from pytorch_pretrained_bert import BertForMaskedLM import torch
def main(args): bert_model_origin = BertForMaskedLM.from_pretrained("bert-large-uncased") example_tensor = torch.randint(0, 100, (1, 256)) model_int8 = torch.quantization.quantize_dynamic(bert_model_origin, quant_layers={torch.nn.Linear}, dtype=torch.qint8) model_int8.eval() trace_model = torch.jit.trace(model_int8, [example_tensor]) trace_model.eval() shape_list = [(i.debugName().split('.')[0], i.type().sizes()) for i in list(trace_model.graph.inputs())[1:]] mod_bert, params_bert = tvm.relay.frontend.pytorch.from_pytorch(trace_model, shape_list) target = tvm.target.Target(target="llvm", host="llvm") with tvm.transform.PassContext(opt_level=3): lib = relay.build(mod_bert, target=target, params=params_bert) lib.export_library(os.path.realpath("net_int18_cpu.tar")) see code above, when build pre-quantization bert-large masked lm model, it will a failure like this:  --- [Visit Topic](https://discuss.tvm.apache.org/t/bert-large-masked-lm-pre-quantization-model-build-failed/11800/1) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/09fcdf5ea934d061b9ce23c6c4b15ce30bc7c2e04310c2c62df33066be3f6a47).