Fix MultiSystems loading of unlabeled data from deepmd/npy/mixed format

[Copilot]

The dpdata.MultiSystems.from_file() method with fmt="deepmd/npy/mixed" was failing when attempting to load data that was dumped from systems without labels (i.e., regular System objects instead of LabeledSystem objects). The error occurred because the code always tried to create LabeledSystem objects which require "energies" data, but unlabeled systems don't have this data.

Example of the issue:

import dpdata
import numpy as np

# Create unlabeled systems (no energies/forces)
system_data = {
    'atom_names': ['H', 'O'],
    'atom_numbs': [2, 1],
    'atom_types': np.array([0, 0, 1]),
    'orig': np.array([0., 0., 0.]),
    'cells': np.random.random((2, 3, 3)),
    'coords': np.random.random((2, 3, 3))
}

system = dpdata.System(data=system_data)
ms = dpdata.MultiSystems(system)

# Dump works fine
ms.to_deepmd_npy_mixed("mixed_dir")

# But loading fails with: DataError: energies not found in data
ms_loaded = dpdata.MultiSystems.from_file("mixed_dir", fmt="deepmd/npy/mixed")

Solution:
Modified MultiSystems.from_fmt_obj() to auto-detect whether loaded data contains labels by checking for the presence of required label fields (specifically "energies"). When labeled=True (the default), the method now:

1. Loads data using the labeled format loader to get all available fields
2. Checks if the returned data contains "energies"
3. Creates LabeledSystem objects if labels are present, System objects otherwise

This approach maintains full backward compatibility while enabling unlabeled data to be loaded correctly. The existing labeled=False parameter continues to work as before.

Testing:

• Added comprehensive test coverage for unlabeled systems in test_deepmd_mixed_unlabeled.py
• Verified all existing deepmd/npy/mixed tests continue to pass
• Tested mixed scenarios with both labeled and unlabeled data
• Confirmed the labeled=False parameter still functions correctly

Fixes #817.

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