pytorch

aa49aa85 - Tensor type set (#25308)

Tensor type set (#25308) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/25308 Instead of storing a single TensorTypeId in a Tensor, we store a bitset of tensor type IDs in a Tensor, TensorTypeSet. This class comes with some unit tests. This is in preparation for making Variable a TensorTypeId. In order to help flush out places where this makes a semantic difference, we rename `Tensor::type_id()` to `Tensor::type_set()` and smoke out all of the locations where this was semantically meaningful. Because the new tensor type set is 64-bits, this increases the size of Tensor by a word. Listing of semantic changes: * Many TensorImpl related constructors just propagate TensorTypeId to a parent constructor. These are pretty simple to adjust. * Backend extensions are now in the business of explicitly constructing a TensorTypeSet and then passing it in. This is probably OK for now but when Variable drops, these dispatch IDs may get immediately overwritten to have Variable set. * `sparseTensorSetToDeviceType` and similar functions previously did an equality test with TensorTypeId, to determine what an appropriate device type is. This equality is now replaced with a set inclusion test. This is valid, under the assumption that we don't ever have weird sets like "this tensor is simultaneously a sparse CPU tensor and a sparse CUDA tensor", which will be true in the short term plan of adding Variable to the dispatch ID. * `impl::dispatchTypeId` was generally introduced for cases where we legitimately need to convert from `TensorTypeSet -> TensorTypeId` in a dispatch related manner. At the moment, the implementation is trivial, but they will soon be adjusted to handle TLS. I've tried to make these call sites as forwards compatible as possible: * `checked_tensor_unwrap` and co now use `dispatchTypeId`. When Variable is added to the type set, these will always be called in a context where the Variable type ID is disabled, so we will get the correct underlying tensor type ID. * Uses of `Backend` in dispatch are now replaced with `TensorTypeSet`. The general heuristic here for whether or not to accept a `TensorTypeId` or `TensorTypeSet` is that we want to make the generated code as simple as possible. It is easier to retrieve a `TensorTypeSet`, so that's a more appropriate API in these cases. * In some cases, I could not conveniently switch an implementation to the new semantics, because it was blocked on some other refactor. In this case, I introduced `legacyExtractTypeId`, which gives what would be a BC-compatible `TensorTypeSet` to `TensorTypeId` implementation that will continue to report the same values it would have prior to this change. This is **different** from `dispatchTypeId`, because this function does NOT respect TLS; it always ignores Variable type IDs. * c10 dispatcher tests, which are oblivious to Variable dispatch, use this BC function (actually, they use `extractTypeId`, an overload for Tensor. * The implementation of `new_*` methods heavily relies on tensor type ID, I chose not to unwind this. PR to refactor this at https://github.com/pytorch/pytorch/pull/25475 * Slicing also relies on tensor type ID, see `torch/csrc/autograd/python_variable_indexing.cpp` (though in some cases in this file, I was able to replace use of tensor type ID with TensorOptions) * In some cases, there is an equality test on tensor type ID which would be better done by testing "tensor axes". In those cases, I replaced those equality tests with more equality tests. * Example: `torch/csrc/nn/type_checks.h` * There is a total punt in `torch/csrc/tensor/python_tensor.cpp` where "instance of" checking is done via dispatch ids. In general, the Variable-ness of a tensor doesn't participate in instanceof testing. It's not entirely clear what to do here. * Instead of storing `Backend` in `VariableInfo`, we now just store Layout. c10 dispatcher test updates were done with: ``` :%s/\([^ ]\+\)\.type_id()/extractTypeId(\1)/g :%s/\([^( ]\+\)->type_id()/extractTypeId(*\1)/g ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/25308 Differential Revision: D17092791 Test Plan: sandcastle and ossci Reviewed By: bwasti Pulled By: ezyang fbshipit-source-id: 22207d14fe62dd31ee19cc5011af22e3d9aabb5b