OSSForks/pytorch
1
0
Fork 0
mirror of https://github.com/zebrajr/pytorch.git synced 2025-12-07 12:21:27 +01:00
Code Issues Actions 38 Packages Projects Releases Wiki Activity
67,579 Commits 8,304 Branches 150 Tags 1.5 GiB
a7bfa04da6
Commit Graph

22 Commits

Author SHA1 Message Date
PyTorch MergeBot
a7bfa04da6 Revert "More markDynamoStrictTest (#115870)" 
This reverts commit 7f686c8fe1.

Reverted https://github.com/pytorch/pytorch/pull/115870 on behalf of https://github.com/jeanschmidt due to Breaking internal tests and builds, please check diff ([comment](https://github.com/pytorch/pytorch/pull/115870#issuecomment-1862997125))
 2023-12-19 15:40:57 +00:00
rzou
7f686c8fe1 More markDynamoStrictTest (#115870) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/115870
Approved by: https://github.com/voznesenskym
ghstack dependencies: #115845, #115855, #115856, #115857, #115858
 2023-12-15 05:26:54 +00:00
Jithun Nair
2ea2421b44 Skip unit tests that fail on MI210 runners (#114613) 
Taken from https://github.com/pytorch/pytorch/pull/105980
Pull Request resolved: https://github.com/pytorch/pytorch/pull/114613
Approved by: https://github.com/malfet
 2023-11-27 22:25:35 +00:00
rraminen
44367c59b2 Update skip reason for failing unit tests on ROCm 5.7 (#113286) 
Follow up to https://github.com/pytorch/pytorch/pull/110465. Updated skip reason for failing unit tests on ROCm 5.7

Pull Request resolved: https://github.com/pytorch/pytorch/pull/113286
Approved by: https://github.com/malfet
 2023-11-13 19:29:04 +00:00
rraminen
3a429423fc Upgrade CI to ROCm5.7 (#110465) 
This PR is to upgrade CI to ROCm5.7

Pull Request resolved: https://github.com/pytorch/pytorch/pull/110465
Approved by: https://github.com/pruthvistony, https://github.com/malfet
 2023-11-08 06:11:10 +00:00
Pruthvi Madugundu
9ce2e02fd6 Revert "[ROCm] Remove PYTORCH_MIOPEN_SUGGEST_NHWC flag (#90725)" (#110319) 
This reverts commit 66bfcd32fd.

NHWC is have perf regression on MIOpen, so reverting till the performance issue is fixed.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/110319
Approved by: https://github.com/jeffdaily, https://github.com/jithunnair-amd, https://github.com/kit1980
 2023-10-03 19:14:47 +00:00
CaoE
7c9052165a add fp16 support for native conv and deconv on CPU (#99497) 
### Testing

Native conv vs. mkldnn conv on SPR (with avx512_fp16 support)

Single core:

Input | Naïve impl   / us | oneDNN /   us | Speed up
-- | -- | -- | --
IC:   64, OC: 256, kernel: 1, stride: 1, N: 256, H: 56, W: 56, G: 1, pad: 0 | 34676789 | 524199.8 | 66.15185
IC:   128, OC: 512, kernel: 1, stride: 1, N: 256, H: 28, W: 28, G: 1, pad: 0 | 33454125 | 349844.4 | 95.62573
IC: 256, OC: 256, kernel: 3, stride: 1,   N: 1, H: 16, W: 16, G: 1, pad: 0 | 317650.1 | 2317.677 | 137.0554
IC: 128, OC: 256, kernel: 3, stride: 1,   N: 1, L: 64 | 15334.68 | 167.264 | 91.67952

56 cores:
Input | Naïve impl   / us | oneDNN /   us | Speed up
-- | -- | -- | --
IC:   64, OC: 256, kernel: 1, stride: 1, N: 256, H: 56, W: 56, G: 1, pad: 0 | 1032064 | 11073.58 | 93.20061
IC:   128, OC: 512, kernel: 1, stride: 1, N: 256, H: 28, W: 28, G: 1, pad: 0 | 1000097 | 16371.19 | 61.08883
IC:   256, OC: 1024, kernel: 1, stride: 1, N: 256, H: 14, W: 14, G: 1, pad: 0 | 981813.4 | 9008.908 | 108.9825
IC: 1024, OC: 256, kernel: 1, stride: 1,   N: 256, H: 14, W: 14, G: 1, pad: 0 | 1082606 | 10150.47 | 106.6558
IC: 256, OC: 256, kernel: 3, stride: 1,   N: 1, H: 16, W: 16, G: 1, pad: 0 | 319980.6 | 181.598 | 1762.027

Pull Request resolved: https://github.com/pytorch/pytorch/pull/99497
Approved by: https://github.com/jgong5, https://github.com/cpuhrsch
 2023-09-25 01:31:26 +00:00
Justin Chu
79c5e33349 [BE] Enable ruff's UP rules and autoformat nn/ mps/ and torch/ (#105436) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/105436
Approved by: https://github.com/malfet, https://github.com/albanD
 2023-07-21 07:38:46 +00:00
Fuzzkatt
6d570ccd59 tf32 context fixes for various tests (#103137) 
Addresses tf32 context related failures from NVIDIA internal testing for following unit tests:

H100:

- functorch/test_vmap.py: test_op_has_batch_rule

A100:

- test_expanded_weights.py: test_cnn_model_sum
- nn/test_convolution.py: test_conv2d_same_padding_backward

Pull Request resolved: https://github.com/pytorch/pytorch/pull/103137
Approved by: https://github.com/zou3519
 2023-06-15 02:33:12 +00:00
Fuzzkatt
f8896b7b0e update tf32 thresholds in nn/test_convolution.py (#102015) 
updated tf32 thresholds for test_cudnn_convolution_relu, test_cudnn_convolution_add_relu

Pull Request resolved: https://github.com/pytorch/pytorch/pull/102015
Approved by: https://github.com/ngimel
 2023-05-24 22:42:25 +00:00
Fuzzkatt
47e9dba765 move tf32_on_and_off fix for test_convolution.py (#102007) 
move tf32_on_and_off after  @torch.backends.cudnn.flags(enabled=True, benchmark=False) due to  @torch.backends.cudnn.flags(enabled=True, benchmark=False) overwriting tf32_on_and_off if after.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/102007
Approved by: https://github.com/ngimel
 2023-05-24 02:23:06 +00:00
kshitij12345
3b966a6ce3 [autograd] disable backward/grad for complex scalar output (#92753) 
Fixes https://github.com/pytorch/pytorch/issues/92750

Pull Request resolved: https://github.com/pytorch/pytorch/pull/92753
Approved by: https://github.com/ezyang
 2023-02-23 11:38:27 +00:00
Jeff Daily
66bfcd32fd [ROCm] Remove PYTORCH_MIOPEN_SUGGEST_NHWC flag (#90725) 
Fixes #64427.  MIOpen supports ChannelsLast.  No longer need to opt-in with env var.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/90725
Approved by: https://github.com/malfet
 2023-02-09 22:26:24 +00:00
mingfeima
26cba842ad Optimize ConvTransposed2D with mkldnn float32 and bfloat16 on CPU (#92530) 
this PR optimized `ConvTranspose2d` with oneDNN and add channels last support for it. Also the fallback path `slow_conv_transpose2d` also have channels last support. So the memory format propagation behavior would stay the same with or without oneDNN.

Replacement of https://github.com/pytorch/pytorch/pull/77060, https://github.com/pytorch/pytorch/pull/70897 and https://github.com/pytorch/pytorch/pull/74023 which enables oneDNN for `ConvTranspose2d` and `ConvTranspose3d`

The following results collects on Skylake Xeon 8180, dual sockets, 28 cores per socket.
### single core channels last

configs | forward before/ms | forward after/ms | ratio | backward   before/ms | backward after/ms | ratio
-- | -- | -- | -- | -- | -- | --
input size: (32, 32, 100, 100), weight size: (32, 32, 3, 3) | 181.36 | 91.16 | 1.99 | 531.38 | 124.08 | 4.28
input size:   (32, 16, 200, 200), weight size: (16, 16, 3, 3) | 324.35 | 153.50 | 2.11 | 973.16 | 185.97 | 5.23
input size:   (32, 128, 100, 100), weight size: (128, 128, 3, 3) | 1086.82 | 671.52 | 1.62 | 3008.94 | 1453.33 | 2.07

### single core channels first

configs | forward before/ms | forward after/ms | ratio | backward   before/ms | backward after/ms | ratio
-- | -- | -- | -- | -- | -- | --
input size: (32, 32, 100, 100), weight size: (32, 32, 3, 3) | 138.10 | 5.94 | 23.23 | 37.97 | 11.25 | 3.38
input size:   (32, 16, 200, 200), weight size: (16, 16, 3, 3) | 236.43 | 8.75 | 27.03 | 87.77 | 18.58 | 4.72
input size:   (32, 128, 100, 100), weight size: (128, 128, 3, 3) | 484.39 | 37.69 | 12.85 | 185.40 | 90.57 | 2.05

### single socket channels last

configs | forward before/ms | forward after/ms | ratio | backward   before/ms | backward after/ms | ratio
-- | -- | -- | -- | -- | -- | --
input size: (32, 32, 100, 100), weight size: (32, 32, 3, 3) | 138.10 | 5.94 | 23.23 | 37.97 | 11.25 | 3.38
input size:   (32, 16, 200, 200), weight size: (16, 16, 3, 3) | 236.43 | 8.75 | 27.03 | 87.77 | 18.58 | 4.72
input size:   (32, 128, 100, 100), weight size: (128, 128, 3, 3) | 484.39 | 37.69 | 12.85 | 185.40 | 90.57 | 2.0

### single socket channels first

configs | forward before/ms | forward after/ms | ratio | backward   before/ms | backward after/ms | ratio
-- | -- | -- | -- | -- | -- | --
input size: (32, 32, 100,   100), weight size: (32, 32, 3, 3) | 132.56 | 7.19 | 18.43 | 31.43 | 11.20 | 2.81
input size:   (32, 16, 200, 200), weight size: (16, 16, 3, 3) | 227.94 | 13.33 | 17.11 | 63.00 | 23.41 | 2.69
input size:   (32, 128, 100, 100), weight size: (128, 128, 3, 3) | 473.68 | 52.79 | 8.97 | 150.40 | 87.33 | 1.72

Pull Request resolved: https://github.com/pytorch/pytorch/pull/92530
Approved by: https://github.com/jgong5, https://github.com/ezyang
 2023-02-06 10:11:25 +00:00
Jeff Daily
72502b94f3 correct use of torch.backends.cudnn.flags() (#93182) 
Fixes #77467.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/93182
Approved by: https://github.com/ngimel
 2023-01-28 06:50:06 +00:00
Eddie Yan
dabf515c18 [cuDNN][cuDNN V8 API] (re-re-re-open) cuDNN V8 API on by default (#91117) 
Re-opening following #91025

CC @ptrblck @ngimel
Pull Request resolved: https://github.com/pytorch/pytorch/pull/91117
Approved by: https://github.com/ngimel
 2022-12-20 18:52:29 +00:00
PyTorch MergeBot
ba7aeac37b Revert "[cuDNN][cuDNN V8 API] (re-re-open) cuDNN V8 API on by default (#89022)" 
This reverts commit eecd621f06.

Reverted https://github.com/pytorch/pytorch/pull/89022 on behalf of https://github.com/ngimel due to breaks some convolution configurations #91025
 2022-12-16 23:06:35 +00:00
Eddie Yan
eecd621f06 [cuDNN][cuDNN V8 API] (re-re-open) cuDNN V8 API on by default (#89022) 
Testing V8 on by default again after fixes have been merged for e.g., https://github.com/pytorch/torchdynamo/issues/1833

One new failure that seems to be surfaced with V8 on appears in halonext + amp
```
RuntimeError: Internal Triton PTX codegen error:
Segmentation fault (core dumped)
```
But I'm not sure if this points to a V8 issue or a Triton issue CC @ngimel @ptrblck

Current dynamo benchmarks on A100:
v7 vs. v8
|dev |name                           |batch_size|abs_latency_v7|abs_latency_v8|
|----|-------------------------------|----------|--------------|--------------|
|cuda|adv_inception_v3               |128       |166.0240      |165.5798      |
|cuda|beit_base_patch16_224          |64        |123.5912      |123.0797      |
|cuda|botnet26t_256                  |128       |107.7343      |107.5948      |
|cuda|cait_m36_384                   |4         |184.5038      |184.0271      |
|cuda|coat_lite_mini                 |128       |142.3061      |140.5814      |
|cuda|convit_base                    |64        |165.2499      |161.0743      |
|cuda|convmixer_768_32               |32        |325.6984      |325.7094      |
|cuda|convnext_base                  |64        |237.4632      |238.0142      |
|cuda|crossvit_9_240                 |128       |72.2980       |72.4367       |
|cuda|cspdarknet53                   |64        |96.6862       |96.8308       |
|cuda|deit_base_distilled_patch16_224|64        |117.6045      |117.9616      |
|cuda|dla102                         |128       |182.3073      |182.2304      |
|cuda|dm_nfnet_f0                    |128       |133.6011      |133.6298      |
|cuda|dpn107                         |32        |148.5080      |148.5885      |
|cuda|eca_botnext26ts_256            |128       |113.8676      |113.1514      |
|cuda|eca_halonext26ts               |128       |119.2242      |119.1845      |
|cuda|ese_vovnet19b_dw               |128       |80.0217       |79.9438       |
|cuda|fbnetc_100                     |128       |91.4548       |91.4009       |
|cuda|fbnetv3_b                      |128       |115.4496      |115.5058      |
|cuda|gernet_l                       |128       |114.8365      |114.7870      |
|cuda|ghostnet_100                   |128       |58.5766       |58.5766       |
|cuda|gluon_inception_v3             |128       |165.5222      |165.7167      |
|cuda|gluon_xception65               |32        |165.8779      |165.7818      |
|cuda|gmixer_24_224                  |128       |116.3611      |113.4925      |
|cuda|gmlp_s16_224                   |128       |121.2607      |121.2534      |
|cuda|hrnet_w18                      |128       |246.5706      |246.7599      |
|cuda|inception_v3                   |128       |166.1096      |166.2034      |
|cuda|jx_nest_base                   |32        |93.6064       |93.4088       |
|cuda|lcnet_050                      |128       |21.4156       |21.4207       |
|cuda|levit_128                      |128       |27.2901       |27.2543       |
|cuda|mixer_b16_224                  |128       |157.8992      |158.2878      |
|cuda|mixnet_l                       |128       |197.3443      |197.2125      |
|cuda|mnasnet_100                    |128       |71.4604       |71.2997       |
|cuda|mobilenetv2_100                |128       |67.6080       |67.7515       |
|cuda|mobilenetv3_large_100          |128       |57.7224       |57.6591       |
|cuda|mobilevit_s                    |64        |93.0372       |93.0530       |
|cuda|nfnet_l0                       |128       |113.1664      |113.2853      |
|cuda|pit_b_224                      |64        |133.3333      |133.4153      |
|cuda|pnasnet5large                  |16        |238.9545      |238.8122      |
|cuda|poolformer_m36                 |64        |144.2353      |144.2375      |
|cuda|regnety_002                    |128       |32.8534       |32.9069       |
|cuda|repvgg_a2                      |128       |102.4150      |102.3827      |
|cuda|res2net101_26w_4s              |64        |120.8127      |120.8322      |
|cuda|res2net50_14w_8s               |128       |149.7052      |149.8969      |
|cuda|res2next50                     |128       |153.7439      |153.8215      |
|cuda|resmlp_12_224                  |128       |89.1918       |86.9226       |
|cuda|resnest101e                    |64        |159.4706      |159.3133      |
|cuda|rexnet_100                     |128       |88.0032       |88.0397       |
|cuda|sebotnet33ts_256               |64        |80.4635       |80.0120       |
|cuda|selecsls42b                    |128       |70.4430       |70.3663       |
|cuda|spnasnet_100                   |128       |78.0537       |78.1991       |
|cuda|swin_base_patch4_window7_224   |64        |212.9073      |213.0824      |
|cuda|swsl_resnext101_32x16d         |32        |193.0229      |193.0404      |
|cuda|tf_efficientnet_b0             |128       |97.1316       |97.0410       |
|cuda|tf_mixnet_l                    |128       |203.4956      |203.5340      |
|cuda|tinynet_a                      |128       |82.4038       |82.8733       |
|cuda|tnt_s_patch16_224              |128       |284.8576      |284.8867      |
|cuda|twins_pcpvt_base               |64        |118.3893      |119.2329      |
|cuda|visformer_small                |128       |126.0533      |126.0390      |
|cuda|vit_base_patch16_224           |64        |118.2873      |118.0573      |
|cuda|volo_d1_224                    |64        |108.7764      |108.2063      |
|cuda|xcit_large_24_p8_224           |5         |100.4656      |100.5209      |

v7 vs. v8 amp

|dev |name                           |batch_size|abs_latency_v7|abs_latency_v8|
|----|-------------------------------|----------|--------------|--------------|
|cuda|adv_inception_v3               |128       |104.9729      |105.1237      |
|cuda|beit_base_patch16_224          |64        |75.4330       |75.2039       |
|cuda|botnet26t_256                  |128       |74.5149       |74.8071       |
|cuda|cait_m36_384                   |4         |110.9788      |111.5170      |
|cuda|coat_lite_mini                 |128       |62.3618       |64.4965       |
|cuda|convit_base                    |64        |116.4054      |117.9129      |
|cuda|convmixer_768_32               |32        |264.4401      |264.4491      |
|cuda|convnext_base                  |64        |182.9009      |179.2136      |
|cuda|crossvit_9_240                 |128       |48.8586       |48.8359       |
|cuda|cspdarknet53                   |64        |80.0245       |80.0160       |
|cuda|deit_base_distilled_patch16_224|64        |66.5921       |66.7448       |
|cuda|dla102                         |128       |116.7780      |117.1683      |
|cuda|dm_nfnet_f0                    |128       |78.9322       |79.1135       |
|cuda|dpn107                         |32        |85.5206       |85.7514       |
|cuda|eca_botnext26ts_256            |128       |76.3672       |77.0050       |
|cuda|eca_halonext26ts               |128       |86.2458       |              |
|cuda|ese_vovnet19b_dw               |128       |43.2943       |43.3379       |
|cuda|fbnetc_100                     |128       |54.8479       |54.9251       |
|cuda|fbnetv3_b                      |128       |70.7504       |71.0188       |
|cuda|gernet_l                       |128       |66.1607       |66.0379       |
|cuda|ghostnet_100                   |128       |43.8882       |43.9336       |
|cuda|gluon_inception_v3             |128       |104.9297      |105.0204      |
|cuda|gluon_xception65               |32        |85.7118       |85.8370       |
|cuda|gmixer_24_224                  |128       |75.1214       |76.1170       |
|cuda|gmlp_s16_224                   |128       |76.4207       |76.6641       |
|cuda|hrnet_w18                      |128       |186.1326      |186.2435      |
|cuda|inception_v3                   |128       |105.0561      |105.0783      |
|cuda|jx_nest_base                   |32        |65.3066       |65.3245       |
|cuda|lcnet_050                      |128       |14.7991       |14.8687       |
|cuda|levit_128                      |128       |19.2893       |19.4772       |
|cuda|mixer_b16_224                  |128       |93.9826       |94.2056       |
|cuda|mixnet_l                       |128       |147.1245      |147.0435      |
|cuda|mnasnet_100                    |128       |39.1781       |39.2565       |
|cuda|mobilenetv2_100                |128       |42.3704       |42.3114       |
|cuda|mobilenetv3_large_100          |128       |37.2946       |37.2816       |
|cuda|mobilevit_s                    |64        |55.8930       |55.8934       |
|cuda|nfnet_l0                       |128       |64.0448       |64.4438       |
|cuda|pit_b_224                      |64        |80.6342       |80.2933       |
|cuda|pnasnet5large                  |16        |154.9611      |154.8654      |
|cuda|poolformer_m36                 |64        |101.7489      |101.8138      |
|cuda|regnety_002                    |128       |27.0939       |27.0309       |
|cuda|repvgg_a2                      |128       |60.9651       |61.2533       |
|cuda|res2net101_26w_4s              |64        |77.3291       |77.4739       |
|cuda|res2net50_14w_8s               |128       |93.6572       |93.7221       |
|cuda|res2next50                     |128       |112.4975      |112.3248      |
|cuda|resmlp_12_224                  |128       |59.5422       |60.7644       |
|cuda|resnest101e                    |64        |97.9894       |98.3358       |
|cuda|rexnet_100                     |128       |55.2218       |55.0718       |
|cuda|sebotnet33ts_256               |64        |60.4880       |60.8113       |
|cuda|selecsls42b                    |128       |41.4294       |41.5341       |
|cuda|spnasnet_100                   |128       |45.0037       |45.0304       |
|cuda|swin_base_patch4_window7_224   |64        |98.2561       |98.6925       |
|cuda|swsl_resnext101_32x16d         |32        |100.6179      |100.9195      |
|cuda|tf_efficientnet_b0             |128       |56.5344       |56.4591       |
|cuda|tf_mixnet_l                    |128       |153.0318      |152.9367      |
|cuda|tinynet_a                      |128       |54.1307       |53.9298       |
|cuda|tnt_s_patch16_224              |128       |142.4801      |142.6589      |
|cuda|twins_pcpvt_base               |64        |67.9027       |67.8325       |
|cuda|visformer_small                |128       |72.5589       |72.9427       |
|cuda|vit_base_patch16_224           |64        |71.4885       |71.7342       |
|cuda|volo_d1_224                    |64        |69.3539       |69.5910       |
|cuda|xcit_large_24_p8_224           |5         |59.9000       |59.9699       |

v7 vs. v8 float16
|dev |name                           |batch_size|abs_latency|abs_latency|
|----|-------------------------------|----------|-----------|-----------|
|cuda|adv_inception_v3               |128       |104.2544   |104.2677   |
|cuda|beit_base_patch16_224          |64        |85.3601    |85.3786    |
|cuda|botnet26t_256                  |128       |72.1476    |71.8277    |
|cuda|cait_m36_384                   |4         |108.3075   |108.5941   |
|cuda|coat_lite_mini                 |128       |61.2382    |61.6049    |
|cuda|convmixer_768_32               |32        |263.3818   |263.3598   |
|cuda|convnext_base                  |64        |172.6821   |173.8520   |
|cuda|crossvit_9_240                 |128       |44.6321    |44.6340    |
|cuda|cspdarknet53                   |64        |79.3165    |79.2964    |
|cuda|deit_base_distilled_patch16_224|64        |61.9816    |62.2109    |
|cuda|dla102                         |128       |115.7403   |115.9928   |
|cuda|dm_nfnet_f0                    |128       |77.5434    |77.7440    |
|cuda|dpn107                         |32        |83.6489    |83.5605    |
|cuda|eca_botnext26ts_256            |128       |73.9953    |74.1031    |
|cuda|eca_halonext26ts               |128       |81.7951    |81.7103    |
|cuda|ese_vovnet19b_dw               |128       |42.9618    |42.8853    |
|cuda|fbnetc_100                     |128       |54.3590    |54.3575    |
|cuda|fbnetv3_b                      |128       |69.7977    |70.1696    |
|cuda|gernet_l                       |128       |64.8684    |65.1726    |
|cuda|ghostnet_100                   |128       |43.2054    |43.1319    |
|cuda|gluon_inception_v3             |128       |104.1988   |104.3030   |
|cuda|gluon_xception65               |32        |84.2245    |84.5085    |
|cuda|gmixer_24_224                  |128       |82.0418    |82.7252    |
|cuda|gmlp_s16_224                   |128       |75.4792    |75.8374    |
|cuda|hrnet_w18                      |128       |184.1450   |184.1848   |
|cuda|inception_v3                   |128       |104.1203   |104.2536   |
|cuda|jx_nest_base                   |32        |58.2386    |58.4901    |
|cuda|lcnet_050                      |128       |14.6409    |14.5616    |
|cuda|levit_128                      |128       |22.3875    |22.4680    |
|cuda|mixer_b16_224                  |128       |98.9534    |98.4730    |
|cuda|mixnet_l                       |128       |146.1623   |146.1947   |
|cuda|mnasnet_100                    |128       |38.9208    |39.3463    |
|cuda|mobilenetv2_100                |128       |41.8946    |41.9847    |
|cuda|mobilenetv3_large_100          |128       |36.7810    |36.8264    |
|cuda|mobilevit_s                    |64        |55.3211    |55.3186    |
|cuda|nfnet_l0                       |128       |63.1302    |63.5544    |
|cuda|pit_b_224                      |64        |73.8752    |73.4602    |
|cuda|pnasnet5large                  |16        |151.6806   |151.6111   |
|cuda|poolformer_m36                 |64        |86.8341    |86.8021    |
|cuda|regnety_002                    |128       |26.6798    |26.5295    |
|cuda|repvgg_a2                      |128       |61.6652    |62.1482    |
|cuda|res2net101_26w_4s              |64        |75.8037    |75.7739    |
|cuda|res2net50_14w_8s               |128       |92.6362    |92.4338    |
|cuda|res2next50                     |128       |111.5371   |111.5832   |
|cuda|resmlp_12_224                  |128       |58.2349    |57.9807    |
|cuda|resnest101e                    |64        |96.1114    |96.2742    |
|cuda|rexnet_100                     |128       |54.8138    |54.7643    |
|cuda|sebotnet33ts_256               |64        |53.1524    |53.3823    |
|cuda|selecsls42b                    |128       |40.6070    |40.7104    |
|cuda|spnasnet_100                   |128       |44.5732    |44.4318    |
|cuda|swin_base_patch4_window7_224   |64        |98.6447    |98.8445    |
|cuda|swsl_resnext101_32x16d         |32        |97.0195    |97.2968    |
|cuda|tf_efficientnet_b0             |128       |56.0640    |56.0278    |
|cuda|tf_mixnet_l                    |128       |152.0958   |152.0874   |
|cuda|tinynet_a                      |128       |53.3694    |53.3762    |
|cuda|tnt_s_patch16_224              |128       |130.2981   |130.3726   |
|cuda|twins_pcpvt_base               |64        |62.5459    |62.6416    |
|cuda|visformer_small                |128       |68.8502    |69.1756    |
|cuda|vit_base_patch16_224           |64        |65.8587    |66.0285    |
|cuda|volo_d1_224                    |64        |64.5348    |64.6057    |

Pull Request resolved: https://github.com/pytorch/pytorch/pull/89022
Approved by: https://github.com/ngimel
 2022-12-15 03:24:44 +00:00
kshitij12345
6a964c16e5 [flaky] relax tolerance conv1d_vs_scipy (#89193) 
Fixes https://github.com/pytorch/pytorch/issues/89087

Pull Request resolved: https://github.com/pytorch/pytorch/pull/89193
Approved by: https://github.com/kit1980
 2022-11-18 07:31:10 +00:00
PyTorch MergeBot
d98a884b33 Revert "[cuDNN] (re-open) Enable cuDNN Frontend v8 API by Default (#87669)" 
This reverts commit 3c6bddc3f6.

Reverted https://github.com/pytorch/pytorch/pull/87669 on behalf of https://github.com/eqy due to investigating convnext benchmark regressions
 2022-11-08 19:04:25 +00:00
eqy
3c6bddc3f6 [cuDNN] (re-open) Enable cuDNN Frontend v8 API by Default (#87669) 
#58414

Has a small tweak to a test that was breaking on A10 (CC @malfet).

CC @ptrblck @ngimel
Pull Request resolved: https://github.com/pytorch/pytorch/pull/87669
Approved by: https://github.com/ngimel
 2022-11-02 01:36:37 +00:00
Kshiteej K
6735bf21c7 [test_nn] split convolution tests from test_nn (#87474) 
Ref #63085

Pull Request resolved: https://github.com/pytorch/pytorch/pull/87474
Approved by: https://github.com/albanD
 2022-10-31 04:42:45 +00:00