fix bugs

Author: zewenli98

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

@@ -1,8 +1,8 @@
 import math
 from typing import Optional
 
+import numpy as np
 import tensorrt as trt
-import torch
 from torch.fx.node import Target
 from torch_tensorrt.dynamo._SourceIR import SourceIR
 from torch_tensorrt.dynamo.conversion import impl
@@ -13,11 +13,9 @@
 )
 from torch_tensorrt.dynamo.conversion.impl.slice.base import slice
 from torch_tensorrt.fx.converters.converter_utils import (
-    Frameworks,
     has_dynamic_shape,
     prepend_ones,
     set_layer_name,
-    unified_dtype_converter,
 )
 from torch_tensorrt.fx.types import Shape, TRTTensor
 
@@ -130,18 +128,16 @@ def cumsum(
     input_shape = input.shape
     dim = get_positive_dim(dim, len(input_shape))
     loop = ctx.net.add_loop()
-    axis = torch.tensor(input_shape[dim], dtype=torch.int32)
+    axis = np.array(input_shape[dim])
     trip_limit = get_trt_tensor(ctx, axis, f"{name}_trip_limit")
     loop.add_trip_limit(trip_limit, trt.TripLimit.COUNT)
     iterator = loop.add_iterator(input, dim, reverse=False)
     data = iterator.get_output(0)
     new_dims = tuple(data.shape)
-    zero_tensor = torch.zeros(
-        new_dims, dtype=unified_dtype_converter(input.dtype, Frameworks.TORCH)
-    )
-    zero_tensor = get_trt_tensor(ctx, zero_tensor, f"{name}_initial_value")
+    zeros = np.zeros(new_dims)
+    zero_trttensor = get_trt_tensor(ctx, zeros, f"{name}_initial_value")
 
-    running_sum = loop.add_recurrence(zero_tensor)
+    running_sum = loop.add_recurrence(zero_trttensor)
     set_layer_name(running_sum, target, f"{name}_running_sum", source_ir)
     running_sum_tensor = running_sum.get_output(0)