[Feature] Env with tensorclass attributes

ghstack-source-id: a3b2a95
Pull Request resolved: #2788

Author: Vincent Moens

test/mocking_classes.py

@@ -10,11 +10,11 @@
 
 import torch
 import torch.nn as nn
-from tensordict import TensorDict, TensorDictBase
+from tensordict import tensorclass, TensorDict, TensorDictBase
 from tensordict.nn import TensorDictModuleBase
 from tensordict.utils import expand_right, NestedKey
 
-from torchrl.data.tensor_specs import (
+from torchrl.data import (
     Binary,
     Bounded,
     Categorical,
@@ -2356,3 +2356,42 @@ def _step(self, tensordict: TensorDictBase, **kwargs) -> TensorDict:
 
     def _set_seed(self, seed: Optional[int]):
         ...
+
+
+@tensorclass()
+class TC:
+    field0: str
+    field1: torch.Tensor
+
+
+class EnvWithTensorClass(CountingEnv):
+    tc_cls = TC
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.observation_spec["tc"] = Composite(
+            field0=NonTensor(example_data="an observation!", shape=self.batch_size),
+            field1=Unbounded(shape=self.batch_size),
+            shape=self.batch_size,
+            data_cls=TC,
+        )
+
+    def _reset(self, tensordict: TensorDictBase, **kwargs) -> TensorDictBase:
+        td = super()._reset(tensordict, **kwargs)
+        td["tc"] = TC("0", torch.zeros(self.batch_size))
+        return td
+
+    def _step(self, tensordict: TensorDictBase, **kwargs) -> TensorDictBase:
+        td = super()._step(tensordict, **kwargs)
+        default = TC("0", 0)
+        f0 = tensordict.get("tc", default).field0
+        if f0 is None:
+            f0 = "0"
+        f1 = tensordict.get("tc", default).field1
+        if f1 is None:
+            f1 = torch.zeros(self.batch_size)
+        td["tc"] = TC(
+            str(int(f0) + 1),
+            f1 + 1,
+        )
+        return td

test/test_env.py

@@ -127,6 +127,7 @@
         EnvThatDoesNothing,
         EnvWithDynamicSpec,
         EnvWithMetadata,
+        EnvWithTensorClass,
         HeterogeneousCountingEnv,
         HeterogeneousCountingEnvPolicy,
         MockBatchedLockedEnv,
@@ -166,6 +167,7 @@
         EnvThatDoesNothing,
         EnvWithDynamicSpec,
         EnvWithMetadata,
+        EnvWithTensorClass,
         HeterogeneousCountingEnv,
         HeterogeneousCountingEnvPolicy,
         MockBatchedLockedEnv,
@@ -3708,6 +3710,29 @@ def test_str2str_rb_slicesampler(self):
         else:
             raise RuntimeError("Failed to sample both trajs")
 
+    def test_env_with_tensorclass(self):
+        env = EnvWithTensorClass()
+        env.check_env_specs()
+        r = env.reset()
+        for _ in range(3):
+            assert isinstance(r["tc"], env.tc_cls)
+            a = env.rand_action(r)
+            s = env.step(a)
+            assert isinstance(s["tc"], env.tc_cls)
+            r = env.step_mdp(s)
+
+    @pytest.mark.parametrize("cls", [SerialEnv, ParallelEnv])
+    def test_env_with_tensorclass_batched(self, cls):
+        env = cls(2, EnvWithTensorClass)
+        env.check_env_specs()
+        r = env.reset()
+        for _ in range(3):
+            assert isinstance(r["tc"], EnvWithTensorClass.tc_cls)
+            a = env.rand_action(r)
+            s = env.step(a)
+            assert isinstance(s["tc"], EnvWithTensorClass.tc_cls)
+            r = env.step_mdp(s)
+
 
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