✅ Reduce run time for Mapde test (#627)

- Reduce run time for Mapde test.

tests/models/test_arch_mapde.py

@@ -2,17 +2,20 @@
 import numpy as np
 import torch
 
-from tiatoolbox import utils
 from tiatoolbox.models import MapDe
 from tiatoolbox.models.architecture import fetch_pretrained_weights
+from tiatoolbox.utils import env_detection as toolbox_env
+from tiatoolbox.utils.misc import select_device
 from tiatoolbox.wsicore.wsireader import WSIReader
 
+ON_GPU = toolbox_env.has_gpu()
+
 
 def _load_mapde(tmp_path, name):
     """Loads MapDe model with specified weights."""
     model = MapDe()
     fetch_pretrained_weights(name, f"{tmp_path}/weights.pth")
-    map_location = utils.misc.select_device(utils.env_detection.has_gpu())
+    map_location = select_device(ON_GPU)
     pretrained = torch.load(f"{tmp_path}/weights.pth", map_location=map_location)
     model.load_state_dict(pretrained)
 
@@ -34,14 +37,10 @@ def test_functionality(remote_sample, tmp_path):
         (0, 0, 252, 252), resolution=0.50, units="mpp", coord_space="resolution"
     )
 
-    model = _load_mapde(tmp_path=tmp_path, name="mapde-crchisto")
+    model = _load_mapde(tmp_path=tmp_path, name="mapde-conic")
     patch = model.preproc(patch)
     batch = torch.from_numpy(patch)[None]
-    output = model.infer_batch(model, batch, on_gpu=False)
-    output = model.postproc(output[0])
-    assert np.all(output[0:2] == [[99, 178], [64, 218]])
-
-    model = _load_mapde(tmp_path=tmp_path, name="mapde-conic")
-    output = model.infer_batch(model, batch, on_gpu=False)
+    model = model.to(select_device(ON_GPU))
+    output = model.infer_batch(model, batch, on_gpu=ON_GPU)
     output = model.postproc(output[0])
     assert np.all(output[0:2] == [[19, 171], [53, 89]])