[Code scan] block_avg crashes when no full block remains

[njzjz]

Source: Codex global repository scan of deepmodeling/dpti at commit b719828.
Project: DeepModeling Agent Code Scan

Problem
block_avg() assumes at least one full block survives after skip. If the input after skipping is empty, data_chunks[-1] raises IndexError; if it has fewer samples than block_size, the only partial block is dropped and NumPy later raises an axis error.

Code references

dpti/dpti/lib/utils.py

Line 105 in b719828

def block_avg(inp, skip = 0, block_size = 10) :

dpti/dpti/lib/utils.py

Line 112 in b719828

if (len(data_chunks[-1]) != block_size) :

dpti/dpti/lib/utils.py

Line 120 in b719828

data_chunks = np.array(data_chunks)

Reproduction
Run:

import numpy as np
from dpti.lib.utils import block_avg
block_avg(np.arange(5), block_size=10)

Expected result
The function should either handle the partial block intentionally or raise a clear validation error explaining that no complete block is available.