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Historically, DML was only able to fuse partitions when all sizes are known in advance or when we were overriding them at session creation time. But in practice, it should be possible to compile partitions at compute time if the caller knows that the dimensions won't be changed for every inference (e.g. resizing a webcam window, or padding the input to powers of 2). This graph will be cached and reused until the sizes change. This is an opt-in option gated under the `enable_dynamic_graph_fusion` option, which means that it will only be enabled when the caller requests it since they have more context on how their model will be called between inferences. This PR also adds the option to disable metacommands from the python API, which is an option for the C API but was lacking for python. |
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