add initial pass at arg_constraints and arg validation. (#123)

torch_struct/distributions.py

@@ -1,4 +1,5 @@
 import torch
+from torch.distributions import constraints
 from torch.distributions.distribution import Distribution
 from torch.distributions.utils import lazy_property
 from .linearchain import LinearChain
@@ -36,15 +37,18 @@ class StructDistribution(Distribution):
         log_potentials (tensor, batch_shape x event_shape) :  log-potentials :math:`\phi`
         lengths (long tensor, batch_shape) : integers for length masking
     """
-    validate_args = False
+    arg_constraints = {
+        "log_potentials": constraints.real,
+        "lengths": constraints.nonnegative_integer
+    }
 
-    def __init__(self, log_potentials, lengths=None, args={}):
+    def __init__(self, log_potentials, lengths=None, args={}, validate_args=False):
         batch_shape = log_potentials.shape[:1]
         event_shape = log_potentials.shape[1:]
         self.log_potentials = log_potentials
         self.lengths = lengths
         self.args = args
-        super().__init__(batch_shape=batch_shape, event_shape=event_shape)
+        super().__init__(batch_shape=batch_shape, event_shape=event_shape, validate_args=validate_args)
 
     def _new(self, *args, **kwargs):
         return self._param.new(*args, **kwargs)
@@ -295,11 +299,17 @@ class AlignmentCRF(StructDistribution):
 
     """
     struct = Alignment
-
-    def __init__(self, log_potentials, local=False, lengths=None, max_gap=None):
+    arg_constraints = {
+        "log_potentials": constraints.real,
+        "local": constraints.boolean,
+        "max_gap": constraints.nonnegative_integer,
+        "lengths": constraints.nonnegative_integer
+    }
+
+    def __init__(self, log_potentials, local=False, lengths=None, max_gap=None, validate_args=False):
         self.local = local
         self.max_gap = max_gap
-        super().__init__(log_potentials, lengths)
+        super().__init__(log_potentials, lengths, validate_args=validate_args)
 
     def _struct(self, sr=None):
         return self.struct(
@@ -324,9 +334,9 @@ class HMM(StructDistribution):
     Implemented as a special case of linear chain CRF.
     """
 
-    def __init__(self, transition, emission, init, observations, lengths=None):
+    def __init__(self, transition, emission, init, observations, lengths=None, validate_args=False):
         log_potentials = HMM.struct.hmm(transition, emission, init, observations)
-        super().__init__(log_potentials, lengths)
+        super().__init__(log_potentials, lengths, validate_args=validate_args)
 
     struct = LinearChain
 
@@ -380,8 +390,8 @@ class DependencyCRF(StructDistribution):
 
     """
 
-    def __init__(self, log_potentials, lengths=None, args={}, multiroot=True):
-        super(DependencyCRF, self).__init__(log_potentials, lengths, args)
+    def __init__(self, log_potentials, lengths=None, args={}, multiroot=True, validate_args=False):
+        super(DependencyCRF, self).__init__(log_potentials, lengths, args, validate_args=validate_args)
         self.struct = DepTree
         setattr(self.struct, "multiroot", multiroot)
 
@@ -436,13 +446,13 @@ class SentCFG(StructDistribution):
 
     struct = CKY
 
-    def __init__(self, log_potentials, lengths=None):
+    def __init__(self, log_potentials, lengths=None, validate_args=False):
         batch_shape = log_potentials[0].shape[:1]
         event_shape = log_potentials[0].shape[1:]
         self.log_potentials = log_potentials
         self.lengths = lengths
         super(StructDistribution, self).__init__(
-            batch_shape=batch_shape, event_shape=event_shape
+            batch_shape=batch_shape, event_shape=event_shape, validate_args=validate_args
         )
 
 
@@ -468,8 +478,12 @@ class NonProjectiveDependencyCRF(StructDistribution):
 
     """
 
-    def __init__(self, log_potentials, lengths=None, args={}, multiroot=False):
-        super(NonProjectiveDependencyCRF, self).__init__(log_potentials, lengths, args)
+    arg_constraints = {
+        "log_potentials": constraints.real
+    }
+
+    def __init__(self, log_potentials, lengths=None, args={}, multiroot=False, validate_args=False):
+        super(NonProjectiveDependencyCRF, self).__init__(log_potentials, lengths, args, validate_args=validate_args)
         self.multiroot = multiroot
 
     @lazy_property