[Docs] Add Description of validate_args for torch.distributions (#152173)

Fixes #152165

Pull Request resolved: https://github.com/pytorch/pytorch/pull/152173
Approved by: https://github.com/soulitzer

torch/distributions/bernoulli.py

@@ -36,6 +36,7 @@ class Bernoulli(ExponentialFamily):
     Args:
         probs (Number, Tensor): the probability of sampling `1`
         logits (Number, Tensor): the log-odds of sampling `1`
+        validate_args (bool, optional): whether to validate arguments, None by default
     """
 
     arg_constraints = {"probs": constraints.unit_interval, "logits": constraints.real}

torch/distributions/distribution.py

@@ -16,6 +16,11 @@ __all__ = ["Distribution"]
 class Distribution:
     r"""
     Distribution is the abstract base class for probability distributions.
+
+    Args:
+        batch_shape (torch.Size): The shape over which parameters are batched.
+        event_shape (torch.Size): The shape of a single sample (without batching).
+        validate_args (bool, optional): Whether to validate arguments. Default: None.
     """
 
     has_rsample = False

torch/distributions/weibull.py

@@ -28,6 +28,7 @@ class Weibull(TransformedDistribution):
     Args:
         scale (float or Tensor): Scale parameter of distribution (lambda).
         concentration (float or Tensor): Concentration parameter of distribution (k/shape).
+        validate_args (bool, optional): Whether to validate arguments. Default: None.
     """
 
     arg_constraints = {