.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00010.npz"
+        },
+        {
+            "latent_index": 11,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00011.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00011.npz"
+        },
+        {
+            "latent_index": 12,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00012.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00012.npz"
+        },
+        {
+            "latent_index": 13,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00013.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00013.npz"
+        },
+        {
+            "latent_index": 14,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00014.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00014.npz"
+        },
+        {
+            "latent_index": 15,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00015.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00015.npz"
+        },
+        {
+            "latent_index": 16,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00016.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00016.npz"
+        },
+        {
+            "latent_index": 17,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00017.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00017.npz"
+        },
+        {
+            "latent_index": 18,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00018.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00018.npz"
+        },
+        {
+            "latent_index": 19,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00019.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00019.npz"
+        }
+    ]
+}
\ No newline at end of file
diff --git a/DeepSDFStruct/trained_models/test_experiment/training_summary.json b/DeepSDFStruct/trained_models/test_experiment/training_summary.json
index 6b14bee0..24acb5b6 100644
--- a/DeepSDFStruct/trained_models/test_experiment/training_summary.json
+++ b/DeepSDFStruct/trained_models/test_experiment/training_summary.json
@@ -1,10 +1,10 @@
 {
-    "loss": 0.0635075570008433,
+    "loss": 0.05482380986213684,
     "num_epochs": 5,
-    "timestamp": "2026-01-19 11:05:17",
+    "timestamp": "2026-05-21 17:40:15",
     "host_name": "neptune",
     "device": "cpu",
-    "training_duration": "0:00:02",
+    "training_duration": "0:00:06",
     "data_dir": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd",
-    "version": "1.4.2.dev7+gce8bfe994.d20260119"
+    "version": "1.7.1.dev40+g989384bd4.d20260330"
 }
\ No newline at end of file
diff --git a/DeepSDFStruct/trained_models/test_experiment_hierarchical/LatentCodes/latent_code_data_map.json b/DeepSDFStruct/trained_models/test_experiment_hierarchical/LatentCodes/latent_code_data_map.json
new file mode 100644
index 00000000..c6014077
--- /dev/null
+++ b/DeepSDFStruct/trained_models/test_experiment_hierarchical/LatentCodes/latent_code_data_map.json
@@ -0,0 +1,106 @@
+{
+    "data_source": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd",
+    "sdf_samples_subdir": "SdfSamples",
+    "latent_codes": [
+        {
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+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00000.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00000.npz"
+        },
+        {
+            "latent_index": 1,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00001.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00001.npz"
+        },
+        {
+            "latent_index": 2,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00002.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00002.npz"
+        },
+        {
+            "latent_index": 3,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00003.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00003.npz"
+        },
+        {
+            "latent_index": 4,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00004.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00004.npz"
+        },
+        {
+            "latent_index": 5,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00005.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00005.npz"
+        },
+        {
+            "latent_index": 6,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00006.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00006.npz"
+        },
+        {
+            "latent_index": 7,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00007.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00007.npz"
+        },
+        {
+            "latent_index": 8,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00008.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00008.npz"
+        },
+        {
+            "latent_index": 9,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00009.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00009.npz"
+        },
+        {
+            "latent_index": 10,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00010.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00010.npz"
+        },
+        {
+            "latent_index": 11,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00011.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00011.npz"
+        },
+        {
+            "latent_index": 12,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00012.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00012.npz"
+        },
+        {
+            "latent_index": 13,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00013.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00013.npz"
+        },
+        {
+            "latent_index": 14,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00014.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00014.npz"
+        },
+        {
+            "latent_index": 15,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00015.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00015.npz"
+        },
+        {
+            "latent_index": 16,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00016.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00016.npz"
+        },
+        {
+            "latent_index": 17,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00017.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00017.npz"
+        },
+        {
+            "latent_index": 18,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00018.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00018.npz"
+        },
+        {
+            "latent_index": 19,
+            "relative_npz_filename": "microstructure/CrossLattice/CrossLattice_00019.npz",
+            "npz_filename": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd/SdfSamples/microstructure/CrossLattice/CrossLattice_00019.npz"
+        }
+    ]
+}
\ No newline at end of file
diff --git a/DeepSDFStruct/trained_models/test_experiment_hierarchical/training_summary.json b/DeepSDFStruct/trained_models/test_experiment_hierarchical/training_summary.json
index 4540e490..9ff8d2c8 100644
--- a/DeepSDFStruct/trained_models/test_experiment_hierarchical/training_summary.json
+++ b/DeepSDFStruct/trained_models/test_experiment_hierarchical/training_summary.json
@@ -1,10 +1,10 @@
 {
     "loss": 0.12290580123662949,
     "num_epochs": 5,
-    "timestamp": "2026-02-10 16:05:37",
+    "timestamp": "2026-05-21 17:39:59",
     "host_name": "neptune",
     "device": "cpu",
-    "training_duration": "0:00:01",
-    "data_dir": "/usr2/lfrei/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd",
-    "version": "1.1.1.dev23+g6170b62c2.d20251202"
+    "training_duration": "0:00:08",
+    "data_dir": "/usr2/mkofler/.cache/huggingface/hub/datasets--mkofler--lattice_structure_unit_cells/snapshots/b80339abc071df77ff81e8abc19ad4856d96ddbd",
+    "version": "1.7.1.dev40+g989384bd4.d20260330"
 }
\ No newline at end of file
diff --git a/DeepSDFStruct/trained_models/test_experiment_homogenization/LatentCodes/latent_code_data_map.json b/DeepSDFStruct/trained_models/test_experiment_homogenization/LatentCodes/latent_code_data_map.json
new file mode 100644
index 00000000..9920102a
--- /dev/null
+++ b/DeepSDFStruct/trained_models/test_experiment_homogenization/LatentCodes/latent_code_data_map.json
@@ -0,0 +1,5006 @@
+{
+    "data_source": "/storage/mkofler/dissertation/data/",
+    "sdf_samples_subdir": "SdfSamples",
+    "latent_codes": [
+        {
+            "latent_index": 0,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00000.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00000.npz"
+        },
+        {
+            "latent_index": 1,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00001.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00001.npz"
+        },
+        {
+            "latent_index": 2,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00002.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00002.npz"
+        },
+        {
+            "latent_index": 3,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00003.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00003.npz"
+        },
+        {
+            "latent_index": 4,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00004.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00004.npz"
+        },
+        {
+            "latent_index": 5,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00005.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00005.npz"
+        },
+        {
+            "latent_index": 6,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00006.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00006.npz"
+        },
+        {
+            "latent_index": 7,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00007.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00007.npz"
+        },
+        {
+            "latent_index": 8,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00008.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00008.npz"
+        },
+        {
+            "latent_index": 9,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00009.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00009.npz"
+        },
+        {
+            "latent_index": 10,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00010.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00010.npz"
+        },
+        {
+            "latent_index": 11,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00011.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00011.npz"
+        },
+        {
+            "latent_index": 12,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00012.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00012.npz"
+        },
+        {
+            "latent_index": 13,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00013.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00013.npz"
+        },
+        {
+            "latent_index": 14,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00014.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00014.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00015.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00015.npz"
+        },
+        {
+            "latent_index": 16,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00016.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00016.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00017.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00017.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00018.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00018.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00019.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00019.npz"
+        },
+        {
+            "latent_index": 20,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00020.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00020.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00021.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00021.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00022.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00022.npz"
+        },
+        {
+            "latent_index": 23,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00023.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00023.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00024.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00024.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00025.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00025.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00026.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00026.npz"
+        },
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00027.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00027.npz"
+        },
+        {
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+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00028.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00029.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00029.npz"
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+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00031.npz"
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+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00032.npz"
+        },
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+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00033.npz"
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+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00034.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00034.npz"
+        },
+        {
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+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00035.npz"
+        },
+        {
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+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00036.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00036.npz"
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+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00955.npz"
+        },
+        {
+            "latent_index": 956,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00956.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00956.npz"
+        },
+        {
+            "latent_index": 957,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00957.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00957.npz"
+        },
+        {
+            "latent_index": 958,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00958.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00958.npz"
+        },
+        {
+            "latent_index": 959,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00959.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00959.npz"
+        },
+        {
+            "latent_index": 960,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00960.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00960.npz"
+        },
+        {
+            "latent_index": 961,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00961.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00961.npz"
+        },
+        {
+            "latent_index": 962,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00962.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00962.npz"
+        },
+        {
+            "latent_index": 963,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00963.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00963.npz"
+        },
+        {
+            "latent_index": 964,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00964.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00964.npz"
+        },
+        {
+            "latent_index": 965,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00965.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00965.npz"
+        },
+        {
+            "latent_index": 966,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00966.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00966.npz"
+        },
+        {
+            "latent_index": 967,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00967.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00967.npz"
+        },
+        {
+            "latent_index": 968,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00968.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00968.npz"
+        },
+        {
+            "latent_index": 969,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00969.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00969.npz"
+        },
+        {
+            "latent_index": 970,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00970.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00970.npz"
+        },
+        {
+            "latent_index": 971,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00971.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00971.npz"
+        },
+        {
+            "latent_index": 972,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00972.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00972.npz"
+        },
+        {
+            "latent_index": 973,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00973.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00973.npz"
+        },
+        {
+            "latent_index": 974,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00974.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00974.npz"
+        },
+        {
+            "latent_index": 975,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00975.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00975.npz"
+        },
+        {
+            "latent_index": 976,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00976.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00976.npz"
+        },
+        {
+            "latent_index": 977,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00977.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00977.npz"
+        },
+        {
+            "latent_index": 978,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00978.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00978.npz"
+        },
+        {
+            "latent_index": 979,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00979.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00979.npz"
+        },
+        {
+            "latent_index": 980,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00980.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00980.npz"
+        },
+        {
+            "latent_index": 981,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00981.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00981.npz"
+        },
+        {
+            "latent_index": 982,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00982.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00982.npz"
+        },
+        {
+            "latent_index": 983,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00983.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00983.npz"
+        },
+        {
+            "latent_index": 984,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00984.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00984.npz"
+        },
+        {
+            "latent_index": 985,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00985.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00985.npz"
+        },
+        {
+            "latent_index": 986,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00986.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00986.npz"
+        },
+        {
+            "latent_index": 987,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00987.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00987.npz"
+        },
+        {
+            "latent_index": 988,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00988.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00988.npz"
+        },
+        {
+            "latent_index": 989,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00989.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00989.npz"
+        },
+        {
+            "latent_index": 990,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00990.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00990.npz"
+        },
+        {
+            "latent_index": 991,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00991.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00991.npz"
+        },
+        {
+            "latent_index": 992,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00992.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00992.npz"
+        },
+        {
+            "latent_index": 993,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00993.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00993.npz"
+        },
+        {
+            "latent_index": 994,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00994.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00994.npz"
+        },
+        {
+            "latent_index": 995,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00995.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00995.npz"
+        },
+        {
+            "latent_index": 996,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00996.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00996.npz"
+        },
+        {
+            "latent_index": 997,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00997.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00997.npz"
+        },
+        {
+            "latent_index": 998,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00998.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00998.npz"
+        },
+        {
+            "latent_index": 999,
+            "relative_npz_filename": "microstructure_splines_v2/splines_v2/splines_v2_00999.npz",
+            "npz_filename": "/storage/mkofler/dissertation/data/SdfSamples/microstructure_splines_v2/splines_v2/splines_v2_00999.npz"
+        }
+    ]
+}
\ No newline at end of file
diff --git a/DeepSDFStruct/trained_models/test_experiment_homogenization/LatentCodes/latest.pth b/DeepSDFStruct/trained_models/test_experiment_homogenization/LatentCodes/latest.pth
new file mode 100644
index 00000000..cbedaf71
Binary files /dev/null and b/DeepSDFStruct/trained_models/test_experiment_homogenization/LatentCodes/latest.pth differ
diff --git a/DeepSDFStruct/trained_models/test_experiment_homogenization/Logs.png b/DeepSDFStruct/trained_models/test_experiment_homogenization/Logs.png
new file mode 100644
index 00000000..e4c9cfb6
Binary files /dev/null and b/DeepSDFStruct/trained_models/test_experiment_homogenization/Logs.png differ
diff --git a/DeepSDFStruct/trained_models/test_experiment_homogenization/ModelParameters/latest.pth b/DeepSDFStruct/trained_models/test_experiment_homogenization/ModelParameters/latest.pth
new file mode 100644
index 00000000..b247e76a
Binary files /dev/null and b/DeepSDFStruct/trained_models/test_experiment_homogenization/ModelParameters/latest.pth differ
diff --git a/DeepSDFStruct/trained_models/test_experiment_homogenization/OptimizerParameters/latest.pth b/DeepSDFStruct/trained_models/test_experiment_homogenization/OptimizerParameters/latest.pth
new file mode 100644
index 00000000..c69017ae
Binary files /dev/null and b/DeepSDFStruct/trained_models/test_experiment_homogenization/OptimizerParameters/latest.pth differ
diff --git a/DeepSDFStruct/trained_models/test_experiment_homogenization/specs.json b/DeepSDFStruct/trained_models/test_experiment_homogenization/specs.json
new file mode 100644
index 00000000..180f55b6
--- /dev/null
+++ b/DeepSDFStruct/trained_models/test_experiment_homogenization/specs.json
@@ -0,0 +1,83 @@
+{
+  "Description": "This experiment is intented for testing purposes only.",
+  "NetworkArch": "deep_sdf_decoder",
+  "TrainSplit": "splits/splines_v2_small.json",
+  "TestSplit": "splits/splines_v2_small.json",
+  "ReconstructionSplit": "",
+  "NetworkSpecs": {
+    "dims": [
+      32,
+      32,
+      32,
+      32,
+      32,
+      32
+    ],
+    "dropout": [
+      0,
+      1,
+      2,
+      3,
+      4,
+      5,
+      6,
+      7
+    ],
+    "dropout_prob": 0.2,
+    "norm_layers": [
+      0,
+      1,
+      2,
+      3,
+      4,
+      5,
+      6,
+      7
+    ],
+    "latent_in": [
+      2
+    ],
+    "xyz_in_all": false,
+    "use_tanh": false,
+    "latent_dropout": false,
+    "weight_norm": true,
+    "geom_dimension": 3,
+    "homogen_predictor_dims": [
+      64,
+      64,
+      64,
+      64,
+      9
+    ]
+  },
+  "CodeLength": 10,
+  "NumEpochs": 5,
+  "LogFrequency": 5,
+  "SnapshotFrequency": 100,
+  "AdditionalSnapshots": [
+    1,
+    5
+  ],
+  "LearningRateSchedule": [
+    {
+      "Type": "Step",
+      "Initial": 0.0005,
+      "Interval": 500,
+      "Factor": 0.5
+    },
+    {
+      "Type": "Step",
+      "Initial": 0.001,
+      "Interval": 500,
+      "Factor": 0.5
+    }
+  ],
+  "SamplesPerScene": 4,
+  "ScenesPerBatch": 2,
+  "DataLoaderThreads": 1,
+  "ClampingDistance": 0.1,
+  "CodeRegularization": true,
+  "AddHomogenization": true,
+  "CodeRegularizationLambda": 1e-4,
+  "CodeBound": 1.0
+}
\ No newline at end of file
diff --git a/DeepSDFStruct/trained_models/test_experiment_homogenization/training_summary.json b/DeepSDFStruct/trained_models/test_experiment_homogenization/training_summary.json
new file mode 100644
index 00000000..8cb8e874
--- /dev/null
+++ b/DeepSDFStruct/trained_models/test_experiment_homogenization/training_summary.json
@@ -0,0 +1,10 @@
+{
+    "loss": 9775.975620117188,
+    "num_epochs": 5,
+    "timestamp": "2026-05-21 17:39:48",
+    "host_name": "neptune",
+    "device": "cpu",
+    "training_duration": "0:00:28",
+    "data_dir": "/storage/mkofler/dissertation/data/",
+    "version": "1.7.1.dev40+g989384bd4.d20260330"
+}
\ No newline at end of file
diff --git a/tests/test_DOE.py b/tests/test_DOE.py
index 1d5a909c..6769a853 100644
--- a/tests/test_DOE.py
+++ b/tests/test_DOE.py
@@ -1,9 +1,29 @@
 from DeepSDFStruct.design_of_experiments import run_experiment, ExperimentSpecifications
 from huggingface_hub import snapshot_download
+from huggingface_hub.utils import HfHubHTTPError
+import time
+
+
+def snapshot_download_with_retry(*args, max_retries=3, **kwargs):
+    """Download with retry on 429 rate limit errors."""
+    for attempt in range(max_retries):
+        try:
+            return snapshot_download(*args, **kwargs)
+        except HfHubHTTPError as e:
+            if e.response and e.response.status_code == 429:
+                if attempt < max_retries - 1:
+                    wait_time = 60 * (attempt + 1)
+                    print(
+                        f"Rate limited (429). Waiting {wait_time}s before retry {attempt + 2}/{max_retries}"
+                    )
+                    time.sleep(wait_time)
+                else:
+                    raise
+            raise
 
 
 def test_DOE():
-    data_dir = snapshot_download(
+    data_dir = snapshot_download_with_retry(
         "mkofler/lattice_structure_unit_cells",
         repo_type="dataset",
         revision="b80339abc071df77ff81e8abc19ad4856d96ddbd",
diff --git a/tests/test_generate_dataset.py b/tests/test_generate_dataset.py
index 688610bc..bc993ac5 100644
--- a/tests/test_generate_dataset.py
+++ b/tests/test_generate_dataset.py
@@ -29,7 +29,7 @@ def test_generate_dataset_from_obj_files():
         sampling_strategy="uniform",
         add_surface_samples=True,
         also_save_vtk=True,
-        n_samples=1000,
+        n_samples=10,
     )
 
     sdf_sampler.write_json("chairs_train.json")
@@ -61,11 +61,11 @@ def test_generate_dataset(n_workers, tmp_path):
             tile, _ = chi.create_tile(np.array([[phi, t, x1, x2, r]] * 5))
             chi_tiles.append(splinepy.Multipatch(tile))
 
-    sdf_sampler.add_class(chi_tiles, class_name="Chi3D_center", n_faces=100)
-    sdf_sampler.add_class(crosslattice_tiles, class_name="CrossLattice", n_faces=100)
+    sdf_sampler.add_class(chi_tiles, class_name="Chi3D_center", n_faces=3)
+    sdf_sampler.add_class(crosslattice_tiles, class_name="CrossLattice", n_faces=3)
 
     sdf_sampler.process_geometries(
-        sampling_strategy="uniform", n_workers=n_workers, n_samples=1000
+        sampling_strategy="uniform", n_workers=n_workers, n_samples=10
     )
 
     sdf_sampler.write_json("chi_and_cross.json")
diff --git a/tests/test_mesh_export.py b/tests/test_mesh_export.py
index c2efd2bd..6c234242 100644
--- a/tests/test_mesh_export.py
+++ b/tests/test_mesh_export.py
@@ -53,7 +53,7 @@ def test_deepsdf_lattice_export_3D():
     )
     surf_mesh, derivative = create_3D_mesh(
         lattice_struct,
-        30,
+        10,
         differentiate=True,
         mesh_type="surface",
         device=model.device,
@@ -72,7 +72,7 @@ def test_deepsdf_lattice_export_3D():
 
     # test other method to export 3D mesh:
     volume_mesh, derivative_vols = create_3D_mesh(
-        lattice_struct, 30, differentiate=True, mesh_type="volume", device=model.device
+        lattice_struct, 10, differentiate=True, mesh_type="volume", device=model.device
     )
     _gus.io.meshio.export(
         fname="tests/tmp_outputs/volumes.inp", mesh=volume_mesh.to_gus()
@@ -106,7 +106,7 @@ def test_deepsdf_lattice_export_2D():
 
     surf_mesh, derivative = create_2D_mesh(
         lattice_struct,
-        30,
+        10,
         differentiate=True,
         mesh_type="surface",
         device=model.device,
@@ -122,11 +122,11 @@ def test_2D_mesh_export():
     linemesh.vertices = linemesh.vertices[:, :2]
 
     sdf_from_linemesh = SDFfromLineMesh(linemesh, thickness=0.5)
-    mesh = generate_2D_surf_mesh(sdf_from_linemesh, 300)
+    mesh = generate_2D_surf_mesh(sdf_from_linemesh, 100)
     _gus.io.meshio.export("tests/tmp_outputs/triangles.inp", mesh)
 
     sdf_from_linemesh = SDFfromLineMesh(linemesh, thickness=0.5, smoothness=0.1)
-    mesh = generate_2D_surf_mesh(sdf_from_linemesh, 300)
+    mesh = generate_2D_surf_mesh(sdf_from_linemesh, 100)
     _gus.io.meshio.export("tests/tmp_outputs/triangles_smooth.inp", mesh)
 
 
diff --git a/tests/test_sdf_functions.py b/tests/test_sdf_functions.py
index daff94d9..6ddc7511 100644
--- a/tests/test_sdf_functions.py
+++ b/tests/test_sdf_functions.py
@@ -19,7 +19,7 @@ def test_sdf_from_multipatch_cubes_equivalence():
 
     multipatch = splinepy.Multipatch([cube1, cube2])
 
-    n = 30
+    n = 10
     xs = torch.linspace(-0.5, 2.5, n)
     ys = torch.linspace(-0.5, 1.5, n)
     zs = torch.linspace(-0.5, 1.5, n)
@@ -28,8 +28,8 @@ def test_sdf_from_multipatch_cubes_equivalence():
         -1, 3
     )
 
-    multipatch_sdf = SDFfromMesh(multipatch.extract.faces(30))
-    big_cube_sdf = SDFfromMesh(big_cube.extract.faces(30))
+    multipatch_sdf = SDFfromMesh(multipatch.extract.faces(10))
+    big_cube_sdf = SDFfromMesh(big_cube.extract.faces(10))
 
     vals_multipatch = multipatch_sdf(queries)
     vals_big_cube = big_cube_sdf(queries)
@@ -44,7 +44,7 @@ def test_sdf_from_multipatch_cubes_equivalence():
 
 
 def test_cap_border_dict():
-    n = 21
+    n = 11
     xs = torch.linspace(-1.0, 1.0, n)
     ys = torch.linspace(-1.0, 1.0, n)
     zs = torch.linspace(-1.0, 1.0, n)
@@ -76,7 +76,7 @@ def test_cap_border_dict():
         print(cap_border_dict)
         capped_sdf_vals = capped_sdf(queries)
         export_sdf_grid_vtk(capped_sdf, f"tests/tmp_outputs/sdf_{name}.vtk")
-        surf_mesh, _ = create_3D_mesh(capped_sdf, 51, mesh_type="surface")
+        surf_mesh, _ = create_3D_mesh(capped_sdf, 11, mesh_type="surface")
         export_surface_mesh(f"tests/tmp_outputs/sdf_{name}.obj", surf_mesh.to_gus())
         export_surface_mesh(f"tests/tmp_outputs/sdf_{name}.stl", surf_mesh.to_gus())
         interior_low = caps[0] + measure
diff --git a/tests/test_structural_optimization.py b/tests/test_structural_optimization.py
index b6aa7bea..1a317c41 100644
--- a/tests/test_structural_optimization.py
+++ b/tests/test_structural_optimization.py
@@ -73,7 +73,7 @@ def test_structural_optimization(num_iter=1):
         torch.set_default_dtype(torch.float32)
         mesh, _ = create_3D_mesh(
             lattice_struct,
-            30,
+            10,
             mesh_type="volume",
             differentiate=False,
             device=model.device,
@@ -81,7 +81,7 @@ def test_structural_optimization(num_iter=1):
         )
         surf_mesh, _ = create_3D_mesh(
             lattice_struct,
-            30,
+            10,
             mesh_type="surface",
             differentiate=False,
             device=model.device,
@@ -110,7 +110,10 @@ def test_structural_optimization(num_iter=1):
             init_vol = vols.sum().item()
             logger.info(f"Initial volume: {init_vol} on {len(vols)} elements.")
         eps = 1e-12
-        mask = vols > eps
+        # Use float64 for the mask to match torchfem's internal precision;
+        # tets with tiny float32-positive volumes can become negative in float64.
+        vols_f64 = tet_signed_vol(verts.to(torch.float64), tets_oriented)
+        mask = vols_f64 > eps
         vol = vols[mask].sum()
 
         # keep only the good tets
@@ -155,6 +158,9 @@ def test_structural_optimization(num_iter=1):
         dG = torch.autograd.grad(G, param, retain_graph=True)[0]
         optimizer.step(F, dF, G, dG)
 
+        # Reset default dtype to float32 for other tests
+        torch.set_default_dtype(torch.float32)
+
     # torch.autograd.grad(compliance, cantilever.thickness)[0]
     mesh = get_mesh_from_torchfem(cantilever)
     mesh.point_data["u"] = u.detach().cpu().numpy()
diff --git a/tests/test_train_model.py b/tests/test_train_model.py
index 505ce2a9..06e76f55 100644
--- a/tests/test_train_model.py
+++ b/tests/test_train_model.py
@@ -5,45 +5,74 @@
 )
 from DeepSDFStruct.pretrained_models import get_model
 from huggingface_hub import snapshot_download
+from huggingface_hub.utils import HfHubHTTPError
+import pytest
 import torch
+import time
+
+REVISION = "dbe58ebaa00057d5f15096c2b253c7efa91e19d3"
+
+
+def snapshot_download_with_retry(*args, max_retries=3, **kwargs):
+    """Download with retry on 429 rate limit errors."""
+    for attempt in range(max_retries):
+        try:
+            return snapshot_download(*args, **kwargs)
+        except HfHubHTTPError as e:
+            if e.response and e.response.status_code == 429:
+                if attempt < max_retries - 1:
+                    wait_time = 60 * (attempt + 1)
+                    print(
+                        f"Rate limited (429). Waiting {wait_time}s before retry {attempt + 2}/{max_retries}"
+                    )
+                    time.sleep(wait_time)
+                else:
+                    raise
+            raise
+
+
+@pytest.fixture(scope="module", autouse=True)
+def set_float32_dtype():
+    torch.set_default_dtype(torch.float32)
+    torch.set_default_device("cpu")
+    yield
 
 
-def test_train_hierarchical_model():
-    data_dir = snapshot_download(
+@pytest.fixture(scope="module")
+def data_dir():
+    return snapshot_download_with_retry(
         "mkofler/lattice_structure_unit_cells",
         repo_type="dataset",
-        revision="b80339abc071df77ff81e8abc19ad4856d96ddbd",
+        revision=REVISION,
+        ignore_patterns=["*.stl", "**/*.stl"],
     )
+
+
+def test_train_homogenization_model(data_dir):
+    exp_dir = "DeepSDFStruct/trained_models/test_experiment_homogenization"
+
+    device = "cpu"
+    train_deep_sdf(exp_dir, data_dir, device=device)
+
+
+def test_train_hierarchical_model(data_dir):
     exp_dir = "DeepSDFStruct/trained_models/test_experiment_hierarchical"
 
     device = "cpu"
-    torch.set_default_device("cpu")
     train_deep_sdf(exp_dir, data_dir, device=device)
 
 
-def test_train_model():
-    data_dir = snapshot_download(
-        "mkofler/lattice_structure_unit_cells",
-        repo_type="dataset",
-        revision="b80339abc071df77ff81e8abc19ad4856d96ddbd",
-    )
+def test_train_model(data_dir):
     exp_dir = "DeepSDFStruct/trained_models/test_experiment"
 
     device = "cpu"
-    torch.set_default_device("cpu")
     train_deep_sdf(exp_dir, data_dir, device=device)
 
 
-def test_continue_from():
-    data_dir = snapshot_download(
-        "mkofler/lattice_structure_unit_cells",
-        repo_type="dataset",
-        revision="b80339abc071df77ff81e8abc19ad4856d96ddbd",
-    )
+def test_continue_from(data_dir):
     exp_dir = "DeepSDFStruct/trained_models/test_experiment"
 
     device = "cpu"
-    torch.set_default_device("cpu")
     train_deep_sdf(exp_dir, data_dir, device=device, continue_from="1")
 
 
@@ -65,8 +94,17 @@ def test_cpp_file_export():
     import warnings
 
     warnings.filterwarnings("error")
-    test_train_hierarchical_model()
-    test_train_model()
-    test_continue_from()
+    torch.set_default_dtype(torch.float32)
+    torch.set_default_device("cpu")
+    data_dir = snapshot_download_with_retry(
+        "mkofler/lattice_structure_unit_cells",
+        repo_type="dataset",
+        revision=REVISION,
+        ignore_patterns=["*.stl", "**/*.stl"],
+    )
+    test_train_homogenization_model(data_dir)
+    test_train_hierarchical_model(data_dir)
+    test_train_model(data_dir)
+    test_continue_from(data_dir)
     test_latent_recon()
     test_cpp_file_export()