Merge branch 'main' into repo_status

README.md

@@ -36,6 +36,14 @@ The best way to install `plenoptic` is via `pip`.
 $ pip install plenoptic
 ```
 
+Our dependencies include [pytorch](https://pytorch.org/) and
+[pyrtools](https://pyrtools.readthedocs.io/en/latest/). Installation should take
+care of them (along with our other dependencies) automatically, but if you have
+an installation problem (especially on a non-Linux operating system), it is
+likely that the problem lies with one of those packages. [Open an
+issue](https://github.com/LabForComputationalVision/plenoptic/issues) and we'll
+try to help you figure out the problem!
+
 See the [installation
 page](https://plenoptic.readthedocs.io/en/latest/install.html) for more details,
 including how to set up a virtual environment and jupyter.

docs/install.rst

@@ -11,6 +11,8 @@ $ conda create --name plenoptic pip python=3.9
 $ conda activate plenoptic
 $ pip install plenoptic
 
+Our dependencies include `pytorch <https://pytorch.org/>`_ and `pyrtools <https://pyrtools.readthedocs.io/en/latest/>`_. Installation should take care of them (along with our other dependencies) automatically, but if you have an installation problem (especially on a non-Linux operating system), it is likely that the problem lies with one of those packages. `Open an issue <https://github.com/LabForComputationalVision/plenoptic/issues>`_ and we'll try to help you figure out the problem!
+
 You can also install it directly from source to have a local editable copy. This is most useful for developing (for more info, see `our contributing guide <https://github.com/LabForComputationalVision/plenoptic/blob/main/CONTRIBUTING.md>`_) or if you want to use the most cutting-edge version::
 
 $ conda create --name plenoptic pip python=3.9

tests/test_geodesic.py

@@ -303,4 +303,5 @@ def test_stop_criterion(self, einstein_small_seq, model):
         moog = po.synth.Geodesic(einstein_small_seq[:1], einstein_small_seq[-1:],
                                  model, 5)
         moog.synthesize(max_iter=10, stop_criterion=.06, stop_iters_to_check=1)
-        assert len(moog.pixel_change_norm) == 6, "Didn't stop when hit criterion! (or optimization changed)"
+        assert (abs(moog.pixel_change_norm[-1:]) < .06).all(), "Didn't stop when hit criterion!"
+        assert (abs(moog.pixel_change_norm[:-1]) > .06).all(), "Stopped after hit criterion!"

tests/test_mad.py

@@ -207,4 +207,5 @@ def test_stop_criterion(self, einstein_img):
         po.tools.set_seed(0)
         mad = po.synth.MADCompetition(einstein_img, po.metric.mse, dis_ssim, 'min')
         mad.synthesize(max_iter=15, stop_criterion=1e-3, stop_iters_to_check=5)
-        assert len(mad.losses) == 12, "Didn't stop when hit criterion! (or optimization changed)"
+        assert abs(mad.losses[-5]-mad.losses[-1]) < 1e-3, "Didn't stop when hit criterion!"
+        assert abs(mad.losses[-6]-mad.losses[-2]) > 1e-3, "Stopped after hit criterion!"

tests/test_metamers.py

@@ -225,11 +225,6 @@ def test_stop_criterion(self, einstein_img, model):
         po.tools.set_seed(0)
         met = po.synth.Metamer(einstein_img, model)
         # takes different numbers of iter to converge on GPU and CPU
-        if DEVICE.type == 'cuda':
-            max_iter = 30
-            check_iter = 25
-        else:
-            max_iter = 10
-            check_iter = 8
-        met.synthesize(max_iter=max_iter, stop_criterion=1e-5, stop_iters_to_check=5)
-        assert len(met.losses) == check_iter, "Didn't stop when hit criterion! (or optimization changed)"
+        met.synthesize(max_iter=30, stop_criterion=1e-5, stop_iters_to_check=5)
+        assert abs(met.losses[-5]-met.losses[-1]) < 1e-5, "Didn't stop when hit criterion!"
+        assert abs(met.losses[-6]-met.losses[-2]) > 1e-5, "Stopped after hit criterion!"