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wassname
2025-03-12 15:30:33 +08:00
parent 756b653913
commit 6fed0032f2
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activation_store/collect.py
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@@ -17,7 +17,7 @@ from torch import Tensor
default_output_folder = (Path(__file__).parent.parent / "outputs").resolve()
@torch.no_grad()
def default_postprocess_result(input: dict, trace: TraceDict, output: ModelOutput, model: AutoModelForCausalLM, last_token=False, dtype=torch.float16) -> Dict[str, Tensor]:
def default_postprocess_result(input: dict, trace: TraceDict, output: ModelOutput, model: AutoModelForCausalLM, last_token=True, dtype=torch.float16) -> Dict[str, Tensor]:
"""Make your own. This adds activations to output, and rearranges hidden states.
Note the parquet write support float16, so we use that. It does not support float8, bfloat16, etc.