DeepEP now records an HTTPS DeepJIT URL, so build_vendor no longer needs the git@github.com rewrite.
Co-authored-by: Shaoyuan Chen <chensy@deepseek.com>
The config and sampling-parameter classes had zero test coverage despite
containing non-trivial validation logic that is exercised on every engine
startup. This PR adds two focused, CPU-only test files that cover all
_verify_args paths and several construction edge cases.
tests/test_sampling_params.py (47 tests)
Covers every validation rule in SamplingParams._verify_args:
- temperature: non-negative check, greedy-mode clamp (< SAMPLING_EPS
→ temperature=SAMPLING_EPS, top_p=1.0, top_k=-1).
- top_p: exclusive lower bound (> 0.0) and upper bound (<= 1.0).
- top_k: -1 (disabled) or [1, INT32_MAX]; zero and other negatives rejected.
- max_tokens: >= 1 and <= INT32_MAX; notably max_tokens=0 now raises
ValueError (the original code silently coerced 0 → 1 before validation).
- top_logprobs: [0, 1000].
- seq_seed: auto-generation, explicit value, uint64 masking, non-int raises.
- logprobs deprecation: logprobs=False emits no warning; logprobs=True
emits DeprecationWarning matching "logprobs.*deprecated".
- Optional fields: golden_token_ids, so_args, ignore_eos, first_n_token_no_eos,
eos_id, prompt_logprobs.
- Greedy mode: temperature=0 overrides top_k and top_p; non-zero preserves them.
tests/test_config.py (23 tests)
CacheConfig:
- Valid construction, boundary values (utilization=1.0), lookahead_tokens,
deferred-field initialisation (num_gpu_blocks etc. start as None).
- Rejects gpu_memory_utilization > 1.0 (existing check).
- Two tests marked xfail(strict=True) for the missing lower-bound guard
(0.0 and negative values currently pass silently). These will flip to
XPASS once PR fix/cache-config-validation is merged.
ParallelConfig:
- Auto-derivation of data_parallel_size when 0 is passed (min 1).
- world_size, data_parallel_rank, model_parallel_size, engram derivation.
- AssertionError when (cp * dp) is not divisible by ep.
- AssertionError when engine_rank is out of range.
SchedulerConfig:
- max_num_batched_tokens auto-default (>= max(max_model_len, 4096)).
- ValueError when explicit max_num_batched_tokens < max_model_len and
chunked_prefill=False; passes when chunked_prefill=True.
- ValueError for prefill_attempt_interval <= 0 and
prefill_any_attempt_interval <= 0.
- runtime_max_model_len >= max_model_len.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
