[Feature] Make ProbabilisticTensorDictSequential account for more tha…

…n one distribution

ghstack-source-id: b62b81b5cfd49168b5875f7ba9b4f35b51cd2423
Pull Request resolved: #1114

tensordict/nn/distributions/composite.py

@@ -221,22 +221,6 @@ def from_distributions(
         self.inplace = inplace
         return self
 
-    @property
-    def aggregate_probabilities(self):
-        aggregate_probabilities = self._aggregate_probabilities
-        if aggregate_probabilities is None:
-            warnings.warn(
-                "The default value of `aggregate_probabilities` will change from `False` to `True` in v0.7. "
-                "Please pass this value explicitly to avoid this warning.",
-                FutureWarning,
-            )
-            aggregate_probabilities = self._aggregate_probabilities = False
-        return aggregate_probabilities
-
-    @aggregate_probabilities.setter
-    def aggregate_probabilities(self, value):
-        self._aggregate_probabilities = value
-
     def sample(self, shape=None) -> TensorDictBase:
         if shape is None:
             shape = torch.Size([])
@@ -337,7 +321,7 @@ def log_prob(
             aggregate_probabilities (bool, optional): if provided, overrides the default ``aggregate_probabilities``
                 from the class.
             include_sum (bool, optional): Whether to include the summed log-probability in the output TensorDict.
-                Defaults to ``self.inplace`` which is set through the class constructor (``True`` by default).
+                Defaults to ``self.include_sum`` which is set through the class constructor (``True`` by default).
                 Has no effect if ``aggregate_probabilities`` is set to ``True``.
 
                 .. warning:: The default value of ``include_sum`` will switch to ``False`` in v0.9 in the constructor.
@@ -356,6 +340,8 @@ def log_prob(
         """
         if aggregate_probabilities is None:
             aggregate_probabilities = self.aggregate_probabilities
+            if aggregate_probabilities is None:
+                aggregate_probabilities = False
         if not aggregate_probabilities:
             return self.log_prob_composite(
                 sample, include_sum=include_sum, inplace=inplace
@@ -382,7 +368,7 @@ def log_prob_composite(
 
         Keyword Args:
             include_sum (bool, optional): Whether to include the summed log-probability in the output TensorDict.
-                Defaults to ``self.inplace`` which is set through the class constructor (``True`` by default).
+                Defaults to ``self.include_sum`` which is set through the class constructor (``True`` by default).
 
                 .. warning:: The default value of ``include_sum`` will switch to ``False`` in v0.9 in the constructor.
 
@@ -451,7 +437,7 @@ def entropy(
                 setting from the class. Determines whether to return a single summed entropy tensor or a TensorDict
                 with individual entropies. Defaults to ``False`` if not set in the class.
             include_sum (bool, optional): Whether to include the summed entropy in the output TensorDict.
-                Defaults to `self.inplace`, which is set through the class constructor. Has no effect if
+                Defaults to `self.include_sum`, which is set through the class constructor. Has no effect if
                 `aggregate_probabilities` is set to `True`.
 
                 .. warning:: The default value of `include_sum` will switch to `False` in v0.9 in the constructor.
@@ -466,6 +452,8 @@ def entropy(
         """
         if aggregate_probabilities is None:
             aggregate_probabilities = self.aggregate_probabilities
+            if aggregate_probabilities is None:
+                aggregate_probabilities = False
         if not aggregate_probabilities:
             return self.entropy_composite(samples_mc, include_sum=include_sum)
         se = 0.0