ViperEkura
75304d084d
- add skip_no_fp8 (CUDA + fp8_mm kernel + cc 8.9+) to tests/conftest.py - use skip_no_cuda / skip_no_kernel / skip_no_fp8 directly in test modules - drop _GPU alias and tests.extension.conftest re-exports - remove unused imports (Union in hf_adapter, make_grpo_config in data conftest)
64 lines
2.1 KiB
Python
64 lines
2.1 KiB
Python
import torch
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import torch.distributed as dist
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from torch.distributed.fsdp import fully_shard
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from torch.distributed.tensor import DTensor, Shard
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from torch.nn.parallel import DistributedDataParallel as DDP
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from astrai.model import AutoRegressiveLM
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from astrai.optim import NoraNAdamW
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from astrai.parallel.setup import find_free_port
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from tests.conftest import skip_no_cuda
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from tests.helpers import make_tiny_config
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pytestmark = skip_no_cuda
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def _assign_grads_and_step(model):
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optimizer = NoraNAdamW(model)
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for param in model.parameters():
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if param.requires_grad:
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param.grad = torch.ones_like(param)
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optimizer.step()
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return optimizer
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def test_nora_nadamw_steps_after_ddp_and_fsdp2_wrapping():
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torch.cuda.set_device(0)
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dist.init_process_group(
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"nccl",
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rank=0,
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world_size=1,
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init_method=f"tcp://127.0.0.1:{find_free_port()}",
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)
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try:
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ddp_model = AutoRegressiveLM(make_tiny_config()).to(
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device="cuda", dtype=torch.bfloat16
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)
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ddp_model = DDP(ddp_model, device_ids=[0], output_device=0)
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ddp_optimizer = _assign_grads_and_step(ddp_model)
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assert ddp_optimizer.state_dict()["nora"]["state"]
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fsdp_model = AutoRegressiveLM(make_tiny_config()).to(
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device="cuda", dtype=torch.bfloat16
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)
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for child in fsdp_model.children():
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if isinstance(child, torch.nn.ModuleList):
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for submodule in child:
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fully_shard(submodule, reshard_after_forward=False)
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else:
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fully_shard(child, reshard_after_forward=False)
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fsdp_optimizer = _assign_grads_and_step(fsdp_model)
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nora_params = fsdp_optimizer.nora.param_groups[0]["params"]
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assert nora_params
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assert all(isinstance(param, DTensor) for param in nora_params)
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assert all(
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all(
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not isinstance(placement, Shard) or placement.dim == 0
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for placement in param.placements
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)
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for param in nora_params
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)
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finally:
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dist.destroy_process_group()
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