pytorch

e47e946b - [aotinductor] Use dynamic_shape instead of constraints (#110360)

[aotinductor] Use dynamic_shape instead of constraints (#110360) Summary: Previously we used export's constraints to specify all batch-size dimensions being dynamic. This is done by creating 1 constraint `dynamic_dim(inp[0][0], lower, upper)`, followed by `dynamic_dim(inp[0][0]) == dynamic_dim(inp[i][0])` for every input `i`. Through the new `dynamic_shapes` API, we can use `Dims("batch_size")` on every dimension to specify which dimensions are dynamic and equal to each other, and `None` otherwise: `{i: [Dims("batch_size", lower, upper), None] for every input i}` Note: `dynamic_shapes` and `constraints` utilize the same "constraints" backend so this diff should be idempotent. Test Plan: `buck2 run @//mode/dev-nosan //caffe2/torch/fb/model_transform/experimental/benchmark/test/aotinductor:test_aot_inductor_benchmark` Reviewed By: chenyang78, aakhundov Differential Revision: D49784351 Pull Request resolved: https://github.com/pytorch/pytorch/pull/110360 Approved by: https://github.com/desertfire