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[fix] fix mem assert;

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duanjunwen 2024-09-19 08:27:47 +00:00
parent a115106f8d
commit 4753bf7add
1 changed files with 11 additions and 9 deletions
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20
tests/test_pipeline/test_schedule/test_zerobubble_pp.py
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@ -596,7 +596,7 @@ def run_fwd_bwd_vschedule_with_optim(test_config):
batch_size = test_config["batch_size"] batch_size = test_config["batch_size"]
num_layers = 8 num_layers = 8
assert num_layers % num_model_chunk == 0, f"Model with {num_layers} layer can not dist on {num_model_chunk} chunk" assert num_layers % num_model_chunk == 0, f"Model with {num_layers} layer can not dist on {num_model_chunk} chunk"
in_dim = out_dim = 1024 in_dim = out_dim = 4096
before_init_memory = torch.cuda.memory_allocated() / 1024**3 before_init_memory = torch.cuda.memory_allocated() / 1024**3
print(f"Before init Model: {before_init_memory :.3f} GB on device {stage_manager.get_rank()};") print(f"Before init Model: {before_init_memory :.3f} GB on device {stage_manager.get_rank()};")
model = MlpModel(in_dim=in_dim, out_dim=out_dim, num_layers=num_layers).to(rank) model = MlpModel(in_dim=in_dim, out_dim=out_dim, num_layers=num_layers).to(rank)
@ -674,19 +674,21 @@ def run_fwd_bwd_vschedule_with_optim(test_config):
# assert memory # assert memory
if rank != 0: if rank != 0:
# w.grad: hid_dim * hid_dim * 4(fp32) * 2 (2 layer in each stage) / 1024**3 # w.grad: hid_dim * hid_dim * microbatch * 4(fp32) * 2 (2 layer in each stage) / 1024**3
# output: hid_dim * hid_dim * 4(fp32) / 1024**3 # output: hid_dim * hid_dim * microbatch * 4(fp32) / 1024**3
# optim: state hid_dim * hid_dim * 4(fp32) * 2 (2 layer in each stage) / 1024**3 # optim: state hid_dim * hid_dim * 4(fp32) * 2 (2 layer in each stage) / 1024**3
print(f"rank {rank}: {(after_pp_step_memory - after_init_memory)} <= {(in_dim * in_dim * 4 * 5 / 1024**3)}") print(
# assert (after_pp_step_memory - after_init_memory) <= (in_dim * in_dim * 4 * 5 / 1024**3) f" num_microbatch {num_microbatch} rank {rank}: {(after_pp_step_memory - after_init_memory)} <= {(in_dim * in_dim * 4 * 5 * batch_size / 1024**3)}"
)
assert (after_pp_step_memory - after_init_memory) <= (in_dim * in_dim * 4 * 5 * batch_size / 1024**3)
else: else:
# rank0 will also hold output; # rank0 will also hold output;
print( print(
f"rank {rank}: {round((after_pp_step_memory - after_init_memory), 5)} <= {round((in_dim * in_dim * 4 * 5 / 1024**3 + batch_size * in_dim * in_dim * 4 / 1024**3), 5)}" f" num_microbatch {num_microbatch} rank {rank}: {round((after_pp_step_memory - after_init_memory), 5)} <= {round((in_dim * in_dim * 4 * 5 * batch_size / 1024**3 + batch_size * in_dim * in_dim * 4 / 1024**3), 5)}"
)
assert round((after_pp_step_memory - after_init_memory), 5) <= round(
(in_dim * in_dim * 4 * 5 * batch_size / 1024**3 + batch_size * in_dim * in_dim * 4 / 1024**3), 5
) )
# assert round((after_pp_step_memory - after_init_memory), 5) <= round(
# (in_dim * in_dim * 4 * 5 / 1024**3 + batch_size * in_dim * in_dim * 4 / 1024**3), 5
# )
########################## ##########################
# Fwd bwd for base # Fwd bwd for base