[BUG] DPA4C compression crashes for trainable=False descriptors #5990

Summary

DescrptDPA4C.enable_compression() crashes when the descriptor was constructed with the supported trainable=False option.

This reproduces on origin/master at 8cfd46e37448.

Reproduction

from deepmd.pt_expt.descriptor.dpa4c import DescrptDPA4C

d = DescrptDPA4C(
    rcut=3.0,
    ntypes=2,
    channels=8,
    lmax=2,
    n_radial=4,
    precision="float32",
    trainable=False,
).eval()
d.enable_compression(0.5, table_stride_1=0.2)

Actual result:

deepmd/kernels/cuda/dpa4c/graph_compress.py:525
sample_parameter = next(descriptor.radial_embedding.parameters())
StopIteration

Cause

build_radial_table() obtains the device and dtype from the first radial-embedding parameter. With trainable=False, the frozen radial MLP weights are registered as buffers, so radial_embedding.parameters() is empty.

Expected behavior

Compression should work for a frozen descriptor. trainable changes parameter registration, not the learned function or compression eligibility.

The device/dtype should be obtained from a tensor that exists in both trainable and frozen forms, and a regression test should enable compression on a trainable=False DPA4C descriptor.

Coding agent: Codex
Codex version: codex-cli 0.149.0
Model: gpt-5.6-sol
Reasoning effort: xhigh