revert prelu impl

Author: zewenli98

py/torch_tensorrt/dynamo/conversion/impl/prelu.py

@@ -2,7 +2,6 @@
 
 from torch.fx.node import Target
 from torch_tensorrt.dynamo._SourceIR import SourceIR
-from torch_tensorrt.dynamo.conversion import impl
 from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
 from torch_tensorrt.dynamo.conversion.converter_utils import set_layer_name
 from torch_tensorrt.dynamo.types import TRTTensor
@@ -16,12 +15,6 @@ def prelu(
     input: TRTTensor,
     weight: TRTTensor,
 ) -> TRTTensor:
-    # TRT requires that the slopes tensor must be unidirectional broadcastable to the input tensor:
-    # the rank of the two tensors must be the same, and all dimensions of the slopes tensor must
-    # either equal the input tensor or be 1. The output tensor has the same shape as the input tensor.
-    input, weight = impl.elementwise.broadcast(
-        ctx, input, weight, f"{name}_broadcast_input", f"{name}_broadcast_weight"
-    )
-    layer = ctx.net.add_parametric_relu(input, slopes=weight)
+    layer = ctx.net.add_parametric_relu(input, weight)
     set_layer_name(layer, target, name, source_ir)
     return layer.get_output(0)