covert pytorch to onnx

[newbecoder]

when i try to convert dinov3-vitb16 model to onnx, i come across a problem, the exported onnx model's input have two param: input and t_mask, i wanna know what is the t_masks, and if i wanna deploy the model by tritonserver, how can i write the config.pbtxt? here is my convert code :
`# we take DINOv3 ViT-B
MODEL_NAME = "dinov3_vitb16"

def convert(weights):
device = torch.device("cpu")
print(f"Using device: {device}")

# 1. load model 
original_model = torch.hub.load(
    repo_or_dir=DINOV3_LOCATION,
    model=MODEL_NAME,
    source="local",
    weights=weights,
).to(device)
original_model.eval()

# 2. input
dynamic_batch_size = 1
dummy_input = torch.randn(dynamic_batch_size, 3, 224, 224).to(device)

onnx_model_path = "dinov3_vitb16.onnx"
torch.onnx.export(
    original_model,
    dummy_input,
    onnx_model_path,
    input_names=["input"],
    output_names=["output"],
    dynamic_axes={
        'input': {0: 'batch_size'}, 
        'output': {0: 'batch_size'}
    },
    opset_version=14,
    do_constant_folding=True,
    verbose=False,
    # dynamo=True
)

# 3. 
onnx_model = onnx.load(onnx_model_path)
onnx.checker.check_model(onnx_model)

print("\n input layer info:")
for i, input in enumerate(onnx_model.graph.input):
    dims = [dim.dim_value if dim.dim_value > 0 else -1 
            for dim in input.type.tensor_type.shape.dim]
    print(f" {i}: name='{input.name}', shape={dims}")

print("\n output layer info:")
for i, output in enumerate(onnx_model.graph.output):
    dims = [dim.dim_value if dim.dim_value > 0 else -1 
            for dim in output.type.tensor_type.shape.dim]
    print(f" {i}: name='{output.name}', shape={dims}")
return onnx_model_path

`