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➜ SHARK git:(bloom) ✗ python tank/bloom_model.py | |
Some weights of BloomForSequenceClassification were not initialized from the model checkpoint at bigscience/bloom-560m and are newly initialized: ['score.weight'] | |
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference. | |
/home/chi/src/ubuntu20/shark/SHARK/shark.venv/lib/python3.10/site-packages/torch/jit/_check.py:181: UserWarning: The TorchScript type system doesn't support instance-level annotations on empty non-base types in `__init__`. Instead, either 1) use a type annotation in the class body, or 2) wrap the type in `torch.jit.Attribute`. | |
warnings.warn("The TorchScript type system doesn't support " | |
/home/chi/src/ubuntu20/shark/SHARK/shark.venv/lib/python3.10/site-packages/torch/jit/_trace.py:744: UserWarning: The input to trace is already a ScriptModule, tracing it is a no-op. Returning the object as is. | |
warnings.warn( | |
Target triple found:x86_64-linux-gnu | |
tensor([[ 7.2041, -17.0263]], grad_fn=<Inde |
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python tank/bloom_model.py | |
with torch_mlir_lockstep_tensor.py | |
...... | |
...... | |
Mismatched elements: 131059 / 131072 (100%) | |
Max absolute difference: 2.3001497 | |
Max relative difference: 2833.5105 | |
x: array([[[-0.013242, -0.013242, -0.013242, ..., -0.013242, -0.013242, |
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Args: ./../torch-mlir/build/bin/torch-mlir-opt -pass-pipeline=torch-backend-to-linalg-on-tensors-backend-pipeline --debug ./shark_tmp/_lambda.mlir | |
Load new dialect in Context builtin | |
ImplicitTypeIDRegistry::lookupOrInsert(mlir::SubElementTypeInterface) | |
ImplicitTypeIDRegistry::lookupOrInsert(mlir::ShapedType) | |
ImplicitTypeIDRegistry::lookupOrInsert(mlir::MemRefLayoutAttrInterface) | |
ImplicitTypeIDRegistry::lookupOrInsert(mlir::SubElementAttrInterface) | |
ImplicitTypeIDRegistry::lookupOrInsert(mlir::ElementsAttr) | |
ImplicitTypeIDRegistry::lookupOrInsert(mlir::TypedAttr) | |
ImplicitTypeIDRegistry::lookupOrInsert(mlir::SymbolOpInterface) | |
ImplicitTypeIDRegistry::lookupOrInsert(mlir::OpAsmOpInterface) |
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