[src/MaxText/inference/offline_engine.py] Make OfflineEngine a fluent interface

[SamuelMarks]

Description

[src/MaxText/inference/offline_engine.py] OfflineEngine.__init__ takes many configuration flags ( enable_batch_prefill, min_decode_steps, prefill_lengths, eos_ids) to configure internal workers and prefill helpers. The setup logic branches based on these flags (e.g., choosing BatchedPrefillProcessor vs PrefillProcessor) ; [tests/{grpo_trainer_correctness_test.py,inference/benchmark_offline_engine.py,offline_engine_test.py}] Update tests for new fluent interface

TL;DR: Instead of passing a long list of arguments (some mutually exclusive or dependent on flags like enable_batch_prefill) directly to __init__, we now use a Builder pattern. This validates configuration (e.g. checking scan_layers vs batch_prefill) before the engine is created.

Before:

# Initialization was brittle with many positional/keyword args
engine = OfflineEngine(
    config=self.config,
    params=self.params,
    min_decode_steps=10,
    enable_batch_prefill=True,
    batch_prefill_max_batch_size=16,
    tokenizer=self.tokenizer,
    eos_ids=[100, 101],
    rng=self.rng
)

After:

# Initialization is now fluent, explicit, and pre-validated
engine = (
    OfflineEngineBuilder(self.config)
    .set_params(self.params)
    .enable_batch_prefill(max_batch_size=16)
    .set_decoding_params(min_steps=10)
    .set_tokenizer(self.tokenizer_path) # Or strictly passing tokenizer instance via builder
    .set_eos_ids([100, 101])
    .set_rng(self.rng)
    .build() # Validation happens here
)

Tests

CI

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