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15 Commits

Author SHA1 Message Date
Tom Ritchford
d8c8ba2440 Fix unused Python variables in test/[e-z]* (#136964) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136964
Approved by: https://github.com/justinchuby, https://github.com/albanD
 2024-12-18 23:02:30 +00:00
Xuehai Pan
fbe6f42dcf [BE][Easy][8/19] enforce style for empty lines in import segments in test/[k-p]*/ (#129759) 
See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501. Most changes are auto-generated by linter.

You can review these PRs via:

```bash
git diff --ignore-all-space --ignore-blank-lines HEAD~1
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129759
Approved by: https://github.com/justinchuby, https://github.com/ezyang
 2024-07-31 02:09:20 +00:00
Yuanhao Ji
706f7d1f22 Enable UFMT on test/jit_hooks, test/lazy and some files (#123807) 
Part of: #123062

Ran lintrunner on:

- `test/jit_hooks`
- `test/lazy`
- `test/linear.py`
- `test/load_torchscript_model.py`
- `test/mkl_verbose.py`
- `test/mkldnn_verbose.py`

with command:

```bash
lintrunner -a --take UFMT --all-files
```

Co-authored-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/123807
Approved by: https://github.com/ezyang
 2024-04-12 03:39:38 +00:00
Jane Xu
8695f0cced Rectify native_batch_norm schema by splitting it into two legit schemas (#88697) 
Using the same repro from the issue (but with BatchNorm2D)

Rectifies native_batch_norm schema by splitting the schema into 2:
1. one will have NON-optional alias-able running_mean and running_var inputs
2. the other will just not have those parameters at all (no_stats variation)

**Calling for name suggestions!**

## test plan
I've added tests in test_functionalization.py as well as an entry in common_method_invocations.py for `native_batch_norm_legit`
CI should pass.

## next steps
Because of bc/fc reasons, we reroute native_batch_norm to call our new schemas ONLY through the python dispatcher, but in 2 weeks or so, we should make `native_batch_norm_legit` the official batch_norm.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/88697
Approved by: https://github.com/albanD
 2022-11-23 23:23:17 +00:00
Henry Tu
02093da36c Autogen native_batch_norm and native_batch_norm_backward (#79637) 
This PR makes the `native_batch_norm` and `native_batch_norm_backward` ops autogen, and implements their respective shape inference functions.

Previously, these two ops were manually implemented.

cc: @ke1337 @antoniojkim @wconstab @desertfire
Pull Request resolved: https://github.com/pytorch/pytorch/pull/79637
Approved by: https://github.com/Gamrix, https://github.com/desertfire
 2022-06-24 23:29:33 +00:00
Edward Z. Yang
f7ee061638 Wconstab/reland pysymint (#79795) 
rebased https://github.com/pytorch/pytorch/pull/79617/ to see if issues are reproducible.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/79795
Approved by: https://github.com/malfet
 2022-06-20 22:55:06 +00:00
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
Bin Bao
29189d2ba8 [LT] Add IR resuing support for manually-implemented ops 
Summary: Add CanBeReused methods for manually-implemented ops and replace MakeNode with
ReuseOrMakeNode.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/77616

Approved by: https://github.com/JackCaoG, https://github.com/wconstab
 2022-05-26 16:04:47 +00:00
Nikolay Korovaiko
df1f9b9840 Implement sym_sizes to create proper IR for sym ints representing tensor sizes (#77756) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77756
Approved by: https://github.com/desertfire
 2022-05-20 05:39:03 +00:00
Bin Bao
25c6ebd12c Revert "Revert "[LT] Codegen ReuseNode for supported ops"" 
Summary: Fixed a XLC build failure by generating an always-return-false
default CanBeReused method.

This reverts commit 3cade9d454.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/77513

Approved by: https://github.com/alanwaketan
 2022-05-16 20:14:42 +00:00
PyTorch MergeBot
3cade9d454 Revert "[LT] Codegen ReuseNode for supported ops" 
This reverts commit 6066e5929f.

Reverted https://github.com/pytorch/pytorch/pull/76738 on behalf of https://github.com/malfet
 2022-05-14 00:33:10 +00:00
Bin Bao
6066e5929f [LT] Codegen ReuseNode for supported ops 
Summary:
1. Update the codegen script to add a TrieCache lookup (ReuseNode)
before creating a new IR node. The following is an example generated
code,

```
    at::Tensor LazyNativeFunctions::add(const at::Tensor & self, const at::Tensor & other, const at::Scalar & alpha) {
        ...
        torch::lazy::NodePtr node = torch::lazy::ReuseNode<AddTensor>(lazy_self->GetIrValue(), lazy_other->GetIrValue(), node_alpha);
        if (!node) {
            auto out_meta = at::meta::add(self, other, alpha);
            std::vector<Shape> shapes{Shape(out_meta.scalar_type(), out_meta.sizes().vec())};
            TORCH_INTERNAL_ASSERT(shapes.size() == 1);
            if(symbolicShapeEnabled()){
                std::vector<jit::IValue> inputs = { self, other, alpha };
                char* schema_str = "aten::add.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor";
                applySymbolicShapesOnLT(schema_str, inputs, shapes);
            }

            node = torch::lazy::MakeNode<AddTensor>(lazy_self->GetIrValue(), lazy_other->GetIrValue(), node_alpha, std::move(shapes));
            CacheNode(node);
        }
        ...
    }
```
2. TrieCache lookup depends on each IR node subclass to provide its own
comparison function. The following is an example generated code,

```
  bool CanBeReused(const torch::lazy::Value& self, const torch::lazy::Value& other, const torch::lazy::Value& alpha) const {
    size_t i = 0;
    return (operand(i++) == self &&
        operand(i++) == other &&
        operand(i++) == alpha);
  }
```

3. DeviceData is specially handled.

4. Non-codegen op changes are coming a separate PR.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/76738

Approved by: https://github.com/JackCaoG, https://github.com/wconstab
 2022-05-13 19:13:58 +00:00