Merge pull request #149 from GFNOrg/no_more_class_factories

No more class factories

docs/requirements_docs.txt

@@ -1,9 +1,9 @@
 pre-commit
 black
 pytest
-sphinx==5.3.0
-myst-parser==0.18.1
-sphinx_rtd_theme==1.1.1
-sphinx-math-dollar==1.2.1
-sphinx-autoapi==2.0.0
+sphinx>=6.2.1
+myst-parser
+sphinx_rtd_theme
+sphinx-math-dollar
+sphinx-autoapi>=3.0.0
 renku-sphinx-theme

pyproject.toml

@@ -33,9 +33,9 @@ myst-parser = { version = "*", optional = true }
 pre-commit = { version = "*", optional = true }
 pytest = { version = "*", optional = true }
 renku-sphinx-theme = { version = "*", optional = true }
-sphinx = { version = "*", optional = true }
+sphinx = { version = ">=6.2.1", optional = true }
 sphinx_rtd_theme = { version = "*", optional = true }
-sphinx-autoapi = { version = "*", optional = true }
+sphinx-autoapi = { version = ">=3.0.0", optional = true }
 sphinx-math-dollar = { version = "*", optional = true }
 tox = { version = "*", optional = true }
 
@@ -85,8 +85,6 @@ all = [
 "Homepage" = "https://gfn.readthedocs.io/en/latest/"
 "Bug Tracker" = "https://github.com/saleml/gfn/issues"
 
-
-
 [tool.black]
 py36 = true
 include = '\.pyi?$'

src/gfn/containers/replay_buffer.py

@@ -46,8 +46,8 @@ def __init__(
             self.training_objects = Transitions(env)
             self.objects_type = "transitions"
         elif objects_type == "states":
-            self.training_objects = env.States.from_batch_shape((0,))
-            self.terminating_states = env.States.from_batch_shape((0,))
+            self.training_objects = env.states_from_batch_shape((0,))
+            self.terminating_states = env.states_from_batch_shape((0,))
             self.objects_type = "states"
         else:
             raise ValueError(f"Unknown objects_type: {objects_type}")

src/gfn/containers/trajectories.py

@@ -79,13 +79,11 @@ def __init__(
         self.states = (
             states
             if states is not None
-            else env.States.from_batch_shape(batch_shape=(0, 0))
+            else env.states_from_batch_shape((0, 0))
         )
         assert len(self.states.batch_shape) == 2
         self.actions = (
-            actions
-            if actions is not None
-            else env.Actions.make_dummy_actions(batch_shape=(0, 0))
+            actions if actions is not None else env.actions_from_batch_shape((0, 0))
         )
         assert len(self.actions.batch_shape) == 2
         self.when_is_done = (
@@ -253,9 +251,13 @@ def extend(self, other: Trajectories) -> None:
 
         # Either set, or append, estimator outputs if they exist in the submitted
         # trajectory.
-        if self.estimator_outputs is None and is_tensor(other.estimator_outputs):
+        if self.estimator_outputs is None and isinstance(
+            other.estimator_outputs, Tensor
+        ):
             self.estimator_outputs = other.estimator_outputs
-        elif is_tensor(self.estimator_outputs) and is_tensor(other.estimator_outputs):
+        elif isinstance(self.estimator_outputs, Tensor) and isinstance(
+            other.estimator_outputs, Tensor
+        ):
             batch_shape = self.actions.batch_shape
             n_bs = len(batch_shape)
             output_dtype = self.estimator_outputs.dtype

src/gfn/containers/transitions.py

@@ -68,14 +68,12 @@ def __init__(
         self.states = (
             states
             if states is not None
-            else env.States.from_batch_shape(batch_shape=(0,))
+            else env.states_from_batch_shape(batch_shape=(0,))
         )
         assert len(self.states.batch_shape) == 1
 
         self.actions = (
-            actions
-            if actions is not None
-            else env.Actions.make_dummy_actions(batch_shape=(0,))
+            actions if actions is not None else env.actions_from_batch_shape((0,))
         )
         self.is_done = (
             is_done
@@ -85,7 +83,7 @@ def __init__(
         self.next_states = (
             next_states
             if next_states is not None
-            else env.States.from_batch_shape(batch_shape=(0,))
+            else env.states_from_batch_shape(batch_shape=(0,))
         )
         assert (
             len(self.next_states.batch_shape) == 1