Commit Graph

36 Commits

Author SHA1 Message Date
PyTorch MergeBot
44436947bc Revert "Reland PySymInt (#79617)"
This reverts commit 8ef6356f26.

Reverted https://github.com/pytorch/pytorch/pull/79617 on behalf of https://github.com/zengk95 due to this is breaking periodic jobs (and maybe pull) on trunk
2022-06-16 19:40:27 +00:00
Nikolay Korovaiko
8ef6356f26 Reland PySymInt (#79617)
Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/79617
Approved by: https://github.com/Chillee
2022-06-16 04:18:06 +00:00
PyTorch MergeBot
b8db0a0475 Revert "Python Bindings for SymInts (#78135)"
This reverts commit d332724071.

Reverted https://github.com/pytorch/pytorch/pull/78135 on behalf of https://github.com/ezyang due to broke torchvision tests
2022-06-15 13:52:14 +00:00
Nikolay Korovaiko
d332724071 Python Bindings for SymInts (#78135)
This PR adds support for `SymInt`s in python. Namely,
* `THPVariable_size` now returns `sym_sizes()`
* python arg parser is modified to parse PyObjects into ints and `SymbolicIntNode`s
* pybind11 bindings for `SymbolicIntNode` are added, so size expressions can be traced
* a large number of tests added to demonstrate how to implement python symints.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/78135
Approved by: https://github.com/ezyang
2022-06-14 02:17:59 +00:00
Michael Suo
30fb2c4aba [lint] autoformat test/cpp and torch/csrc
Let's have some fun.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/78828

Approved by: https://github.com/ezyang
2022-06-11 21:11:16 +00:00
Nikita Shulga
a9b0a921d5 Disable avoid-non-const-global-variables lint check (#62008)
Summary:
As GoogleTest `TEST` macro is non-compliant with it as well as `DEFINE_DISPATCH`

All changes but the ones to `.clang-tidy` are generated using following script:
```
for i in `find . -type f -iname "*.c*" -or -iname "*.h"|xargs grep cppcoreguidelines-avoid-non-const-global-variables|cut -f1 -d:|sort|uniq`;  do sed -i "/\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)/d" $i; done
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/62008

Reviewed By: driazati, r-barnes

Differential Revision: D29838584

Pulled By: malfet

fbshipit-source-id: 1b2f8602c945bd4ce50a9bfdd204755556e31d13
2021-07-22 18:04:40 -07:00
Richard Barnes
349f2f767c Modernize to default constructor and nullptr in torch (#61735)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/61735

Test Plan: Sandcastle

Reviewed By: malfet

Differential Revision: D29716659

fbshipit-source-id: ec2a0a0b7e55d2e50b1d35f0b651bd40675ae7e8
2021-07-16 10:51:13 -07:00
Richard Barnes
e3d75b8475 irange for PyTorch sans jit (#59481)
Summary:
Switches most of the simple for loops outside of `jit` directories to use `c10::irange`.

Generated with D28874212.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/59481

Test Plan: Sandcastle

Reviewed By: ngimel

Differential Revision: D28909681

fbshipit-source-id: ec9ab1bd602933238d9d0f73d4d8d027b75d9d85
2021-06-09 14:46:11 -07:00
Nikita Shulga
4cb534f92e Make PyTorch code-base clang-tidy compliant (#56892)
Summary:
This is an automatic change generated by the following script:
```
#!/usr/bin/env python3
from subprocess import check_output, check_call
import os

def get_compiled_files_list():
    import json
    with open("build/compile_commands.json") as f:
        data = json.load(f)
    files = [os.path.relpath(node['file']) for node in data]
    for idx, fname in enumerate(files):
        if fname.startswith('build/') and fname.endswith('.DEFAULT.cpp'):
            files[idx] = fname[len('build/'):-len('.DEFAULT.cpp')]
    return files

def run_clang_tidy(fname):
    check_call(["python3", "tools/clang_tidy.py", "-c", "build", "-x", fname,"-s"])
    changes = check_output(["git", "ls-files", "-m"])
    if len(changes) == 0:
        return
    check_call(["git", "commit","--all", "-m", f"NOLINT stubs for {fname}"])

def main():
    git_files = check_output(["git", "ls-files"]).decode("ascii").split("\n")
    compiled_files = get_compiled_files_list()
    for idx, fname in enumerate(git_files):
        if fname not in compiled_files:
            continue
        if fname.startswith("caffe2/contrib/aten/"):
            continue
        print(f"[{idx}/{len(git_files)}] Processing {fname}")
        run_clang_tidy(fname)

if __name__ == "__main__":
    main()
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/56892

Reviewed By: H-Huang

Differential Revision: D27991944

Pulled By: malfet

fbshipit-source-id: 5415e1eb2c1b34319a4f03024bfaa087007d7179
2021-04-28 14:10:25 -07:00
Edward Yang
6ec71ed4f9 Replace all direct cdata access with THPVariable_Unpack (#55799)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55799

I'm going to change the implementation of cdata soon so I need to
abstract over cdata access with a function.  Additionally, many
users are casting manually casting to THPVariable to access
the member so I can remove these unsafe casts in the client code
(the implementation, of course, is still doing an unsafe cast.)

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Test Plan: Imported from OSS

Reviewed By: albanD

Differential Revision: D27712130

Pulled By: ezyang

fbshipit-source-id: 95fcc013bf3913d67f2c634068eb5b3aab144cb3
2021-04-15 08:57:04 -07:00
peterjc123
815d38395a PyLong_{As/From}{Long/UnsignedLong} lint checks (#49280)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/45581

Pull Request resolved: https://github.com/pytorch/pytorch/pull/49280

Reviewed By: mruberry

Differential Revision: D25592330

Pulled By: ezyang

fbshipit-source-id: 5c16d6aed88ad1feaa7f129b4cd44c0561be2de2
2020-12-17 09:32:08 -08:00
Pritam Damania
2b221a9599 Remove PyCFunction casts as much as possible. (#46227)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/46227

Follow up from https://github.com/pytorch/pytorch/issues/45419, in
this PR I've removed as many PyCFunction casts as I could from the codebase.

The only ones I didn't remove were the ones with `METH_VARARGS | METH_KEYWORDS`
which have 3 parameters instead of 2 and had to be casted. Example: `
{"copy_", (PyCFunction)(void(*)(void))THPStorage_(copy_), METH_VARARGS |
METH_KEYWORDS, nullptr},`
ghstack-source-id: 114632704

Test Plan: waitforbuildbot

Reviewed By: albanD

Differential Revision: D24269435

fbshipit-source-id: 025cfd43a9a2a3e59f6b2951c1a78749193d77cf
2020-10-20 15:01:51 -07:00
David Reiss
6d642a6f6c Remove (most) Python 2 support from C++ code (#35614)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35614

Python 2 has reached end-of-life and is no longer supported by PyTorch.
Now we can clean up a lot of cruft that we put in place to support it.
These changes were all done manually, and I skipped anything that seemed
like it would take more than a few seconds, so I think it makes sense to
review it manually as well.

Test Plan: CI

Differential Revision: D20842876

Pulled By: dreiss

fbshipit-source-id: 18abf0d324ed2185ec6d27c864e935d856dcc6ad
2020-05-14 15:01:49 -07:00
Michael Suo
dbe850af5b [jit] do the code reorg (#33851)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/33851

Rationale and context described in #33828.

Script to reproduce the move:
https://gist.github.com/suo/16cbefaaeb67ca5a7c6caffd49b7f6e9
ghstack-source-id: 99079645

Test Plan: Make sure CI passes

Reviewed By: jamesr66a

Differential Revision: D20133869

fbshipit-source-id: 390e9241a9c85366d9005c492ac31f10aa96488e
2020-02-27 13:02:51 -08:00
vishwakftw
86c64440c9 Make PyTorch Python 3.8 compatible (#29302)
Summary:
PEP 590 modifies the `tp_print` offset to `tp_vectorcall_offset` - which requires a Py_ssize_t object.
Passing a nullptr caused compatibility issues for Python 3.8.

Changelog:
- Modify all occurrences of `nullptr  /* tp_print */` to 0  /* tp_vectorcall_offset */
- Minor formatting changes
Pull Request resolved: https://github.com/pytorch/pytorch/pull/29302

Test Plan:
- Local fresh build with Python 3.8 completed successfully.

Fixes https://github.com/pytorch/pytorch/issues/28060.
Fixes https://github.com/pytorch/pytorch/issues/29162.

Supersedes https://github.com/pytorch/pytorch/pull/28364

Differential Revision: D18372022

Pulled By: ezyang

fbshipit-source-id: 8e9a15b0d0f72101ccc69bd489f5efa216b880bb
2019-11-07 09:20:19 -08:00
Ralf Gommers
1b4951d3a5 Fix remaining invalid function cast warnings that show up with GCC 8/9 (#26104)
Summary:
Follow-up to gh-25483, more of the same fixes for warnings like:

```
../torch/csrc/autograd/python_variable.cpp:503:31: warning: cast between incompatible function types from ‘PyObject* (*)(THPVariable*)’ {aka ‘_object* (*)(THPVariable*)’} to ‘getter’ {aka ‘_object* (*)(_object*, void*)’} [-Wcast-function-type]
  503 |   {"_backward_hooks", (getter)THPVariable_get_backwards_hooks, (setter)THPVariable_set_backwards_hooks, nullptr, nullptr},
      |                               ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```

This takes the build log output for a full rebuild with GCC 9.1 from ~10,000 to ~7,000 lines.

`clang-tidy` is going to complain, no way around that - see discussion at the end of gh-25483.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26104

Differential Revision: D17396831

Pulled By: ezyang

fbshipit-source-id: d71696bfe4dbe25519e4bcb7753151c118bd39f7
2019-09-17 07:43:37 -07:00
Ailing
c68119387d serialize torch.Size object (#20952)
Summary:
fixes https://github.com/pytorch/pytorch/issues/20823
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20952

Differential Revision: D15514274

Pulled By: ailzhang

fbshipit-source-id: 8340a40fadfd06063f7f33b0d99d693e74d5defb
2019-06-25 10:44:35 -07:00
Ronan Lamy
742568e7eb PyPy compatibility: let unmodified slots be inherited in the standard way (#17837)
Summary:
This is needed to fix a segfault on PyPy 3.6, see https://bitbucket.org/pypy/pypy/issues/2968/segfault-calling-cpyext_tp_new_tuple and https://github.com/pytorch/pytorch/issues/17835
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17837

Differential Revision: D14399408

Pulled By: soumith

fbshipit-source-id: 75328a30018313d3223dd3e3eef9240a416c049b
2019-03-09 11:42:16 -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
Peter Goldsborough
d6c53328f9 Large scale fix of python-related files in torch/csrc/
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/14515

Differential Revision: D13247966

Pulled By: goldsborough

fbshipit-source-id: 7a127c508fc576a7a92626dd6b729f660162d628
2018-12-07 13:04:46 -08:00
Sam Gross
21ff6de4b3 Add missing HANDLE_TH_ERRORS (#12770)
Summary:
THPSize_pynew is called from the Python C API and may throw exceptions.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12770

Differential Revision: D10431180

Pulled By: colesbury

fbshipit-source-id: 93dd1b604ac6bc05d4eb02b97e3f79a73aec73c5
2018-10-17 13:52:02 -07:00
Tongzhou Wang
83a1ab2136 Sparse tensor printing; add NotImplemented autograd fn (#10181)
Summary:
Commits:

1. Add autograd function `NotImplemented` (subclass of `Error`) so python `grad_fn` prints nicer. Since `Error` is used in `DelayedError` to implement `oncedifferentiable`, I can't just change its name. cc colesbury

2. Add printing for sparse tensors. Fixes https://github.com/pytorch/pytorch/issues/9412 . cc weiyangfb The controller you requested could not be found. .

3. Add tests for sparse printing

Examples:
```diff
  In [2]: x = torch.sparse.FloatTensor(torch.arange(4).view(2,2), torch.randn(2, 2), [10, 10, 2])

  In [3]: x
  Out[3]:
- torch.sparse.FloatTensor of size (10,10,2) with indices:
- tensor([[0, 1],
-         [2, 3]])
- and values:
- tensor([[-1.1832, -0.5927],
-         [ 0.0831,  0.2511]])
+ tensor(indices=tensor([[0, 1],
+                        [2, 3]]),
+        values=tensor([[ 1.5081,  0.3451],
+                       [-0.0392,  0.4776]]),
+        size=(10, 10, 2), nnz=2, layout=torch.sparse_coo)

  In [4]: x.requires_grad_()
  Out[4]:
- torch.sparse.FloatTensor of size (10,10,2) with indices:
- tensor([[0, 1],
-         [2, 3]], grad_fn=<Error>)
- and values:
- tensor([[-1.1832, -0.5927],
-         [ 0.0831,  0.2511]], grad_fn=<Error>)
+ tensor(indices=tensor([[0, 1],
+                        [2, 3]]),
+        values=tensor([[ 1.5081,  0.3451],
+                       [-0.0392,  0.4776]]),
+        size=(10, 10, 2), nnz=2, layout=torch.sparse_coo, requires_grad=True)

  In [5]: x + x
  Out[5]:
- torch.sparse.FloatTensor of size (10,10,2) with indices:
- tensor([[0, 1],
-         [2, 3]], grad_fn=<Error>)
- and values:
- tensor([[-2.3664, -1.1855],
-         [ 0.1662,  0.5021]], grad_fn=<Error>)
+ tensor(indices=tensor([[0, 1],
+                        [2, 3]]),
+        values=tensor([[ 3.0162,  0.6902],
+                       [-0.0785,  0.9553]]),
+        size=(10, 10, 2), nnz=2, layout=torch.sparse_coo, grad_fn=<AddBackward0>)

  In [6]: x.double()
  Out[6]:
- torch.sparse.DoubleTensor of size (10,10,2) with indices:
- tensor([[0, 1],
-         [2, 3]], grad_fn=<Error>)
- and values:
- tensor([[-1.1832, -0.5927],
-         [ 0.0831,  0.2511]], dtype=torch.float64, grad_fn=<Error>)
+ tensor(indices=tensor([[0, 1],
+                        [2, 3]]),
+        values=tensor([[ 1.5081,  0.3451],
+                       [-0.0392,  0.4776]]),
+        size=(10, 10, 2), nnz=2, dtype=torch.float64, layout=torch.sparse_coo,
+        grad_fn=<NotImplemented>)

  In [7]: x = torch.sparse.FloatTensor(torch.ones(0, 2, dtype=torch.long), torch.randn(2, 0), [0])

  In [8]: x
  Out[8]:
- torch.sparse.FloatTensor of size (0,) with indices:
- tensor([], size=(0, 2), dtype=torch.int64)
- and values:
- tensor([], size=(2, 0))
+ tensor(indices=tensor([], size=(0, 2)),
+        values=tensor([], size=(2, 0)),
+        size=(0,), nnz=2, layout=torch.sparse_coo)

  In [9]: x = torch.sparse.FloatTensor(torch.ones(0, 2, dtype=torch.long), torch.randn(2), [])

  In [10]: x
  Out[10]:
- torch.sparse.FloatTensor of size () with indices:
- tensor([], size=(0, 2), dtype=torch.int64)
- and values:
- tensor([-0.0064,  0.8518])
+ tensor(indices=tensor([], size=(0, 2)),
+        values=tensor([ 0.9800, -0.5978]),
+        size=(), nnz=2, layout=torch.sparse_coo)
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10181

Differential Revision: D9139845

Pulled By: SsnL

fbshipit-source-id: 353eebd55fac4049ed9bf85f8b0ee2c1418a744e
2018-09-05 19:41:22 -07:00
Peter Goldsborough
7ddc6f84c4 NULL -> nullptr (#11047)
Summary:
How did we get so many uses of `NULL` again?

ezyang
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11047

Differential Revision: D9566799

Pulled By: goldsborough

fbshipit-source-id: 83469f352ac69aa65bdaf1a1a21f922d892e0db3
2018-08-30 16:25:42 -07:00
Adam Paszke
aa7af94656 Make JIT tracing a thread-local property (#9414)
Summary:
As in the title. Lets us simplify a lot of code.

Depends on #9363, so please review only the last commit.

zdevito
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9414

Reviewed By: zdevito

Differential Revision: D8836496

Pulled By: apaszke

fbshipit-source-id: 9b3c3d1f001a9dc522f8478abc005b6b86cfa3e3
2018-07-19 19:09:39 -07:00
Richard Zou
769f5f7cfe
Handling of scalars in torch.Size (#5676)
* Handling of scalars in torch.Size

torch.Size() constructor uses python_arg_parser

IntList in python_arg_parser can take iter/range

Have IntList take python iterables and ranges.

Address comments: don't use python_arg_parser and instead call __index__ in THPSize_pynew

Address comments

Address comments

* Rebased

* Address nit
2018-05-30 17:50:32 -04:00
Adam Paszke
0829d4502d
Trace size-dependent expressions correctly (#6554)
This makes the JIT tracer much more robust, by allowing it to record
dependencies on tensor sizes. For example, if you were to trace this
function

def fn(x):
    return x.view(x.size(1), -1)

before this patch, then it would embed the actual value of x.size(1)
in the trace as a constant, making it very hard to have e.g. batch size
independent traces. Now, this will correctly record the dependency, and
will retrieve the size of x at every run.
2018-05-04 10:55:39 +02:00
Sam Gross
7588893ce2
Some additional clean-ups (#5505)
- Remove some uses of mega-header THP.h
 - Use HANDLE_TH_ERRORS in functions that may throw
 - Move NumPy includes to common header
 - Delete unused allocator
2018-03-05 17:45:02 -05:00
gchanan
067f799e9f
Implement remaining Variable fallthrough methods via ATen (#3744)
* Use aten version of is_signed.

* Define is_cuda native function and use it for variable.

* Use ATen dim for Variable dim/ndimension.

* Get rid of dim, ndimension fallthroughs in variable.py.

* Move size/stride Variable methods to use ATen.

* Implement shape property on Variable via ATen.

* Remove the _getattr__ function from Variable.

* Get rid of dispatch functions and avoid cast.

* Add THPUtils_packInt64Array.

* Throw python errors.

* Use fallthrough and fix fallthrough generation for native functions.

* is_cuda is a property, not a method.
2017-11-17 15:57:56 -05:00
peterjc123
aa911939a3 Improve Windows Compatibility (for csrc/scripts) (#2941) 2017-11-08 19:51:35 +01:00
Adam Paszke
ddd417faf0 Fix non-CUDA builds after Windows PRs (#2760) 2017-09-17 02:02:52 -04:00
Sam Gross
98206c326e Fix ref counting in wrapped tuple functions (#2042)
Fixes #1963
2017-07-10 18:46:06 -04:00
Trevor Killeen
05bc877a05 make THPPointer have explicit constructors (#1636) 2017-05-25 15:35:54 -04:00
Sam Gross
4c1cdb6148 Refactor Python string utility function 2017-04-28 21:25:26 +02:00
Adam Paszke
b9ece39685 Make torch.Size methods return torch.Size, not tuple 2017-02-17 10:40:08 +05:30
Adam Paszke
3975a2676e Fix invalid DECREF in torch.Size constructor 2017-01-24 17:30:50 -05:00
Sam Gross
f2d7e94948 Use torch.Size for Tensor sizes and tuple for strides
See issue #20

The torch.Size class is a tuple subclass which distinguishes sizes from
other tuples so that torch.Tensor(size) is interpreted as size instead
of data.
2016-10-28 19:37:09 +02:00