add full buffer return to CircularBuffer

source/extensions/omni.isaac.lab/omni/isaac/lab/utils/buffers/circular_buffer.py

@@ -75,6 +75,16 @@ def current_length(self) -> torch.Tensor:
         """
         return torch.minimum(self._num_pushes, self._max_len)
 
+    @property
+    def buffer(self) -> torch.Tensor:
+        """Complete circular buffer with most recent entry at the end and oldest entry at the beginning.
+        Returns:
+            Complete circular buffer with most recent entry at the end and oldest entry at the beginning of dimension 1. The shape is [batch_size, max_length, data.shape[1:]].
+        """
+        buf = self._buffer.clone()
+        buf = torch.roll(buf, shifts=self.max_length - self._pointer - 1, dims=0)
+        return torch.transpose(buf, dim0=0, dim1=1)
+
     """
     Operations.
     """

source/extensions/omni.isaac.lab/test/utils/test_circular_buffer.py

@@ -121,6 +121,32 @@ def test_key_greater_than_pushes(self):
         retrieved_data = self.buffer[torch.tensor([5, 5, 5], device=self.device)]
         self.assertTrue(torch.equal(retrieved_data, data1))
 
+    def test_return_buffer_prop(self):
+        """Test retrieving the whole buffer for correct size and contents.
+        Returning the whole buffer should have the shape [batch_size,max_len,data.shape[1:]]
+        """
+        num_overflow = 2
+        for i in range(self.buffer.max_length + num_overflow):
+            data = torch.tensor([[i]], device=self.device).repeat(3, 2)
+            self.buffer.append(data)
+
+        retrieved_buffer = self.buffer.buffer
+        # check shape
+        self.assertTrue(retrieved_buffer.shape == torch.Size([self.buffer.batch_size, self.buffer.max_length, 2]))
+        # check that batch is first dimension
+        torch.testing.assert_close(retrieved_buffer[0], retrieved_buffer[1])
+        # check oldest
+        torch.testing.assert_close(
+            retrieved_buffer[:, 0], torch.tensor([[num_overflow]], device=self.device).repeat(3, 2)
+        )
+        # check most recent
+        torch.testing.assert_close(
+            retrieved_buffer[:, -1],
+            torch.tensor([[self.buffer.max_length + num_overflow - 1]], device=self.device).repeat(3, 2),
+        )
+        # check that it is returned oldest first
+        for idx in range(self.buffer.max_length - 1):
+            self.assertTrue(torch.all(torch.le(retrieved_buffer[:, idx], retrieved_buffer[:, idx + 1])))
 
 if __name__ == "__main__":
     run_tests()