fix bugs: circular import

Author: zewenli98

py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py

@@ -160,7 +160,7 @@ def aten_ops_gelu(
     kwargs: Dict[str, Argument],
     name: str,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.activation.gelu(
+    return impl.actv.gelu(
         network,
         target,
         SourceIR.ATEN,
@@ -177,7 +177,7 @@ def aten_ops_relu(
     kwargs: Dict[str, Argument],
     name: str,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.activation.relu(
+    return impl.actv.relu(
         network,
         target,
         SourceIR.ATEN,
@@ -194,7 +194,7 @@ def aten_ops_sigmoid(
     kwargs: Dict[str, Argument],
     name: str,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.activation.sigmoid(
+    return impl.actv.sigmoid(
         network,
         target,
         SourceIR.ATEN,
@@ -211,7 +211,7 @@ def aten_ops_tanh(
     kwargs: Dict[str, Argument],
     name: str,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.activation.tanh(
+    return impl.actv.tanh(
         network,
         target,
         SourceIR.ATEN,
@@ -228,7 +228,7 @@ def aten_ops_leaky_relu(
     kwargs: Dict[str, Argument],
     name: str,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.activation.leaky_relu(
+    return impl.actv.leaky_relu(
         network,
         target,
         SourceIR.ATEN,
@@ -246,7 +246,7 @@ def aten_ops_elu(
     kwargs: Dict[str, Argument],
     name: str,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.activation.elu(
+    return impl.actv.elu(
         network,
         target,
         SourceIR.ATEN,
@@ -265,7 +265,7 @@ def aten_ops_softplus(
     kwargs: Dict[str, Argument],
     name: str,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.activation.softplus(
+    return impl.actv.softplus(
         network,
         target,
         SourceIR.ATEN,
@@ -283,7 +283,7 @@ def aten_ops_clip(
     kwargs: Dict[str, Argument],
     name: str,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.activation.clip(
+    return impl.actv.clip(
         network,
         target,
         SourceIR.ATEN,
@@ -302,7 +302,7 @@ def aten_ops_hard_sigmoid(
     kwargs: Dict[str, Argument],
     name: str,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.activation.hard_sigmoid(
+    return impl.actv.hard_sigmoid(
         network,
         target,
         SourceIR.ATEN,

py/torch_tensorrt/dynamo/conversion/impl/__init__.py

@@ -1,7 +1,7 @@
 from torch_tensorrt.fx.converters.impl import convolution
 
 from . import (
-    activation,
+    actv,
     cast,
     condition,
     elementwise,

py/torch_tensorrt/dynamo/conversion/impl/activation/__init__.py renamed to py/torch_tensorrt/dynamo/conversion/impl/actv/__init__.py

@@ -7,7 +7,7 @@
 from torch import Tensor
 from torch.fx.node import Target
 from torch_tensorrt.dynamo._SourceIR import SourceIR
-from torch_tensorrt.dynamo.conversion.impl.activation.base import convert_activation
+from torch_tensorrt.dynamo.conversion.impl.actv.base import convert_activation
 from torch_tensorrt.fx.converters.converter_utils import (
     get_trt_plugin,
     mark_as_int8_layer,