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bigdl-llm: 2.5.0b20240321, all-in-one benchmark tools:
8k prompt refers https://github.com/intel/xFasterTransformer/blob/main/benchmark/prompt.json
2024-03-22 20:38:03,260 - INFO - intel_extension_for_pytorch auto imported
Loading checkpoint shards: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:04<00:00, 1.52it/s]
2024-03-22 20:38:08,095 - INFO - Converting the current model to sym_int4 format......
loading of model costs 8.393956548999995s and 3.583984375GB
<class 'transformers_modules.chatglm3-6b.modeling_chatglm.ChatGLMForConditionalGeneration'>
/build/intel-pytorch-extension/csrc/gpu/aten/operators/Indexing.h:670: operator(): global id: [524544,0,0], local id: [256,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed
/build/intel-pytorch-extension/csrc/gpu/aten/operators/Indexing.h:670: operator(): global id: [524545,0,0], local id: [257,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed
/build/intel-pytorch-extension/csrc/gpu/aten/operators/Indexing.h:670: operator(): global id: [524546,0,0], local id: [258,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed
/build/intel-pytorch-extension/csrc/gpu/aten/operators/Indexing.h:670: operator(): global id: [524547,0,0], local id: [259,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed
/build/intel-pytorch-extension/csrc/gpu/aten/operators/Indexing.h:670: operator(): global id: [524548,0,0], local id: [260,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed
/build/intel-pytorch-extension/csrc/gpu/aten/operators/Indexing.h:670: operator(): global id: [524549,0,0], local id: [261,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed
The text was updated successfully, but these errors were encountered:
As we test, when the input length is larger than 8166, it will show the same error as above. When the input length is smaller or equal to 8166, it will show the error that is similar to llama2 8k issue, which is the IPEX allocation error:
The root cause should be the same. Need further investigation.
bigdl-llm: 2.5.0b20240321, all-in-one benchmark tools:
8k prompt refers https://github.com/intel/xFasterTransformer/blob/main/benchmark/prompt.json
2024-03-22 20:38:03,260 - INFO - intel_extension_for_pytorch auto imported
Loading checkpoint shards: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:04<00:00, 1.52it/s]
2024-03-22 20:38:08,095 - INFO - Converting the current model to sym_int4 format......
The text was updated successfully, but these errors were encountered: