Commit Graph

7 Commits

Author SHA1 Message Date
Mikhail Zolotukhin
d784636b39 Scope: Move implementations from .h to .cpp file. (#20593)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20593
ghimport-source-id: e1e9a7f98158c23adf02d5ed2763ab1e33bb2997

Differential Revision: D15375134

Pulled By: ZolotukhinM

fbshipit-source-id: 8d8e0c1e0ef7697ded59a4b19e2d9de7c5230294
2019-05-16 13:18:04 -07:00
Mikhail Zolotukhin
862d466bef Remove redundant includes from scope.h and attributes.h
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/16472

Differential Revision: D13852553

Pulled By: ZolotukhinM

fbshipit-source-id: d5634982c2c42e704d9902774a77660e05fd71eb
2019-01-28 23:47:15 -08:00
Mikhail Zolotukhin
47bf30661f Directly include headers from ATen.
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/16287

Differential Revision: D13792949

Pulled By: ZolotukhinM

fbshipit-source-id: d627d8dc469df048063c70d0b5b8d33fede809a3
2019-01-24 11:22:27 -08:00
Michael Suo
f636dc9276 clang format world (#15524)
Summary:
The PR clang-formats everything in `torch/csrc/jit/` and adds it to the pre-commit hook.

Here is a list of non-mechanical changes:
- I went over each file and fixed up whenever I could tell that clang-format was clobbering comment formatting.
- Made the macros in register_prim_ops a little more clang-format friendly by omitting trailing commas
- Refactored autodiff.cpp to use a helper class with explicit state rather than a bunch of capturing lambdas
- Small improvements to the precommit hook clang-format
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15524

Differential Revision: D13547989

Pulled By: suo

fbshipit-source-id: 3ff1541bb06433ccfe6de6e33f29227a2b5bb493
2018-12-26 06:55:01 -08:00
Edward Yang
517c7c9861 Canonicalize all includes in PyTorch. (#14849)
Summary:
Anywhere we used #include "foo.h", we now say #include <foo.h>
Paths are adjusted to be rooted out of aten/src, torch/lib, or
the root level directory.

I modified CMakeLists.txt by hand to remove TH and THC from
the include paths.

I used the following script to do the canonicalization:

```
  import subprocess
  import re
  import os.path

  files = subprocess.check_output(['git', 'ls-files']).decode('utf-8').rstrip().split('\n')
  for fn in files:
      if not any(fn.endswith(suff) for suff in ['.cu', '.cpp', '.in', '.h', '.hpp', '.cu', '.cuh', '.cc']):
          continue
      if not any(fn.startswith(pref) for pref in ["aten/", "torch/"]):
          continue
      with open(fn, 'r') as f:
          c = f.read()
      def fmt(p):
          return "#include <{}>".format(p)
      def repl(m):
          p = m.group(1)
          if p in ["dlfcn.h", "unistd.h", "nvrtc.h", "cuda.h", "cuda_runtime.h", "cstdint", "cudnn.h", "Python.h", "cusparse.h", "cuda_runtime_api.h", "cuda_fp16.h", "cublas_v2.h", "stdint.h", "curand_kernel.h"]:
              return fmt(p)
          if any(p.startswith(pref) for pref in ["torch/csrc", "c10/", "ATen/", "caffe2/", "TH/", "THC/", "Eigen/", "gtest/", "zdl/", "gloo/", "onnx/", "miopen/"]):
              return fmt(p)
          for root in ["aten/src", "torch/lib", ""]:
              for bad_root in [os.path.dirname(fn), "aten/src/TH", "aten/src/THC", "torch/csrc"]:
                  new_p = os.path.relpath(os.path.join(bad_root, p), root)
                  if not new_p.startswith("../") and (os.path.exists(os.path.join(root, new_p)) or os.path.exists(os.path.join(root, new_p + ".in"))):
                      return fmt(new_p)
          print("ERROR: ", fn, p)
          return m.group(0)
      new_c = re.sub(r'#include "([^"]+)"', repl, c)
      if new_c != c:
          print(fn)
          with open(fn, 'w') as f:
              f.write(new_c)
```

Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14849

Reviewed By: dzhulgakov

Differential Revision: D13363445

Pulled By: ezyang

fbshipit-source-id: 52361f878a672785f9306c9e9ab2513128092b68
2018-12-08 19:38:30 -08:00
Zachary DeVito
aef9e76283 Get pretty printer ready for use as a serialization format (#13616)
Summary:
Get pretty printer ready for use as a serialization format

This PR adds a bunch of functionality to the pretty printer (now called python_printer to reflect
the fact that it will be used to output valid python source). The idea is to get the printer
ready for use as serialization format.  This PR does not have tests beyond what the pretty
printer already had. PRs stacked on this one will do round-trip export/import to test this functionality more robustly.

Notes:
* PythonPrinter is an evolution of the original pretty printer. However, much of it has changed so it is best just to
  read it as a new implementation. Trying to correlate it to the original implementation is probably not much help.
* The printer tries to get reasonably close to how the original function was likely written, such as
  writing expressions rather than making intermediates when possible. We may decide to turn this off
  for the actual serialization, but it is useful for pretty printing.
* tensor field access was changed so that prim::device and family have schema
* fixed a bug in the compiler where setUniqueName gets called even when a value already has one.
  this sometimes assigned really poor names to graph inputs
* Graph::insert gains an optional range argument to make range-preserving inserts easier.
* prim:: ops that can have schema now have schema. This is because when we parse them back in,
  we will need the schema to correctly set their output types.
* there is code in the python printer to complain if you try to add a prim op and do not update the printer.
* BuiltinModule is generalized to take an operator namespace and a version number for work in future commits.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13616

Reviewed By: goldsborough

Differential Revision: D13008252

Pulled By: zdevito

fbshipit-source-id: 32b33bc6410d6ca1c6f02bd6e050f8d5eea32083
2018-11-12 10:21:30 -08:00
Orion Reblitz-Richardson
046672eed5 Set proper scope on nodes added by JIT (#12400)
Summary:
In order to support tensorboardX and other visualization tools, we need to make sure a non-empty scope is set on all nodes added by the JIT. This attempts to do this, but is still a WIP.

This is a new version of https://github.com/pytorch/pytorch/pull/10749
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12400

Reviewed By: ezyang

Differential Revision: D10224380

Pulled By: orionr

fbshipit-source-id: d1bccd0eee9ef7c4354112c6a39a5987bfac2994
2018-10-24 09:05:46 -07:00