What is _ctx_tx_to_fallback_0 in context_transfer type ?

## ❓Question

I am not sure if this question is about coremltools or the Core ML Frame work or Xcode.

Here is an example to convert a simple pytorch model to coreml model.

```python
import torch
import torch.nn as nn
import coremltools as ct

class SimpleModel(nn.Module):

def __init__(self,):
super(SimpleModel, self).__init__()

self.weight = nn.Parameter(torch.randn(8, 8, 3, 3))

def forward(self, x):
return x * self.weight

if __name__ == '__main__':

model_pytorch = SimpleModel()
model_pytorch.eval()

input_example = torch.randn(8, 8, 1, 1)
model_traced = torch.jit.trace(model_pytorch, input_example)

model_coreml = ct.convert(
model_traced,
convert_to = 'neuralnetwork',
source = 'pytorch',
inputs = [ct.TensorType(name='x', shape=[8, 8, 1, 1])],
outputs = [ct.TensorType(name='output')],
compute_units = ct.ComputeUnit.ALL,
)
model_coreml.save('SimpleModel.mlmodel')
```

Then, open the **SimpleModel.mlmodel** in XCode and generate a performance report as shown below:

## The Questions are:

- What is **_ctx_tx_to_fallback_0** in **context_transfer** type ?
I found nothing about **_ctx_tx_to_fallback_0** or **context_transfer** in Core ML documentation.
- How to modify the code to make this operation work on Neural Engine ?

## Environment:

- macOS Ventura 13.5.2
- XCode 14.3.1
- Python 3.8.17
- coremltools 7.0b2
- torch 2.0.0

Start by reproducing the provided Python/PyTorch conversion example with coremltools 7.0b2 and opening the generated SimpleModel.mlmodel in Xcode 14.3.1. Inspect the performance report's context_transfer entry and compare the reported execution device with the requested Neural Engine behavior; done means explaining the entry and determining whether the example can run that operation on the Neural Engine.

Written by the indexing model from the issue text.