Datasets:
bigcode
/
commits_sample_files

Dataset card Data Studio Files Community
blob_id
stringlengths
40
40
content_id
stringlengths
40
40
path
stringlengths
7
193
directory_id
stringlengths
40
40
length
int64
1
9.54M
cf10dd7f36847eb2aebae69df46e29c52eb3223e
83b6f2fc55e41bfb7cfcc6d939accd52c520c816
/c10/test/core/StreamGuard_test.cpp
acffc11f0e94f4d07f65866410a06477191cc93f
80
c6420239e04eb70319958f3f1ae81120af2fdc93
7c0c15dd0d9c5bc7ff3fab2d32b54e060065ae7a
/c10/util/Unicode.h
acffc11f0e94f4d07f65866410a06477191cc93f
295
043b0b0bfe02c6cb26346ba6a348f2692b00946e
02fa8525d19e22c159cd8240a9b92e1d651bf225
/caffe2/operators/quantized/int8_slice_op.h
acffc11f0e94f4d07f65866410a06477191cc93f
3,024
d6a09a4fbd55df13bc0c1a71f1fa479444650e2c
729bb6d0fbe56bbb758f6271a26d43465c76bb82
/caffe2/opt/backend_cutting_test.cc
acffc11f0e94f4d07f65866410a06477191cc93f
4,483
136fd2834bf9676fa0dc66e98059594dc606c029
4f13c84c2e90a193933829fdf88f987f1d7fcd84
/torch/nn/modules/upsampling.py
acffc11f0e94f4d07f65866410a06477191cc93f
11,200
1f0070a59816cdff9aa5969b66c8c6411c112d10
0db312f2c2093d50f579e08b6e34f0938cc1e169
/torch/testing/_internal/common_quantized.py
acffc11f0e94f4d07f65866410a06477191cc93f
8,680
38e9fee2096eb82e2a1d985befe44001832eadd9
9cd2f3cf31d782c8ea45ccbf2da71bee3ee29b5c
/android/pytorch_android_torchvision/src/main/AndroidManifest.xml
ad010e486c81badd539d422eb90b85252067bcd2
47
53865c00fdd5da800b466318d7754bc09b72de13
e631565c243590fad2e0d41260d930ce74e7946d
/src/transformers/models/conditional_detr/feature_extraction_conditional_detr.py
ad048e043bbd64a12ebf6781508d518ffa5a08f8
53,180
54a7c330633bbbe6f2559c02b13110878a7bfd63
750027117a81647db15326f3540675fddd1cc527
/src/transformers/models/esm/openfold_utils/protein.py
ad048e043bbd64a12ebf6781508d518ffa5a08f8
11,195
7b5dc0bcbee88b1d67cdbef9e69497185c7000c1
e46928a538fdf97f8f12d683f1accd9a0d6a7478
/tests/models/funnel/test_tokenization_funnel.py
ad22c46b20aa910dd37850833acf75e621b75091
2,984
7a868e1024c755f6cc9ed5591768dd8d2494ff43
7c09d34974ebe5abe306d754a131b75be791b4a4
/docs/1.7.1/_sources/generated/torch.randint_like.rst.txt
ad2395b9d7666e1f4d997e952226d73a510e80b6
97
0177ca0590ac556bc2fb16b682eccb92bdc3724d
7faa9c47fe38cbb64d559c9a18a3c2a2d60b844e
/docs/1.7.1/_sources/generated/torch.logical_or.rst.txt
ad2395b9d7666e1f4d997e952226d73a510e80b6
91
264a99fadc792b72ecf413c24955a3722532459b
d1925abaad113c888d702e2ddc3e1c47524d0c50
/docs/1.8.0/generated/torch.any.html
ad2395b9d7666e1f4d997e952226d73a510e80b6
37,287
7cfa26176208055275006a398e6ff5f7c07db14c
1de16f284e8ce83a5dfc85e5f1c22f398197696b
/docs/1.8.0/generated/torch.cdist.html
ad2395b9d7666e1f4d997e952226d73a510e80b6
44,717
6561657b54a7ee5ce9e725dcc868324bc866a036
d13a54c765fdd4887401e7f0d5a09f86030931d5
/docs/1.8.1/generated/torch.mul.html
ad2395b9d7666e1f4d997e952226d73a510e80b6
41,834
1b3af423603201a04ad8884af20f0c7d93c26070
a688239958adfaa04282a97e103924f0ce2715a1
/docs/1.8.1/generated/torch.addr.html
ad2395b9d7666e1f4d997e952226d73a510e80b6
41,600
02a8d2660c45aeba0cbf1c3c16750ed159f67627
d4fa9a377d5ac99cdf6f65007760248ef61792e5
/docs/1.9.0/generated/torch.Tensor.remainder.html
ad2395b9d7666e1f4d997e952226d73a510e80b6
31,880
537e878a1f97a5cbf44ff1335e63e63744e489ca
a929ea3c24e9581942f1a9482e46c98f35bc9043
/docs/1.9.0/generated/torch.Tensor.cumsum.html
ad2395b9d7666e1f4d997e952226d73a510e80b6
31,838
aba2a3e7851e7a01acb98e84965b59a27501bb84
a0f8637fbce77a2bee621c292a7cc5aa11cb5507
/docs/stable/generated/torch._sparse_csr_tensor.html
ad2395b9d7666e1f4d997e952226d73a510e80b6
38,175
4edbc052ebcfa9cb900a4b124f4d101acd438a8c
2f3083a26e769bc1243d0c089b314e52b4da9fe0
/docs/stable/generated/torch.addr.html
ad2395b9d7666e1f4d997e952226d73a510e80b6
41,886
3b0eec3d51349427d3482a44127705f6ae6d9919
54244f0d853471e837ee17afdd1a8bafcc940a11
/docs/1.6.0/_sources/generated/torch.matmul.rst.txt
ad644d1a07636000300700ee5deb4d7f4f054a69
77
e2fa252524af26b40c6cc448b7ffa2c90b3eb5b8
efafb0ae7333a135efd19d07dce77bc184d620cb
/docs/1.7.1/notes/randomness.html
ad644d1a07636000300700ee5deb4d7f4f054a69
41,914
6a1a35a89d245b360d8f8232e16fc8b4d24c02cd
d0d9c1681546fa2a86e27eca5113e00a1f59fe12
/docs/1.8.0/_modules/torch/quantization/fuse_modules.html
ad644d1a07636000300700ee5deb4d7f4f054a69
48,281
7ea6a36610bc5cdd22b5f92d208e702b809254bd
f3e3246d3e444203fb779d763a74fbed73846030
/docs/1.7.1/_sources/generated/torch.nn.utils.remove_weight_norm.rst.txt
ad644d1a07636000300700ee5deb4d7f4f054a69
144
3b8472ddce064ecc5ac4b8de6f567c66f9f36cde
072855350705f6c22a2adbdb3f2dafb669bb858e
/aten/src/ATen/native/quantized/cpu/qnnpack/bench/sgemm.cc
ad651e8d90abea36d0a5eb75fa322614dc3e6083
21,930
2ebe6632468520ed2b6d9a43caebfd160d6e69ae
2e8e1b957db71a05f406674283bcf13956b22e7c
/cmake/FlatBuffers.cmake
ad651e8d90abea36d0a5eb75fa322614dc3e6083
337
f9e357c0571e20fab9d39d02f3688ff09e9cc243
02fa2a089e9e45205a1fdd3e7af575889e65f590
/docs/cpp/source/index.rst
ad651e8d90abea36d0a5eb75fa322614dc3e6083
8,456
20771ea1459be24c5903098bc0055d704c9bb5ed
417246e519a6f3204e0a55666f5f592442261e3d
/docs/0.3.0/_sources/notes/autograd.rst.txt
ad6a3bb5f994788cfd594e669f820787eb2f72b4
6,779
b1c7c378a4fca954383264aafab3522d0b5ee581
032dd423ef28c664052bba6cf278a0f2e34cfba5
/docs/0.3.1/_sources/autograd.rst.txt
ad6a3bb5f994788cfd594e669f820787eb2f72b4
2,301
817e516163fffaf0a793cf74a9e31f2bb2c0fe1f
eff02e3378c49724db45649eab7f455ac0ae88c5
/docs/0.4.1/_modules/torch/optim/optimizer.html
ad6a3bb5f994788cfd594e669f820787eb2f72b4
101,720
2816350306cbc66c3c473affe6bc3f1d0200f135
8f0b4bcf69f8ee003ecf73450c3f193acd4da387
/docs/1.1.0/_modules/torchvision/models/detection/mask_rcnn.html
ad6a3bb5f994788cfd594e669f820787eb2f72b4
58,125
7d9e0095679271a13d48799b465bb1f96d52cb8a
d6a33fbe4b411bcee6afaeb6fac6da91470b5ae0
/docs/1.7.0/_sources/generated/torch.complex.rst.txt
ad6a3bb5f994788cfd594e669f820787eb2f72b4
80
393195690fb1d65bd76f36640dfb6e5c096762ab
c0cfd89c0182f6bdc9f86a50794208f8ff91d50a
/docs/1.7.0/_sources/community/contribution_guide.rst.txt
ad6a3bb5f994788cfd594e669f820787eb2f72b4
15,818
d9e10e7c3f13b48525cddec84bbf0ea3ef3fdbd2
5a207c83d387efa8dbe13a79803e32415ce7643b
/aten/src/ATen/miopen/Types.h
ad7b87110bfae7ee14558bdaad0b5db8266600f6
233
728b428eec6cb488b5b1907bea4f42739a226040
3a49cccde6736ecc2c0ef2206a586ef9391800a2
/aten/src/ATen/cuda/PinnedMemoryAllocator.cpp
ad7b87110bfae7ee14558bdaad0b5db8266600f6
1,093
c531ad662f868f649badd2b696600565f04a2c87
840388d85fb7da8e4d821c49433470b4c2002699
/caffe2/operators/resize_op.cc
ad7b87110bfae7ee14558bdaad0b5db8266600f6
12,551
c969a694010833dc298fddd696e118c0a9a7fa94
f205d8e650b2e913d8a338b2f9e1dd5c83b4dd3a
/caffe2/python/operator_test/jsd_ops_test.py
ad7b87110bfae7ee14558bdaad0b5db8266600f6
1,044
6126b345f65d757a5f5cb7995bccc876a742d426
3f849b4daf7b33dbb1012cc8e875e47f20b90ef8
/torch/csrc/jit/runtime/static/memory_planner.h
ad7b87110bfae7ee14558bdaad0b5db8266600f6
9,080
bde2e4e27fd6c4c08f8e4c48953bf60779a2c3aa
c20b361d583631ccd054cba1ccbeda55b6efaf11
/examples/research_projects/seq2seq-distillation/finetune.py
ad852e36b6afd2229321f783b29ac53091531bc5
19,055
c1d98962f3dc1e4128b48c7ae34cf114ceb8bf40
9c5bb7a30a1f70ee96e4cffb14dcff3bf89c4a21
/docs/0.3.1/_modules/torch/nn/modules/conv.html
ad9cce2e8f5f0f4b7a6852ae4be28316dac0e0d8
132,874
de9956c61e6e021339537a4eda6c5b45c86c695d
08498a87b4b5e51943116c9d43f501f9c274bba0
/docs/0.4.0/_modules/torchvision/models/densenet.html
ad9cce2e8f5f0f4b7a6852ae4be28316dac0e0d8
108,371
77a961cd855aad6fedeeb34c780a6a039ecd327c
307a4d15b7431471d101105f0f771b6f35dcaf34
/docs/1.8.0/generated/torch.norm.html
ad9cce2e8f5f0f4b7a6852ae4be28316dac0e0d8
43,902
6e042d0c88f2caa929d999da88f5aec615d2375f
e15849cebeadb31de864367857af868c6d6b86b6
/docs/1.8.1/_modules/torch/multiprocessing.html
ad9cce2e8f5f0f4b7a6852ae4be28316dac0e0d8
36,499
a15f680915443dd4664b245dda52fe0f6608ed8f
181bcae0031b6f7f0f77b5eebeb7f3de5436c691
/torch/csrc/api/include/torch/data/transforms/collate.h
ae35aea4b9fa41f4a5026877326b4613412cb6fc
1,113
8f63a1168896c65f3aa099ba7ce72ea4693c5174
518feb2e38691bf0d61d19ea9387e889825cffbc
/.circleci/cimodel/data/simple/util/versions.py
ae73604e6e04e74fc6967e8ad12ca893dd4d4262
914
3221ae11b18e939be60be3ba27fb655611b64803
eccc4353a712d6f6515dd8bd93d7a706d83ab487
/caffe2/python/pybind_state.cc
ae70069a9a32c32a99f69e13b0e6c4b98c941d0d
25,181
e5d6b1748c9be378f4f535c6bf0a354515dc5ca4
6e34b3e1e5f41e79f743cf60d59f25a1754ca2f2
/.circleci/scripts/binary_linux_test.sh
aea8866e63fe57dd77fb072b710ae3b35f80a924
4,007
fe4f9e01119b20f34cf30c01e9850e8c6e600bd1
2fadc1cb00674114cb7a91ac788503c0ad3e8f72
/src/FbgemmFloat16ConvertAvx2.cc
aea614253837af864131403389d1bd71bc17683f
2,266
22125933f84c0e9144bc8015427208c2a647dc27
a54343d510a8afacbbe2664d8692968e14755673
/aten/src/ATen/native/IndexKernel.h
aea8866e63fe57dd77fb072b710ae3b35f80a924
1,726
59ca5fb562f7feebcb01dc239057ec07f7a51c54
1e54aae9d6601ae8d3595ee3bc5e0acf38d492bb
/aten/src/ATen/native/mkldnn/TensorShape.cpp
aea8866e63fe57dd77fb072b710ae3b35f80a924
3,572
861949e82bc20464dc20fc41a50256af16253867
d71c45bae4441b6f4576dfc1da2a9f84fdd52db5
/aten/src/ATen/native/quantized/cpu/qnnpack/bench/global-average-pooling.cc
aea8866e63fe57dd77fb072b710ae3b35f80a924
2,945
7c7c952d3f58893afd11803fea2a61d71359078c
c323703cb306cb45404c35b379fdd959c9f35b5d
/caffe2/contrib/shm_mutex/shm_mutex.cc
aea8866e63fe57dd77fb072b710ae3b35f80a924
446
9651275d601305dc185d71306d876e54eae99232
b07f4714b24377e3d3aaad6babfaaabdd491953f
/test/distributed/elastic/multiprocessing/bin/echo3.py
aea8866e63fe57dd77fb072b710ae3b35f80a924
684
e0db5c82be2221a0d4e744e4a85327d5ebd561eb
38c69343bce39f665ba9161c333518aa5ad1e887
/core/scripts/e2e/snapshot.js
aec15bedf725154cefed924739bb9befef187299
4,895
1055018c28ab41087ef9ccefe411606893dabea2
644d35e274fd64ddaf6d12af813e820c424176a9
/_static/jquery.js
aec05194d6d6483baf7c268558cf1025892a88b0
86,659
ac924304ec2cf6b869899127aab25abaf9fc419f
7fafe815af01b5611e7ef551846d8a07ce87b0e7
/core/src/components/nav/nav.scss
aec15bedf725154cefed924739bb9befef187299
364
9157b868e901d134fb38ce21d0d588a19f0294f8
91c79fa141e395f047c460cfa2beee3b37033afa
/docs/0.4.0/_modules/torch/distributions/transformed_distribution.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
85,796
18e0e7a7def15a23de4d897edb9e9273e67e34f9
e036ffbbdde875bbb037cb76b0a4def370fc2f49
/docs/1.10.0/_sources/generated/torch.dequantize.rst.txt
aed30a6bfbebee4a8f093eec234596a7fc8e2389
92
b5c910d40114c4720677ba0f028c3582fceb9766
749b79a878f35db06f3f5fdf3f3525571e0f47e0
/docs/1.10.0/_sources/generated/torch.enable_grad.rst.txt
aed30a6bfbebee4a8f093eec234596a7fc8e2389
226
ac1b80d141d4a991823eddae7923bd0c4f87f92c
19622bea7c2a4233d430edc73227eceec40c3206
/docs/1.10.1/_sources/generated/torch.optim.NAdam.rst.txt
aed30a6bfbebee4a8f093eec234596a7fc8e2389
214
dae05626a0dc15744c294be03ca8efd228905a6a
87fa1feed42cd33072abcc82acba28316a9c6d56
/docs/1.10.1/_sources/generated/torch.optim.lr_scheduler.ConstantLR.rst.txt
aed30a6bfbebee4a8f093eec234596a7fc8e2389
242
15f9c8e277c0886b6ca89f5353019ee53c21a020
445ec7ab538eea0f2313a5bc6f5b9912632e7135
/docs/1.10.1/generated/torch.cuda.nvtx.range_pop.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
32,305
5b2a7488f2755b33fc1f27c73e56831cf3bb073e
186c50e4fa3c348e8a48d8d58d832e984a926f8f
/docs/1.10.1/generated/torch.nn.functional.softshrink.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
32,754
1b59d5e8f640146e51ecd50c89a523858a7f8b8f
11e98f716793c4b288e648c23d63a3dfcd7bc5fe
/docs/1.10/generated/torch.Tensor.logical_not.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
32,325
17ebffbbba8591d2ea913ee2f4f74ef430206435
03708ba72d69c6f1023c873655567d15798dd5fb
/docs/1.10/generated/torch.Tensor.fill_diagonal_.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
35,498
c99ab3dfbca9fd031e895f1f580bdb4c0adf47ef
478bf6978dbe6fc323ae7e9e7fcb77be708be18e
/docs/1.11/_sources/generated/torch.sign.rst.txt
aed30a6bfbebee4a8f093eec234596a7fc8e2389
74
c6bf2e1e097604fb991b103296fb1e96741c497f
92fad4b5c0b766702548d26ab2be2832e19ad4da
/docs/1.11/_static/check-solid.svg
aed30a6bfbebee4a8f093eec234596a7fc8e2389
313
e645a90a617221d9c834a3f6c6299d50722ceef1
74856ea9fdae10930e228cb3e067f7e176e7ef9e
/docs/1.7.0/_static/images/pytorch-x.svg
aed30a6bfbebee4a8f093eec234596a7fc8e2389
676
aa92a4b65193ce63468e285d7916817b14d35ef6
c38c421e719b6a1765c2d80ceb121372900017a2
/docs/1.9.0/_modules/torch/nn/modules/container.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
131,097
e85dee39ba58f041242949ec73dd28f3f142c6f8
52eded6768f0be61ec1137b74acc4d223ce8c47c
/docs/1.8.1/generated/torch.rsqrt.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
36,820
86e27d0819da9022ad40af1e88c02113d925713c
b8d2f75529b997d016716cb9f759b9986b343a25
/docs/1.9.0/generated/torch.Tensor.contiguous.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
32,695
38e909dae6f5d322b3f67e062fd61c03a36dd8d8
4c5bbfb4aefe0f60807adf50d0fc099d3af7c22c
/docs/1.9.0/generated/torch.Tensor.argsort.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
31,887
2ea6a7fa2089dd3086ab011b4675c9d176b4899b
de30eac0df2d5d7e9337b34c125e6308124d0e01
/docs/1.9.1/cpp_extension.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
61,092
997d2c7b1be3988fc6f129527c4549b1ab3418cf
cb7d8d7b8502088c11c0fbeda1b765b6b934d911
/docs/1.9.1/generated/torch.Tensor.logical_xor_.html
aed30a6bfbebee4a8f093eec234596a7fc8e2389
31,929
84bc97172c1df16c5770894ef56f599a0ab5084b
f9f9ba9c68fba59147dfbc9fd1a7fc1e079783a9
/docs/stable/_sources/generated/torch.quantization.qconfig.default_debug_qconfig.rst.txt
aed30a6bfbebee4a8f093eec234596a7fc8e2389
296
f46a07756595d0fc9ffa8ee4ecc87790e585ef57
c302712a7548de58f55f1c7e5f3c852d5fb948f0
/docs/stable/_sources/generated/torch.nn.parameter.UninitializedParameter.rst.txt
aed30a6bfbebee4a8f093eec234596a7fc8e2389
291
fd9872a3f43a1c27d4d4d32d9277a90e3f699f39
e0652cb104107449225554afb4b3770e27066e58
/captum/insights/attr_vis/frontend/src/components/ClassFilter.tsx
aed362c2fa66c8d172b3296994ebcebc42b990b9
1,076
4c7e0b4d04aa497aae127e78684b8d53e3c720ca
cfa62912bc6adb52f7c692b0949de158a2ade60d
/sasha-luccioni-interview.md
aed517f6cae5fa51fa294a3ca21c5b5ee8f4b77e
49,933
c87a286e7f27d8293b6fbfa1fbeea7e6df616d68
59918f6fab3ca3eee05ab19b5378d5d102b3bf46
/benchmarks/operator_benchmark/README.md
aed60eb40734a8ed5d38f2dd8f77fdb2919bcbf6
17,162
7075d102a953ed6151c5f6683d611825452b02ed
57f6cd1dc680ab806bd763473b95ef0c4be57ced
/docs/1.10.0/_modules/torch/overrides.html
aedba5353885066201f078f2192713c36b8ef874
502,355
5c555f4d1577e137ba3e2885a1e0f73966425e9e
6c3004646a32250c6a8a3963ac9cd4900407722f
/docs/1.10.0/_modules/torch/distributions/kumaraswamy.html
aedba5353885066201f078f2192713c36b8ef874
44,230
8a8cffdf3fc6c2ae365293e59a8db09dda613feb
8597209dec894669f3886ef98a863f078564ddf5
/docs/1.10.0/generated/torch.Tensor.byte.html
aedba5353885066201f078f2192713c36b8ef874
33,165
a9f10126c084b6f988206e17c1b282629bdb7226
adbd56ff8b975c5a1c9293101e67812d19ccfef9
/docs/1.10.0/_sources/generated/torch.squeeze.rst.txt
aedba5353885066201f078f2192713c36b8ef874
83
2ad3f1fe50185d5f73e3fe7163f4c341c46bc368
c92a83b557b3fb0d8fdd230ac9bc3208ff6b47f0
/docs/1.10.1/_sources/generated/torch.optim.Rprop.rst.txt
aedba5353885066201f078f2192713c36b8ef874
214
d993b0c211c7fc75d13ae1b400fa427099e34c89
a5c5449da6d97e4a21a014cef7df41982b82aecf
/docs/1.10.1/_sources/generated/torch.Tensor.unfold.rst.txt
aedba5353885066201f078f2192713c36b8ef874
99
b3a73151f2559da915c25f1dec529d58e60cf1f8
e0ea3ebbc6244f723ee3e0976e96406abcdb41c1
/docs/1.10.1/_sources/generated/torch.Tensor.is_coalesced.rst.txt
aedba5353885066201f078f2192713c36b8ef874
119
768cf0222d84b573a54d1e119cb4cac572d1de07
a1e640c11c2f0ecff2e6499ab73bc3c8f580ccc5
/docs/1.11/_sources/generated/torch.nn.functional.gelu.rst.txt
aedba5353885066201f078f2192713c36b8ef874
116
4727705c886722721b45c16110e673281cf454d6
283095c5db4c0409358ad6b81c52d9660bfea215
/docs/1.11/_sources/generated/torch.Tensor.tanh_.rst.txt
aedba5353885066201f078f2192713c36b8ef874
98
af9050ad95294489a490f22d9198f20937ee8bb4
babb4952af1fa34ad9409d8dbef686b26db5aec1
/docs/1.11/_sources/generated/torch.nn.utils.clip_grad_value_.rst.txt
aedba5353885066201f078f2192713c36b8ef874
143
2d04f9e2db03367554a7724769de193f2b1d7657
0f8dff3bea7f00959e42e10b4857d46beaa12893
/docs/1.11/generated/torch.nn.SmoothL1Loss.html
aedba5353885066201f078f2192713c36b8ef874
66,155
89d75682ec2b40b5bc2cbc96cb1155a32650f7c0
25e26fb87d463895bd6123771eedfff983379a4c
/docs/1.11/generated/torch.quantization.observer.PerChannelMinMaxObserver.html
aedba5353885066201f078f2192713c36b8ef874
37,270
01dd261b37e75f9e023181767d6448a9bf030500
fff0bc49b0eceefe3fc8472063515aba9de28583
/docs/1.11/generated/torch.nn.utils.clip_grad_norm_.html
aedba5353885066201f078f2192713c36b8ef874
35,772
4c13385b4e2405cc069e26e18c275e933cc4712a
77772d44a96bf04e3a8ace21340c671ffdda5974
/docs/master/_sources/generated/torch.Tensor.inverse.rst.txt
aedba5353885066201f078f2192713c36b8ef874
102
12f154f5b3930363a2b2e4cb484c95d2644219e6
a2e02777a6e98803f58fae385765d53cde95292d
/docs/1.9.1/generated/torch.nn.LogSoftmax.html
aedba5353885066201f078f2192713c36b8ef874
40,540
b797a43fda69a8c30062d263e5025ad6cabebd82
5efe002f1a6694dac7c8a8772291c1343275cb31
/docs/1.9.1/generated/torch.xlogy.html
aedba5353885066201f078f2192713c36b8ef874
45,005
1d166ab158fbd2f21461e1cc50e028a253705606
7c3b4e7b5005df6a164c76db2c52efd701f03acc
/docs/master/_sources/generated/torch.Tensor.swapdims.rst.txt
aedba5353885066201f078f2192713c36b8ef874
105
588e17bcc5b7e2118b82a80abde1d54e22674384
e08f9d0b3141b13710b516dde3bfbcb44c62ccc5
/docs/master/index.html
aedba5353885066201f078f2192713c36b8ef874
42,730
c5789c43666327cc5ff35b132ebbc73ed05fbbe8
7f41afacc4acbd2cd0ed6e569896d39fb6dd041f
/docs/master/generated/torch.quantization.observer.PlaceholderObserver.html
aedba5353885066201f078f2192713c36b8ef874
34,918
a4d47692d92324cbbe86dccea7c26be58ce857aa
2d05218e6fcd83563697ab9557c5d768c1365433
/docs/1.10/generated/torch.Tensor.trace.html
aee3419bd5831c066e22823ed3ad1b790f984105
32,170
0e69755cbb1e12bf861f7bfc601aefa7ca92eb06
15db6e09160c462a845457b639fed7e9b9aebc37
/docs/1.10/generated/torch.Tensor.squeeze.html
aee3419bd5831c066e22823ed3ad1b790f984105
32,379