no cloned_cache

Author: Milotrince

genesis/sensors/base_sensor.py

@@ -29,6 +29,7 @@ def __init__(self, sensor_options: "SensorOptions", sensor_idx: int, sensor_mana
         self._read_delay_steps: int = 0
         self._shape_indices: list[tuple[int, int]] = []
         self._shared_metadata: dict[str, Any] | None = None
+        self._cache: "TensorRingBuffer" | None = None
 
     # =============================== implementable methods ===============================
 
@@ -91,10 +92,7 @@ def read(self, envs_idx: List[int] | None = None):
         """
         Read the sensor data (with noise applied if applicable).
         """
-        return self._get_formatted_data(
-            self._manager.get_cloned_from_cache(self).get(self._read_delay_steps),
-            envs_idx,
-        )
+        return self._get_formatted_data(self._cache.get(self._read_delay_steps), envs_idx)
 
     @gs.assert_built
     def read_ground_truth(self, envs_idx: List[int] | None = None):

genesis/sensors/sensor_manager.py

@@ -23,9 +23,7 @@ def __init__(self, sim):
         self._cache: dict[Type[torch.dtype], TensorRingBuffer] = {}
         self._cache_slices_by_type: dict[Type["Sensor"], slice] = {}
 
-        self._last_cache_cloned_step: int = -1
         self._last_ground_truth_cache_cloned_step: int = -1
-        self._cloned_cache: dict[Type[torch.dtype], TensorRingBuffer] = {}
         self._cloned_ground_truth_cache: dict[Type[torch.dtype], torch.Tensor] = {}
 
     def create_sensor(self, sensor_options: "SensorOptions"):
@@ -80,11 +78,7 @@ def build(self):
             dtype = sensor_cls._get_cache_dtype()
             for sensor in sensors:
                 sensor._shared_metadata = self._sensors_metadata[sensor_cls]
-
-                cache_slice = slice(sensor._cache_idx, sensor._cache_idx + sensor._cache_size)
-                sensor._cache = self._cache[dtype][cache_slice]
-                sensor._ground_truth_cache = self._ground_truth_cache[dtype][cache_slice]
-
+                sensor._cache = self._cache[dtype][sensor._cache_idx : sensor._cache_idx + sensor._cache_size]
                 sensor.build()
 
     def step(self):
@@ -100,13 +94,6 @@ def step(self):
                 self._cache[dtype][cache_slice],
             )
 
-    def get_cloned_from_cache(self, sensor: "Sensor") -> "TensorRingBuffer":
-        dtype = sensor._get_cache_dtype()
-        if self._last_cache_cloned_step != self._sim.cur_step_global:
-            self._last_cache_cloned_step = self._sim.cur_step_global
-            self._cloned_cache[dtype] = self._cache[dtype].clone()
-        return self._cloned_cache[dtype][:, sensor._cache_idx : sensor._cache_idx + sensor._cache_size]
-
     def get_cloned_from_ground_truth_cache(self, sensor: "Sensor") -> torch.Tensor:
         dtype = sensor._get_cache_dtype()
         if self._last_ground_truth_cache_cloned_step != self._sim.cur_step_global:

genesis/utils/ring_buffer.py

@@ -29,14 +29,17 @@ def append(self, tensor: torch.Tensor):
         self.buffer[self._idx_ptr.value].copy_(tensor)
         self._idx_ptr.value = (self._idx_ptr.value + 1) % self.N
 
-    def get(self, idx: int):
+    def get(self, idx: int, clone: bool = True):
         """
         Parameters
         ----------
         idx : int
             Index of the element to get, where 0 is the latest element, 1 is the second latest, etc.
+        clone : bool
+            Whether to clone the tensor.
         """
-        return self.buffer[(self._idx_ptr.value - idx) % self.N]
+        tensor = self.buffer[(self._idx_ptr.value - idx) % self.N]
+        return tensor.clone() if clone else tensor
 
     def clone(self):
         return TensorRingBuffer(