Tracking issue: #138399

This PR changes the `pow` ref implementation, making its meta kernel consistent with its
CPU implementation. The following example shows the inconsistency between the two:

```python
def run(device):
    S = (5,)
    a = torch.rand(S, device=device, dtype=torch.float32)
    b = 2
    out = torch.empty(S, device=device, dtype=torch.float64)
    return torch.pow(a, b, out=out)

>>> run("cpu")
Traceback (most recent call last):
  File "test.py", line 34, in run
    return torch.pow(a, b, out=out)
RuntimeError: Found dtype Double but expected Float

>>> run("meta")
tensor(..., device='meta', size=(5,), dtype=torch.float64)
```

ghstack-source-id: 5371f04
Pull Request resolved: #140287

Tracking issue: #138399

This PR changes the `pow` C++ implementation, making its C++ meta kernel consistent with
its Python ref implementation. The following example shows the inconsistency between the
two:

```python
def run(device):
    S = (5,)
    a = torch.rand(S, device=device, dtype=torch.float32)
    b = 2
    out = torch.empty(S, device=device, dtype=torch.float64)
    return torch.pow(a, b, out=out)

>>> run("cpu")
Traceback (most recent call last):
  File "test.py", line 34, in run
    return torch.pow(a, b, out=out)
RuntimeError: Found dtype Double but expected Float

>>> run("meta")
tensor(..., device='meta', size=(5,), dtype=torch.float64)
```

ghstack-source-id: 67a3ec5
Pull Request resolved: #140287

Tracking issue: #138399

This PR changes the `pow` C++ implementation, making its C++ meta kernel consistent with
its Python ref implementation. The following example shows the inconsistency between the
two:

```python
def run(device):
    S = (5,)
    a = torch.rand(S, device=device, dtype=torch.float32)
    b = 2
    out = torch.empty(S, device=device, dtype=torch.float64)
    return torch.pow(a, b, out=out)

>>> run("cpu")
Traceback (most recent call last):
  File "test.py", line 34, in run
    return torch.pow(a, b, out=out)
RuntimeError: Found dtype Double but expected Float

>>> run("meta")
tensor(..., device='meta', size=(5,), dtype=torch.float64)
```

ghstack-source-id: b902a55
Pull Request resolved: #140287

Tracking issue: #138399

This PR changes the `pow` C++ implementation, making its C++ meta kernel consistent with
its Python ref implementation. The following example shows the inconsistency between the
two:

```python
def run(device):
    S = (5,)
    a = torch.rand(S, device=device, dtype=torch.float32)
    b = 2
    out = torch.empty(S, device=device, dtype=torch.float64)
    return torch.pow(a, b, out=out)

>>> run("cpu")
Traceback (most recent call last):
  File "test.py", line 34, in run
    return torch.pow(a, b, out=out)
RuntimeError: Found dtype Double but expected Float

>>> run("meta")
tensor(..., device='meta', size=(5,), dtype=torch.float64)
```

ghstack-source-id: ce865dd
Pull Request resolved: #140287

Tracking issue: pytorch#138399

This PR changes the `pow` C++ implementation, making its C++ meta kernel consistent with
its Python ref implementation. The following example shows the inconsistency between the
two:

```python
def run(device):
    S = (5,)
    a = torch.rand(S, device=device, dtype=torch.float32)
    b = 2
    out = torch.empty(S, device=device, dtype=torch.float64)
    return torch.pow(a, b, out=out)

>>> run("cpu")
Traceback (most recent call last):
  File "test.py", line 34, in run
    return torch.pow(a, b, out=out)
RuntimeError: Found dtype Double but expected Float

>>> run("meta")
tensor(..., device='meta', size=(5,), dtype=torch.float64)
```

**~Update:~**

~Note that this happens only for `pow.Tensor_Scalar` overloads. Therefore, this PR needed
further 2 modifications:~

- ~Split the `pow` ref implementation, making `pow.Tensor_Scalar` error on mismatching
output dtypes~
- ~Create a dispatch for `pow` when `_refs.pow()` is called~

**Update:**

Changing the `TensorIteratorConfig` for `pow.Tensor_Scalar` was easier and,
after the discussion below, more correct. The solution was to change the
`TensorIteratorBase::build_output_borrowing_argument_owning_unary_op` function,
setting:

- `cast_common_dtype_to_outputs`; and
- `enforce_safe_casting_to_output`.

Pull Request resolved: pytorch#140287
Approved by: https://github.com/ezyang