[pyTorch] Replace the make_empty implementation to use C++ implementation

[ptrendx]

Description

This PR unifies the implementation of the QuantizedTensor creation by using the C++ implementation of the create_tensor.

Type of change

• Documentation change (change only to the documentation, either a fix or a new content)
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• Infra/Build change
• Code refactoring

Changes

Please list the changes introduced in this PR:

• Replaced the Python implementations of the make_empty with the calls to C++ create_tensor

Checklist:

• I have read and followed the contributing guidelines
• The functionality is complete
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes

[ptrendx]

/te-ci L1 pytorch

[ptrendx]

/te-ci L1 pytorch

[negvet]

This clear NotImplementedError is beneficial for custom quantizers that do not override make_empty().
Now, if custom quantizer does not have make_empty(), then it will fail at the C++ convert_quantizer, because there is no registered C++ converter. C++ failure with NVTE_ERROR("Unexpected type for quantizer") is not as clear as NotImplementedError.

What about making C++ error more clear or even better add a check at base Quantizer.make_empty:

def make_empty(...):
    if getattr(self, "custom", False):
        raise NotImplementedError(
            f"{self.__class__.__name__} does not implement make_empty"
        )
    # ... existing C++ path ...