Commit Graph

16 Commits (d1488c8572579c09dcfa780363cb6544cd6c87f4)

Author SHA1 Message Date
Stella Laurenzo 6c702b149f Add a number of kernels and new patterns.
* convolution, convolution_backward, _log_softmax, _log_softmax_backward_data, nll_loss_forward, nll_loss_backward, nll_loss2d_forward, nll_loss2d_backward, copy_
* Extends the recognition logic and metadata for handling inplace transformations, optional tensors, ints, lists and dropped args.
* The kernel_calls generated by test_conv_nllloss_grads.py now convert to ATen.
* The result *almost* comes out as a pure tensor program with the exception of the copy_ op, which I will do some followup work to deal with.
* More progress on #97
2020-11-04 14:36:59 -08:00
Harsh Menon c2d3820e48 Fix insertion point bug #102
The current code was inserting all build_list ops
after the last constant op since it was assuming that all
elements being passed in were constants.

This patch replaces that patch with a new function that
inserts the build_list ops before the terminator.

Also modifies test_export_conv2d_fwd.py since its output
no longer matches.

TEST: Added test_export_cat.py which is the code in #102
2020-11-02 16:41:26 -08:00
Stella Laurenzo 0c73c535d6 Capture backward conv and copy_ kernels.
* This is sufficient to capture the forward and backward pass and gradients of a convolutional model with an nllloss.
* As with the forward conv, the backward conv is a special case wrapped in an enigma on the PyTorch side. There aren't many like it, so special casing is just what we do.
* When I traced this, I found that the copy_ op is not yet boxing compatible so I had to map it manually. If there are many more like this, I'll probably do something a bit more clever to reduce duplication.
* This exposes new signature patterns that will need to be handled by the ATen lowering. Will take care of that next: It will be nice to have an e2e of a non-trivial case with full gradients.
* Fixes #97.
2020-10-30 22:59:26 -07:00
Stella Laurenzo 8d98dd4551 Support optional args/returns and other odds and ends.
* None's out Device? args.
* Emits bool tensors if needed.
* Adds some stderr tracing to better see what is going on.
* Test case that exercises NLLLoss.
* This test case emits something for backward calculations but there are some issues still to be worked out, so that part is left out of the test case.
* Progress on #97
2020-10-30 14:50:28 -07:00
Stella Laurenzo 510f226df2 Expose signature metadata to ops and implement ATenRecognizeKernelsPass pass.
* Two op interfaces, one for querying instance metadata and one for getting static data needed to construct an op from a generic form.
* For torch.generic_kernel ops, metadata is splatted in during capture from Torch (it comes from the op registry, which will work for either device capture or graph import).
* Moved the 'add' out of the generated set so I can experiment on it. It implements the TorchBuildableKernelOpInterface interface which provides its metadata.
* The ATenRecognizeKernelsPass pass generically lowers from a torch.generic_kernel to recognized ops that implement the TorchBuildableKernelOpInterface, handling the various types of transformations that we allow at this stage.
2020-10-26 20:31:45 -07:00
Stella Laurenzo 58adb6bd8e Work around various PyTorch issues in support of convolution.
* Enables the conv2d fwd test and ResA (which are both small).
* Deletes resnet18 and vgg, which both run but generate output that crashes FileCheck and lit (or at least makes them take an eternity).
2020-10-21 12:44:31 -07:00
Stella Laurenzo 029815152e Add remaining pieces to capture full example models.
* Adds Basicpy List, Tuple, Dict types and plumbs through C API.
* Started debugging the issues around aten::conv2d capture, but a PyTorch bug is suspected.
* Was able to manually verify that the basic conv2d forward test captures correctly with a workaround.
* Need to resolve some printing issues upstream and move these tests to an integration test target (they take ~seconds to run).
2020-10-19 22:16:59 -07:00
Stella Laurenzo 9e52f6235b More progress on PyTorch acap device capture.
* Now gets far enough to capture batch_norm.
* Has some issues still with in-place ops.
* Can materialize constants.
* Includes an upgrade to PyTorch nightly, which has important bug fixes for fallback and boxed kernel dispatch.
* Fixes #78, #79, #80.
* Will do more testing in a follow-up once further bugs are fixed that facilitate getting at the other features.
2020-10-15 21:43:21 -07:00
Stella Laurenzo 30cfc6499f Create public API for torch_mlir python code.
* Adds a trampoline/loader 'torch_mlir' module.
* Plumbs through the MLIR python Context and Module creation, interoping with the MLIR Python API (resolves TODO on creating with own context and accessing the module being built).
* Inter-module Python API interop is still a bit rough but workable via the capsule mechanism. Can be evolved later.
* Exports the frontends/pytorch python sources to the project python/ build directory.
* Requires D89294 to land.
2020-10-13 16:36:49 -07:00
Stella Laurenzo af4edb63ae Start reworking towards a shared library build.
* Need to have a dag of shared library deps in order to interop across python extensions (as presented in ODM).
* Introduced add_npcomp_library and friends to mirror the MLIR setup.
* Adds a libNPCOMP.so shared library.
* Redirects tools and extensions to link against libNPCOMP.so (instead of static libs).
* Moves all libraries to lib/, all binaries to bin/ and all python extensions to python/. The invariant is that the rpaths are setup to have a one level directory structure.
* Reworks the _torch_mlir extension to build like the others (still need to come up with a consolidated rule to do this instead of open coded).
* Includes an upstream version bump to pick up needed changes.

Sizes with dynamic linking (stripped, release, asserts enabled):
  libNPCOMP.so: 43M (includes much of the underlying LLVM codegen deps)
  libMLIR.so: 31M
  _npcomp.so: 1.6M (python extension)
  _torch_mlir.so: 670K (python extension)
  npcomp-capi-ir-test: 6.3K
  npcomp-opt: 351K
  npcomp-run-mlir: 461K
  mnist-playground: 530K

Still more can be done to normalize and optimize but this gets us structurally to the starting point.
2020-10-09 16:02:58 -07:00
Stella Laurenzo 3ccc2214a7 Set PyTorch captured function return type.
* Resolves various TODOs that required an LLVM change/bump.
* Bumps LLVM to 4aa217160e5f06a96c6effc4950c3b402374de58
2020-10-07 10:14:34 -07:00
Stella Laurenzo ad3ddb9edb Implement torch.kernel_call capture.
* Had to stop short of modifying the function return signature because of a missing C-API upstream.
* Committing here is good enough for a test and will resolve the various TODOs about upstream APIs next.
2020-10-06 21:54:28 -07:00
Stella Laurenzo e5433e314f Add capture function arguments.
* Adds at::Tensor -> MlirValue tracking.
* Adds conversions for tensor and scalar types to MLIR types.
* Adds npcomp C APIs for constructing custom types.
* Reworks pybind include so as to get Torch pybind helpers (needed to pass at::Tensor type from Python->C++).
2020-10-01 18:59:58 -07:00
Stella Laurenzo ba03ecc652 Add public API for constructing a module/function to capture PyTorch ops.
* Uses the MLIR-C API since that will save us a lot of grief down the road (i.e. will give PyTorch and libMLIR/libNPCOMP the ability to skew version-wise).
* Quite a few TODOs and not yet populating the function in any way.
2020-09-29 14:23:22 -07:00
Stella Laurenzo b5f010284f Add boilerplate to do device capture (pytorch 1.6).
* Uses the new dispatcher API.
* Just prints to the console for the moment when an op is captured.
* Executes the op through the existing implementation.
2020-09-28 10:30:54 -07:00
Stella Laurenzo 0d91885965
Add initial python bindings for c10 dispatcher internals. (#55)
* Exposes the op registry via a get_registered_ops method.
* Moves the aten dialect generation scripts in prep for integrating them with this facility.
2020-09-24 16:26:29 -07:00