Some spelling corrections in doc strings (pyro-ppl#521)

Author: brettkoonce

pyro/distributions/dirichlet.py

@@ -75,7 +75,7 @@ def sample(self):
 
     def batch_log_pdf(self, x):
         """
-        Evaluates log probabity density over one or a batch of samples.
+        Evaluates log probability density over one or a batch of samples.
 
         Each of alpha and x can be either a single value or a batch of values batched along dimension 0.
         If they are both batches, their batch sizes must agree.

pyro/distributions/distribution.py

@@ -118,7 +118,7 @@ def event_shape(self, x=None, *args, **kwargs):
         """
         The right-hand tensor shape of samples, used for individual events. The
         event dimension(/s) is used to designate random variables that could
-        potentially depend on each other, for instance in the case of dirichlet
+        potentially depend on each other, for instance in the case of Dirichlet
         or the categorical distribution, but could also simply be used for logical
         grouping, for example in the case of a normal distribution with a
         diagonal covariance matrix.

pyro/distributions/poisson.py

@@ -10,7 +10,7 @@
 
 class Poisson(Distribution):
     """
-    Poisson distribution over integers parameterizeds by scale `lambda`.
+    Poisson distribution over integers parameterized by scale `lambda`.
 
     This is often used in conjunction with `torch.nn.Softplus` to ensure the
     `lam` parameter is positive.

pyro/distributions/util.py

@@ -91,7 +91,7 @@ def torch_eye(n, m=None, out=None):
     try:
         return torch.eye(n, m, out=out)
     except TypeError:
-        # Only catch errors due to torch.eye() not being availble for cuda tensors.
+        # Only catch errors due to torch.eye() not being available for cuda tensors.
         module = torch.Tensor.__module__ if out is None else type(out).__module__
         if module != 'torch.cuda':
             raise

pyro/infer/search.py

@@ -29,7 +29,7 @@ def _traces(self, *args, **kwargs):
         is performing exact inference
 
         :returns: Iterator of traces from the posterior.
-        :rtype: Geneator[:class:`pyro.Trace`]
+        :rtype: Generator[:class:`pyro.Trace`]
         """
         # currently only using the standard library queue
         self.queue = Queue()

pyro/nn/auto_reg_nn.py

@@ -47,15 +47,15 @@ class AutoRegressiveNN(nn.Module):
     :type hidden_dim: int
     :param output_dim_multiplier: the dimensionality of the output is given by input_dim x output_dim_multiplier.
         specifically the shape of the output for a single vector input is [output_dim_multiplier, input_dim].
-        for any i, j in range(0, output_dim_multiplier) the subset of outputs [i, :] has identifical
+        for any i, j in range(0, output_dim_multiplier) the subset of outputs [i, :] has identical
         autoregressive structure to [j, :]. defaults to `1`
     :type output_dim_multiplier: int
     :param mask_encoding: a torch Tensor that controls the autoregressive structure (see reference). by default
         this is chosen at random.
     :type mask_encoding: torch.LongTensor
     :param permutation: an optional permutation that is applied to the inputs and controls the order of the
         autoregressive factorization. in particular for the identity permutation the autoregressive structure
-        is such that the jacobian is upper triangular. by default this is chosen at random.
+        is such that the Jacobian is upper triangular. by default this is chosen at random.
     :type permutation: torch.LongTensor
     """
 

pyro/poutine/lift_poutine.py

@@ -29,7 +29,7 @@ def __init__(self, fn, prior):
 
     def _prepare_site(self, msg):
         """
-        Sets flags of params that will be overriden so they are not
+        Sets flags of params that will be overridden so they are not
         reexecuted in the stack and not added to the param store.
         """
         name = msg["name"]

pyro/poutine/poutine.py

@@ -98,7 +98,7 @@ def __exit__(self, exc_type, exc_value, traceback):
         They are all None unless the body of the with statement raised an exception.
         """
         if exc_type is None:  # callee or enclosed block returned successfully
-            # if the callee or enclosed block returned successfuly,
+            # if the callee or enclosed block returned successfully,
             # this poutine should be on the bottom of the stack.
             # If so, remove it from the stack.
             # if not, raise a ValueError because something really weird happened.

pyro/util.py

@@ -223,7 +223,7 @@ def enum_extend(trace, msg, num_samples=None):
     inside_iarange = any(frame.vectorized for frame in msg["map_data_stack"])
     if is_batched and not inside_iarange:
         raise ValueError(
-                "Tried to enumerate a batched pyro.sample site '{}' outiside of a pyro.iarange. "
+                "Tried to enumerate a batched pyro.sample site '{}' outside of a pyro.iarange. "
                 "To fix, either enclose in a pyro.iarange, or avoid batching.".format(msg["name"]))
 
     extended_traces = []
@@ -389,6 +389,6 @@ def check_model_guide_match(model_trace, guide_trace):
 def deep_getattr(obj, name):
     """
     Python getattr() for arbitrarily deep attributes
-    Throws an AttirbuteError if bad attribute
+    Throws an AttributeError if bad attribute
     """
     return functools.reduce(getattr, name.split("."), obj)