chore: import converter_utils from dynamo

Author: keehyuna

py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py

@@ -10,12 +10,10 @@
 from torch_tensorrt.dynamo._SourceIR import SourceIR
 from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
 from torch_tensorrt.dynamo.conversion.converter_utils import (
+    broadcast,
     broadcast_to_same_shape,
     cast_trt_tensor,
     get_trt_tensor,
-)
-from torch_tensorrt.fx.converters.converter_utils import (
-    broadcast,
     has_dynamic_shape,
     set_layer_name,
 )
@@ -152,7 +150,7 @@ def convert_binary_elementwise(
 
     if has_dynamic_shape(lhs_val.shape) or has_dynamic_shape(rhs_val.shape):
         lhs_val, rhs_val = broadcast(
-            ctx.net, lhs_val, rhs_val, f"{name}_broadcast_lhs", f"{name}_broadcast_rhs"
+            ctx, lhs_val, rhs_val, f"{name}_broadcast_lhs", f"{name}_broadcast_rhs"
         )
     else:
         lhs_val, rhs_val = broadcast_to_same_shape(

py/torch_tensorrt/dynamo/conversion/impl/elementwise/ops.py

@@ -1,13 +1,15 @@
 from typing import Optional, Union
 
 import numpy as np
+import tensorrt as trt
 import torch
 import torch_tensorrt.dynamo.conversion.impl as impl
 from torch.fx.node import Target
 from torch_tensorrt import _enums
 from torch_tensorrt.dynamo._SourceIR import SourceIR
 from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
 from torch_tensorrt.dynamo.conversion.converter_utils import (
+    broadcast,
     cast_int_int_div_trt_tensor,
     cast_int_or_float_to_bool,
     cast_trt_tensor,
@@ -19,11 +21,8 @@
 )
 from torch_tensorrt.dynamo.conversion.impl.unary import atan, sign
 from torch_tensorrt.dynamo.conversion.impl.unary.base import convert_unary
-from torch_tensorrt.fx.converters.converter_utils import broadcast
 from torch_tensorrt.fx.types import TRTTensor
 
-import tensorrt as trt
-
 
 def trunc_div(
     ctx: ConversionContext,
@@ -258,7 +257,7 @@ def atan2(
     if isinstance(other, TRTTensor):
         other = cast_trt_tensor(ctx, other, trt.float32, f"{name}_other")
 
-    input, other = broadcast(ctx.net, input, other, f"{name}_input", f"{name}_other")
+    input, other = broadcast(ctx, input, other, f"{name}_input", f"{name}_other")
 
     # Calculate x_zero, y_zero (whether inputs are zero)
     x_zero = eq(ctx, target, source_ir, f"{name}_x_zero", input, 0)