"ValueError: Torch var mask.3 not found in context" when converting PyTorch model

## 🐞Describing the bug
When attempting to convert the text model within [Huggingface Transformers' version of CLIP](https://huggingface.co/docs/transformers/v4.21.1/en/model_doc/clip#overview), the conversion fails due to an unrecognized input for a `triu` op.

## Stack Trace
```py
Converting PyTorch Frontend ==> MIL Ops: 4%|██▌ | 31/811 [00:00<00:00, 3040.63 ops/s]
Traceback (most recent call last):
File "/Users/austin/Projects/openai-clip-trace-v/trace_clip.py", line 83, in
ml_model = ct.convert(
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/_converters_entry.py", line 451, in convert
mlmodel = mil_convert(
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/converter.py", line 193, in mil_convert
return _mil_convert(model, convert_from, convert_to, ConverterRegistry, MLModel, compute_units, **kwargs)
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/converter.py", line 220, in _mil_convert
proto, mil_program = mil_convert_to_proto(
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/converter.py", line 283, in mil_convert_to_proto
prog = frontend_converter(model, **kwargs)
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/converter.py", line 115, in __call__
return load(*args, **kwargs)
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/load.py", line 53, in load
return _perform_torch_convert(converter, debug)
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/load.py", line 92, in _perform_torch_convert
prog = converter.convert()
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/converter.py", line 269, in convert
convert_nodes(self.context, self.graph)
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/ops.py", line 92, in convert_nodes
add_op(context, node)
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/ops.py", line 4031, in triu
inputs = _get_inputs(context, node, expected=2)
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/ops.py", line 190, in _get_inputs
inputs = [context[name] for name in node.inputs]
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/ops.py", line 190, in
inputs = [context[name] for name in node.inputs]
File "/Users/austin/miniconda3/envs/clipp/lib/python3.9/site-packages/coremltools/converters/mil/frontend/torch/converter.py", line 82, in __getitem__
raise ValueError(
ValueError: Torch var mask.3 not found in context
```

## To Reproduce

### Setup environment

```sh
conda create --name clip-triu-bug --yes \
"pytorch::pytorch>=1.10,<1.11" \
huggingface::transformers \
python-dateutil \
pillow
conda activate clip-triu-bug
pip3 install coremltools==6.0b2
```

### Run `clip_text_convert.py`
```py
import torch
import numpy as np
import coremltools as ct

from transformers.models.clip.processing_clip import CLIPProcessor
from transformers.models.clip.modeling_clip import CLIPModel

# Combine CLIP Text Model and Text Projection for exporting as one
# // Disabled text_projection as its not needed to reproduce error
class CLIPTextEmbedder(torch.nn.Module):
def __init__(self, text_model):
super(CLIPTextEmbedder, self).__init__()
self.text_model = text_model
# self.text_projection = text_projection

def forward(self, input_ids):
pooled_out = self.text_model(input_ids)[1]
# embedded_out = self.text_projection(pooled_out)
return pooled_out # embedded_out

# Load the pretrained CLIP Model from Huggingface Transformers
pretrained_identifier = 'openai/clip-vit-base-patch32'
processor = CLIPProcessor.from_pretrained(pretrained_identifier)
# return_dict=False so that it returns tuples... needed for tracing
model = CLIPModel.from_pretrained(pretrained_identifier, return_dict=False)

# Isolate text embedding into separate models for export
text_for_export = CLIPTextEmbedder(model.text_model)#, model.text_projection)

# Pre-processing text for trace
text = "a painting of a corgi wearing a royal cape and crown"
# Since we're tracing, should probably pad the text so that different length inputs are pre-processed to a single input shape
preprocessed_text = processor(text=text, padding='max_length', return_tensors='pt').input_ids

with torch.no_grad():
traced_model = torch.jit.trace(text_for_export, preprocessed_text)
text_outputs = traced_model(preprocessed_text)
ml_model = ct.convert(
model=traced_model,
inputs=[
ct.TensorType(shape=preprocessed_text.shape, dtype=np.int64)
]
)

# Export to CLIPTextEmbedder[openai_clip-vit-base-patch32].mlmodel
out_filename = f'{type(text_for_export).__name__}[{pretrained_identifier.replace("/", "_")}].mlmodel'
ml_model.save(out_filename)

```
## System environment (please complete the following information):
- coremltools version: `6.0b2`
- OS (e.g. MacOS version or Linux type): `macOS Montery v12.2.1`
- Any other relevant version information (e.g. PyTorch or TensorFlow version):
- PyTorch version: `4.10.2`
- transformers version: `4.21.1`

## Additional context
- Using `coremltools` version `5.2` yields a different error, as it's missing the changes from PR #1439 and PR #1454, which allow version `6.0b2` to progress and then produce this error.

Start by reproducing the conversion with the provided CLIP script and inspect coremltools/converters/mil/frontend/torch/ops.py, especially triu and _get_inputs, along with the converter context lookup. Confirm the fix by rerunning the same PyTorch and Hugging Face CLIP conversion without the missing mask.3 error.

Written by the indexing model from the issue text.