mirror of https://github.com/llvm/torch-mlir
25 lines
813 B
Python
25 lines
813 B
Python
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import torch
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import torch_mlir
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from transformers import BertForMaskedLM
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# Wrap the bert model to avoid multiple returns problem
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class BertTinyWrapper(torch.nn.Module):
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def __init__(self) -> None:
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super().__init__()
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self.bert = BertForMaskedLM.from_pretrained("prajjwal1/bert-tiny", return_dict=False)
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def forward(self, data):
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return self.bert(data)[0]
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model = BertTinyWrapper()
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model.eval()
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data = torch.randint(30522, (2, 128))
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out_stablehlo_mlir_path = "./bert_tiny_stablehlo.mlir"
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module = torch_mlir.compile(model, data, output_type=torch_mlir.OutputType.STABLEHLO, use_tracing=True)
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with open(out_stablehlo_mlir_path, "w", encoding="utf-8") as outf:
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outf.write(str(module))
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print(f"StableHLO IR of tiny bert successfully written into {out_stablehlo_mlir_path}")
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