refactor: Moving elementwise core to impl (FX Converter Refactor [3/N]) <Target: converter_reorg_proto>

py/torch_tensorrt/fx/converters/aten_ops_converters.py

@@ -21,6 +21,8 @@
 from .converter_utils import *  # noqa: F403
 import torch_tensorrt.fx.tracer.acc_tracer.acc_utils as acc_utils
 from torch_tensorrt.fx.converters.impl import activation, convolution
+from torch_tensorrt.fx.converters.impl.elementwise import trunc_div
+from torch_tensorrt.fx.converters.impl.elementwise import rsqrt
 
 _LOGGER: logging.Logger = logging.getLogger(__name__)
 
@@ -182,9 +184,7 @@ def aten_ops_div(
             network, target, None, kwargs_new, name
         )
     elif rounding_mode == "trunc":
-        return acc_ops_converters.acc_ops_trunc_div(
-            network, target, None, kwargs_new, name
-        )
+        return trunc_div(network, target, SourceIR.ATEN, name, args[0], args[1])
     else:
         raise RuntimeError(
             f"Target {target} does not support rounding mode {rounding_mode}"
@@ -390,6 +390,42 @@ def aten_ops_relu(
     )
 
 
+@tensorrt_converter(torch.ops.aten.relu.default)
+def aten_ops_relu(
+    network: TRTNetwork,
+    target: Target,
+    args: Tuple[Argument, ...],
+    kwargs: Dict[str, Argument],
+    name: str,
+) -> Union[TRTTensor, Sequence[TRTTensor]]:
+
+    return activation.relu(
+        network,
+        target,
+        SourceIR.ATEN,
+        name,
+        args[0],
+    )
+
+
+@tensorrt_converter(torch.ops.aten.rsqrt.default)
+def aten_ops_rsqrt(
+    network: TRTNetwork,
+    target: Target,
+    args: Tuple[Argument, ...],
+    kwargs: Dict[str, Argument],
+    name: str,
+) -> Union[TRTTensor, Sequence[TRTTensor]]:
+
+    return rsqrt(
+        network,
+        target,
+        SourceIR.ATEN,
+        name,
+        args[0],
+    )
+
+
 @tensorrt_converter(torch.ops.aten.sub.Tensor)
 def aten_ops_sub(
     network: TRTNetwork,