behavior to `torch.tensor` and `torch.Tensor` looks unclear

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## 🐛 Bug

If a callable uses `torch.tensor` or `torch.Tensor` (while the latter is not that recommended as a tensor constructor, https://pytorch.org/docs/stable/tensors.html#torch-tensor), Thunder's interpreter does not seem to cope with them. `examine` seems to show some clumsiness.

### To Reproduce

Run the snippet attached below.

```
### h=
/home/mkozuki/ghq/github.com/Lightning-AI/lightning-thunder/d.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
return torch.tensor(h)
Failed to run the unmodified function. Please verify that your code runs without thunder
The code failed with exception - sin(): argument 'input' (position 1) must be Tensor, not tuple
name 'n' is not defined
### h=
Failed to run the unmodified function. Please verify that your code runs without thunder
The code failed with exception - sin(): argument 'input' (position 1) must be Tensor, not tuple
len() of a 0-d tensor
```

#### Code sample

```python
import torch

import thunder
from thunder.examine import examine

def f(x):
h = torch.sin(x)
return torch.tensor(h)

def g(x):
h = torch.sin(x)
return torch.Tensor(h)

for h in (f, g):
print(f"### {h=}")
x = torch.randn((2, 2), device="cuda", requires_grad=True)
y = h(x)
x = torch.randn((2, 2), device="cuda", requires_grad=True)
try:
examine(h, (x,))
jitted = thunder.jit(h)
y = jitted(x)
except Exception as e:
print(e)
```

### Expected behavior

Clear error, or handle them

Reproduce the issue with the provided Python snippet, focusing on examine(h, (x,)) and thunder.jit(h) for functions using torch.tensor and torch.Tensor. Start by tracing how the interpreter handles these constructors; done means both cases are either supported correctly or produce a clear, accurate error instead of the reported failures.

Written by the indexing model from the issue text.