Comments (1)
I thought of dynamic shapes as like C++ vectors; there's allocated space and something separate that indicates how much of that space you are actually using. You might cache particular compiled combinations of max sizes for inputs. If you are a server, dynamic batch size can help with latency since you would only need to compute for as many samples as you had ready. You could also imagine kernels that could make use of knowing actual sample lengths to reduce the computation in those transformer GEMMs (some hardware skips 0 arithmetic and some hardware does a tile of GEMM in the same amount of time as a partial tile, so it wouldn't matter for them). Whatever Intel did with ngraph along those lines would be in the OpenVINO repo.
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Related Issues (20)
- Installs an empty directory hierarchy under include/ngraph/frontend/ATen HOT 1
- Retrieving LLVM IR using ngraph HOT 1
- Does ngraph support importing a control flow graph into ngraph? HOT 1
- the debug and release mode
- NGraph node cache error HOT 8
- TypeError: Failed to convert object of type <class ‘plaidml.tile.Value’> to Tensor. HOT 4
- openvino error HOT 16
- Pybind11 error when building nGraph wheel HOT 2
- Feature request: GCPU code generation. HOT 1
- Integrating ngraph into Godot Engine HOT 2
- How to implement Depthwise_Convolution via GroupConvolution? HOT 3
- Failed to implement v1::TopK, always get value but not index as output HOT 1
- Missing type name check for distinguishing between bfloat16 and float16 when instantiating element::Type in ngraph deserializer HOT 1
- Are batch sizes fixed in ngraph? HOT 6
- error: ‘cudnnSetRNNDescriptor’ was not declared in this scope; did you mean ‘cudnnSetLRNDescriptor HOT 1
- error: ‘cudnnSetRNNDescriptor’ was not declared in this scope -- cudnn 8.2.0 ...
- src.c:(.text+0x46): undefined reference to `pthread_create' HOT 1
- No matching distribution found for ngraph-core HOT 1
- Is this a defunct project? HOT 3
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