Fix gumbel cdf (#91698)

Fix `Gumbel.cdf` function.

**Description**
When transformed parameters is outside of the support of underlying Uniform distribution. This makes behavior of `Gumbel.cdf` consistent with other `TransformedDistribution` that pass value of validate_args to the base distribution.

**Issue**
running `Gumbel(0.0,1.0,validate_args=False).cdf(20.0)` would cause `ValueError` exception from `_validate_sample`

**Testing**
Test was added to the `test_distributions.py` to check if `Gumbel(0.0,1.0,validate_args=False).cdf(20.0)` successfully returns `1.0`

This is a second attempt to push changes , after pytorch/pytorch#82488

Pull Request resolved: pytorch/pytorch#91698
Approved by: https://github.com/fritzo, https://github.com/zou3519

test/distributions/test_distributions.py

@@ -2589,6 +2589,18 @@ def test_gumbel(self):
         self.assertEqual(Gumbel(loc_1d, scale_1d).sample((1,)).size(), (1, 1))
         self.assertEqual(Gumbel(1.0, 1.0).sample().size(), ())
         self.assertEqual(Gumbel(1.0, 1.0).sample((1,)).size(), (1,))
+        self.assertEqual(Gumbel(torch.tensor(0.0, dtype=torch.float32),
+                                torch.tensor(1.0, dtype=torch.float32),
+                                validate_args=False).cdf(20.0), 1.0, atol=1e-4, rtol=0)
+        self.assertEqual(Gumbel(torch.tensor(0.0, dtype=torch.float64),
+                                torch.tensor(1.0, dtype=torch.float64),
+                                validate_args=False).cdf(50.0), 1.0, atol=1e-4, rtol=0)
+        self.assertEqual(Gumbel(torch.tensor(0.0, dtype=torch.float32),
+                                torch.tensor(1.0, dtype=torch.float32),
+                                validate_args=False).cdf(-5.0), 0.0, atol=1e-4, rtol=0)
+        self.assertEqual(Gumbel(torch.tensor(0.0, dtype=torch.float64),
+                                torch.tensor(1.0, dtype=torch.float64),
+                                validate_args=False).cdf(-10.0), 0.0, atol=1e-8, rtol=0)
 
         def ref_log_prob(idx, x, log_prob):
             l = loc.view(-1)[idx].detach()

torch/distributions/gumbel.py

@@ -31,10 +31,11 @@ def __init__(self, loc, scale, validate_args=None):
         self.loc, self.scale = broadcast_all(loc, scale)
         finfo = torch.finfo(self.loc.dtype)
         if isinstance(loc, Number) and isinstance(scale, Number):
-            base_dist = Uniform(finfo.tiny, 1 - finfo.eps)
+            base_dist = Uniform(finfo.tiny, 1 - finfo.eps, validate_args=validate_args)
         else:
             base_dist = Uniform(torch.full_like(self.loc, finfo.tiny),
-                                torch.full_like(self.loc, 1 - finfo.eps))
+                                torch.full_like(self.loc, 1 - finfo.eps),
+                                validate_args=validate_args)
         transforms = [ExpTransform().inv, AffineTransform(loc=0, scale=-torch.ones_like(self.scale)),
                       ExpTransform().inv, AffineTransform(loc=loc, scale=-self.scale)]
         super().__init__(base_dist, transforms, validate_args=validate_args)