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[shardformer] added embedding gradient check (#4124)

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This commit is contained in:
Frank Lee
2023-06-30 16:16:44 +08:00
parent 44a190e6ac
commit ae035d305d
14 changed files with 255 additions and 74 deletions
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26
tests/test_shardformer/test_model/test_shard_opt.py
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@@ -28,7 +28,10 @@ def check_forward_backward(org_model, sharded_model, data_gen_fn, output_transfo
org_loss.backward()
shard_loss.backward()
# check grad
assert torch.allclose(org_loss, shard_loss,
atol=1e-5), f"shard model loss is not equal to orgin model loss\n{org_loss}\n{shard_loss}"
# unwrap model
if hasattr(org_model, 'model'):
opt_model = org_model.model
shard_opt_model = sharded_model.model
@@ -36,16 +39,23 @@ def check_forward_backward(org_model, sharded_model, data_gen_fn, output_transfo
opt_model = org_model
shard_opt_model = sharded_model
# check attention grad
org_grad = opt_model.decoder.layers[0].self_attn.q_proj.weight.grad
shard_grad = shard_opt_model.decoder.layers[0].self_attn.q_proj.weight.grad
shard_grad_list = [torch.zeros([*shard_grad.shape]).to('cuda') for _ in range(4)]
shard_grad = torch.distributed.all_gather(shard_grad_list, shard_grad)
torch.distributed.all_gather(shard_grad_list, shard_grad)
all_shard_grad = torch.cat(shard_grad_list, dim=0)
assert torch.allclose(org_loss, shard_loss,
atol=1e-5), f"shard model loss is not equal to orgin model loss\n{org_loss}\n{shard_loss}"
assert torch.allclose(org_grad, all_shard_grad,
atol=1e-5), f"shard model grad is not equal to orgin model grad\n{org_grad}\n{shard_grad}"
atol=1e-5), f"shard model grad is not equal to orgin model grad\n{org_grad}\n{all_shard_grad}"
# check embedding grad
org_grad = opt_model.decoder.embed_tokens.weight.grad
shard_grad = shard_opt_model.decoder.embed_tokens.weight.grad
shard_grad_list = [torch.zeros([*shard_grad.shape]).to('cuda') for _ in range(4)]
torch.distributed.all_gather(shard_grad_list, shard_grad)
all_shard_grad = torch.cat(shard_grad_list, dim=0)
assert torch.allclose(org_grad, all_shard_grad,
atol=1e-5), f"shard model grad is not equal to orgin model grad\n{org_grad}\n{all_shard_grad}"
def check_OPTModel(rank, world_size, port):
@@ -65,3 +75,7 @@ def check_OPTModel(rank, world_size, port):
@clear_cache_before_run()
def test_OPTModel():
spawn(check_OPTModel, 4)
if __name__ == '__main__':
test_OPTModel()