What happened?

Two bugs in LocalJob.logs(follow=True) that make it pretty unusable as a streaming interface:

1. Duplicate output. The method calls print() internally, so if you iterate get_job_logs(follow=True) and print each line yourself, everything shows up twice — once from inside the SDK, once from your own code.

2. No real-time streaming. Despite follow=True implying otherwise, nothing is yielded until the job finishes. It's just a batched return wearing a streaming API's clothes.

Steps to Reproduce

from kubeflow.trainer import TrainerClient
from kubeflow.trainer.backends.localprocess.backend import LocalProcessBackendConfig

client = TrainerClient(backend_config=LocalProcessBackendConfig())
job_id = client.train(...)

for line in client.get_job_logs(name=job_id, follow=True):
    print(line)  # every line prints twice

Where it's happening

kubeflow/trainer/backends/localprocess/job.py — logs() method:

def logs(self, follow=False) -> list[str]:
    if not follow:
        return self._stdout.splitlines()
    try:
        for chunk in self.stream_logs():
            print(chunk, end="", flush=True)  # ← writes directly to stdout, caller has no say
    except StopIteration:
        pass
    return self._stdout.splitlines()  # ← blocks until job is done, then dumps everything at once

What should happen instead

• No print() inside the method — yielding lines and leaving output decisions to the caller is the whole point of this API.
• Lines should reach the caller as they're produced, not in one batch after the job exits.

Environment

• Kubeflow SDK: 0.4.0
• Backend: LocalProcessBackend
• No Kubernetes cluster needed to reproduce

/kind bug
/area local