Fix ssim run on cuda 2532 (#2564)

* Remove unnecessary code in BaseOutputHandler

Closes #2438

* Add ReduceLROnPlateauScheduler

Closes #1754

* Fix indentation issue

* Fix another indentation issue

* Fix PEP8 related issues

* Fix other PEP8 related issues

* Fix hopefully the last PEP8 related issue

* Fix hopefully the last PEP8 related issue

* Remove ReduceLROnPlateau's specific params and add link to it

Also fix bug in min_lr check

* Fix state_dict bug and add a test

* Update docs

* Add doctest and fix typo

* fix bug to use on cuda

Co-authored-by: vfdev <vfdev.5@gmail.com>

ignite/metrics/ssim.py

@@ -98,7 +98,7 @@ def __init__(
 
     @reinit__is_reduced
     def reset(self) -> None:
-        self._sum_of_ssim = torch.tensor(0.0, device=self._device)
+        self._sum_of_ssim = torch.tensor(0.0, dtype=torch.float64, device=self._device)
         self._num_examples = 0
         self._kernel = self._gaussian_or_uniform_kernel(kernel_size=self.kernel_size, sigma=self.sigma)
 
@@ -180,7 +180,7 @@ def update(self, output: Sequence[torch.Tensor]) -> None:
         self._num_examples += y.shape[0]
 
     @sync_all_reduce("_sum_of_ssim", "_num_examples")
-    def compute(self) -> torch.Tensor:
+    def compute(self) -> float:
         if self._num_examples == 0:
             raise NotComputableError("SSIM must have at least one example before it can be computed.")
-        return self._sum_of_ssim / self._num_examples
+        return (self._sum_of_ssim / self._num_examples).item()

tests/ignite/metrics/test_ssim.py

@@ -96,10 +96,8 @@ def test_ssim(device, shape, kernel_size, gaussian, use_sample_covariance):
         use_sample_covariance=use_sample_covariance,
     )
 
-    assert isinstance(ignite_ssim, torch.Tensor)
-    assert ignite_ssim.dtype == torch.float64
-    assert ignite_ssim.device.type == torch.device(device).type
-    assert np.allclose(ignite_ssim.cpu().numpy(), skimg_ssim, atol=7e-5)
+    assert isinstance(ignite_ssim, float)
+    assert np.allclose(ignite_ssim, skimg_ssim, atol=7e-5)
 
 
 def test_ssim_variable_batchsize():
@@ -125,7 +123,7 @@ def test_ssim_variable_batchsize():
     ssim.reset()
     ssim.update((torch.cat(y_preds), torch.cat(y_true)))
     expected = ssim.compute()
-    assert torch.allclose(out, expected)
+    assert np.allclose(out, expected)
 
 
 def _test_distrib_integration(device, tol=1e-4):