Commit Graph

7 Commits

Author SHA1 Message Date
f4d8bc46c7 Enable TF32 as fp32 internal precision for matmul/linear/conv (#157520)
### Description

This PR is to enable TF32 as fp32 internal precision for matmul/linear/conv in `mkldnn backend`. Since we have refined fp32 precision API in https://github.com/pytorch/pytorch/pull/125888, we can easily extend the API to support TF32 for `mkldnn backend`.

```
torch.backends.mkldnn.matmul.fp32_precision = 'tf32'
torch.backends.mkldnn.conv.fp32_precision = "tf32"
```

Related kernel update and UTs update are done. And the wrapper `bf32_on_and _off` is updated to `reduced_f32_on_and_off`, and it can run tests 3 times, one is reduced_f32 OFF, the other two are reduced_f32 ON (including `bf32 ON` and `tf32 ON`).

Pull Request resolved: https://github.com/pytorch/pytorch/pull/157520
Approved by: https://github.com/mingfeima, https://github.com/jansel
2025-07-17 08:57:34 +00:00
5a2db5152d allow to use bf16 as fp32 internal precision for mkldnn conv (#126050)
Allow to use `BF16` as the internal computation data types by `torch.backends.mkldnn.conv.fp32_precision="bf16"`

### TestPlan
python test/test_mkldnn.py -k conv

### Benchmarking

FP32 conv2d vs. BF16 internal computation conv2d on SPR

Single core:

Input | fp32 ms | bf16 internal  ms | Speed up
-- | -- | -- | --
IC:   64, OC: 256, kernel: 1, stride: 1, N: 256, H: 56, W: 56, G: 1, pad: 0 | 185.5071 | 83.4749 | 2.22
IC:   128, OC: 512, kernel: 1, stride: 1, N: 256, H: 28, W: 28, G: 1, pad: 0 | 194.7558 | 79.1683| 2.46
IC: 256, OC: 256, kernel: 3, stride: 1,   N: 1, H: 16, W: 16, G: 1, pad: 0 | 1.9213 | 1.3690 | 1.40

56 cores:
Input | fp32 ms | bf16 internal ms | Speed up
-- | -- | -- | --
IC:   64, OC: 256, kernel: 1, stride: 1, N: 256, H: 28, W: 28, G: 1, pad: 0 | 6.5804  | 7.4349 | 0.89
IC:   128, OC: 512, kernel: 1, stride: 1, N: 256, H: 28, W: 28, G: 1, pad: 0 | 4.9940  | 3.8093 | 1.31
IC:   256, OC: 1024, kernel: 1, stride: 1, N: 256, H: 14, W: 14, G: 1, pad: 0 | 8.8359 | 5.5802 | 1.58
IC: 1024, OC: 256, kernel: 1, stride: 1,   N: 256, H: 14, W: 14, G: 1, pad: 0 | 16.5800 | 9.2367 | 1.80
IC: 256, OC: 256, kernel: 3, stride: 1,   N: 1, H: 16, W: 16, G: 1, pad: 0 | 79.5436 | 38.3861  | 2.07

Pull Request resolved: https://github.com/pytorch/pytorch/pull/126050
Approved by: https://github.com/jgong5, https://github.com/jansel

Co-authored-by: Jiang, Yanbing <yanbing.jiang@intel.com>
2025-07-02 01:31:23 +00:00
a0ac63cbd9 [BE]: Apply ruff PERF403 to use dict comprehensions more often (#149257)
Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/149257
Approved by: https://github.com/jansel
2025-03-18 00:46:07 +00:00
24cfeec2c7 Revert "[BE]: Apply ruff PERF403 to use dict comprehensions more often (#149257)"
This reverts commit bfee141666319c80b6c5284394905beef8682515.

Reverted https://github.com/pytorch/pytorch/pull/149257 on behalf of https://github.com/malfet due to Let's see if it helps restore compiler benchmark sanity, see 8bc7bd94a5/1 ([comment](https://github.com/pytorch/pytorch/pull/149257#issuecomment-2731133812))
2025-03-17 22:57:00 +00:00
bfee141666 [BE]: Apply ruff PERF403 to use dict comprehensions more often (#149257)
Fixes #ISSUE_NUMBER

Pull Request resolved: https://github.com/pytorch/pytorch/pull/149257
Approved by: https://github.com/jansel
2025-03-16 23:52:58 +00:00
9bce208dfb Replace follow_imports = silent with normal (#118414)
This is a lot of files changed! Don't panic! Here's how it works:

* Previously, we set `follow_imports = silent` for our mypy.ini configuration. Per https://mypy.readthedocs.io/en/stable/running_mypy.html#follow-imports, what this does is whenever we have an import to a module which is not listed as a file to be typechecked in mypy, we typecheck it as normal but suppress all errors that occurred in that file.
* When mypy is run inside lintrunner, the list of files is precisely the files covered by the glob in lintrunner.toml, but with files in excludes excluded.
* The top-level directive `# mypy: ignore-errors` instructs mypy to typecheck the file as normal, but ignore all errors.
* Therefore, it should be equivalent to set `follow_imports = normal`, if we put `# mypy: ignore-errors` on all files that were previously excluded from the file list.
* Having done this, we can remove the exclude list from .lintrunner.toml, since excluding a file from typechecking is baked into the files themselves.
* torch/_dynamo and torch/_inductor were previously in the exclude list, because they were covered by MYPYINDUCTOR. It is not OK to mark these as `# mypy: ignore-errors` as this will impede typechecking on the alternate configuration. So they are temporarily being checked twice, but I am suppressing the errors in these files as the configurations are not quite the same. I plan to unify the configurations so this is only a temporary state.
* There were some straggler type errors after these changes somehow, so I fixed them as needed. There weren't that many.

In the future, to start type checking a file, just remove the ignore-errors directive from the top of the file.

The codemod was done with this script authored by GPT-4:

```
import glob

exclude_patterns = [
    ...
]

for pattern in exclude_patterns:
    for filepath in glob.glob(pattern, recursive=True):
        if filepath.endswith('.py'):
            with open(filepath, 'r+') as f:
                content = f.read()
                f.seek(0, 0)
                f.write('# mypy: ignore-errors\n\n' + content)
```

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

Pull Request resolved: https://github.com/pytorch/pytorch/pull/118414
Approved by: https://github.com/thiagocrepaldi, https://github.com/albanD
2024-01-27 02:44:11 +00:00
0ae952db76 enable mkldnn bf32 matmul (#116015)
### Testing
FP32 matmul vs. mkldnn BF32 matmul  on SPR

single core:

Input | BF32   / ms | FP32  /   ms | Speed up
-- | -- | -- | --
M: 128, N: 128, K: 128, trans_a: False, trans_b: False | 32.842 | 38.279 | 1.165
M: 128, N: 256, K: 128, trans_a: False, trans_b: False | 38.590 | 73.967 | 1.917
M: 8192, N: 768, K: 768, trans_a: False, trans_b: False | 18456.267 | 74588.002 | 4.041

56 cores:
Input | BF32   / ms | FP32 /   ms | Speed up
-- | -- | -- | --
M: 8192, N: 768, K: 768, trans_a: False, trans_b: False | 1199.400 | 1715.548 | 1.430
M: 8192, N: 768, K: 768, trans_a: False, trans_b: True |1129.204 | 1708.912 |  1.513
M: 8192, N: 768, K: 3072, trans_a: False, trans_b: False | 3655.915  | 7992.877 | 2.186
M: 8192, N: 768, K: 3072, trans_a: False, trans_b: True | 3707.993 |  8026.191 | 2.165
Batch: 768, M: 128, N: 64, K: 128  | 1296.419 | 1308.411 | 1.009

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116015
Approved by: https://github.com/jgong5, https://github.com/ezyang
2024-01-20 09:30:23 +00:00