Existing Tests

The test suite is organized by product surface. This page intentionally lists directories and representative live tests rather than attempting to mirror every filename.

Area	Coverage	Representative tests
`tests/checkpoint/`	Checkpoint process groups and EP mesh handling	`test_checkpointer_process_group.py`, `test_ep_checkpoint_mesh.py`
`tests/data/`	Dataset preparation, packing, collators, dataloaders	`test_data_loader.py`, `collators/test_collate_pipeline.py`
`tests/distillation/`	Teacher-state storage and transport	`test_mooncake_hidden_store.py`
`tests/distributed/`	FSDP/TP/PP/EP/CP collectives and numerical contracts	`test_canonical_moe_contract.py`, `test_deepep_async_combine_guard.py`
`tests/e2e/`	Small-model end-to-end training under torchrun	`qwen3_8b/test_lora.py`, `qwen3_30b/test_server_moe.py`
`tests/experiments/`	Training simulator behavior	`test_training_sim.py`
`tests/fp8_training/`	Full-weight FP8 configuration, linears, and MoE	`test_config_compat.py`, `test_fp8_moe.py`
`tests/models/`	Registry, model loading, attention, batch invariance, architecture guards	`test_dsv4_exact_contract.py`, `test_dsv4_native_combine.py`
`tests/ops/`	Losses, quantization, DSV4, MoE, attention, and kernels	`test_sgl_kernel_smoke.py`, `dsv4/test_compressor.py`
`tests/optim/`	AdamW/Muon/DistSignSGD and scheduler behavior	`test_muon.py`, `test_distsignsgd.py`
`tests/qarl/`	Calibration and fake-quant paths	`test_calibration.py`, `test_fake_quant.py`
`tests/qlora/`	QLoRA detection, loading, adapters, and kernels	`test_detect_prequantized.py`, `test_qlora.py`
`tests/scripts/`	Export and OPD payload scripts	`test_export_quantized.py`, `test_opd_pipeline_payloads.py`
`tests/server/`	API schemas, orchestration, backends, runners, and all weight-sync transports	`api_server/test_api_types.py`, `weight_sync/`
`tests/trainers/`	Trainer construction and architecture-specific training guards	`test_fp8_model_builder.py`, `test_deepseek_v3_training_guards.py`
`tests/utils/`	FLOP accounting, timing, and teacher caches	`test_count_flops.py`, `test_manual_cuda_timing.py`

Get the current inventory:

find tests -type f -name 'test_*.py' | sort

Presence of a conventional test demonstrates the checked-in mechanism and its tested scope. GPU/backend availability, full-model behavior, trainer/sampler revision-pair exactness, and production qualification remain separate gates.