blob_id
stringlengths
40
40
content_id
stringlengths
40
40
path
stringlengths
7
193
directory_id
stringlengths
40
40
length
int64
1
9.54M
cf2e75b8c67814f3b9a7b3ce47bd3cdfd9d3f649
70ddcc87581bc625b5c045526361be15b9e4a06b
/datasets/large_spanish_corpus/README.md
bf90851b3e7303e551f643e5c458ede51455a0bd
5,491
5fbd13d749d8ff3c3a8e63126a2490965c7a0f39
2ac162080ece9a3c7dde78715fdda546468d0b4f
/datasets/onestop_english/README.md
bf90851b3e7303e551f643e5c458ede51455a0bd
3,320
9e4497f96798ef6f0a068cb41f6041ba972033e4
47f3f4726a37442ee2a94f7af1a60baea6b28f1e
/datasets/opus_montenegrinsubs/dataset_infos.json
bf962991f9acb0178b55d467d54e4e7f7ee28e81
1,124
73d294ef79f7a0c83d6a916c29a2e421cebf5886
8ea7b8b9620023ce1ea986255efe21e624753b75
/datasets/guardian_authorship/dataset_infos.json
bf962991f9acb0178b55d467d54e4e7f7ee28e81
52,867
c8cc6b74e851c4ecdd450e1054666d3945c14107
b214ce5738380d43da8850a8980d7137a6465faf
/datasets/clue/README.md
bf962991f9acb0178b55d467d54e4e7f7ee28e81
10,004
adc4a2b079f72e2626db5077bb0708047fd1f2ca
0fcfead5aedc900c9815e806d912b00d44abf417
/docs/1.6.0/_sources/generated/torch.atan.rst.txt
c01e532049c3453d1084d28c51dc4d1e67baeab7
71
7a868e1024c755f6cc9ed5591768dd8d2494ff43
7c09d34974ebe5abe306d754a131b75be791b4a4
/docs/1.6.0/_sources/generated/torch.randint_like.rst.txt
c01e532049c3453d1084d28c51dc4d1e67baeab7
97
4b5bf794fda878cb57681e45fa66502be87b35b3
de0b49294e935e340d70733577c878fc01eba302
/docs/1.7.0/_modules/torchvision/datasets/places365.html
c01e532049c3453d1084d28c51dc4d1e67baeab7
57,821
733d575895c7a3fd9ae344661044fba5634cced1
9985faa6e9bd385c563e0f10998922fb5cdb1ca0
/test/cpp/jit/test_peephole_optimize.cpp
c029c0e9dafe0dd1cec57e725d86dcdf1641e740
2,859
04dbc924ab82fdcacda16f4352cf40f597c595f3
f5ee8747650fc8345d5d16b25715e0eb44f41ca2
/test/cpp/tensorexpr/test_memplanning.cpp
c029c0e9dafe0dd1cec57e725d86dcdf1641e740
21,602
ded3ee503bb6de007e068b7d494584f2e6dc0460
328eebfdfb1af0b9e0b174ab7cd17362b8e79ed7
/docs/1.5.1/_modules/torch/nn/parallel/data_parallel.html
c03090acb806ac01bcd367d42e40ff1a6d9bf079
56,695
fb9a75843b55f2a82cc4245af92322f4b635597f
5e5300038589af8b9a88c09834c2fae7feb6f389
/docs/1.5.1/_static/pytorch-logo-dark.svg
c03090acb806ac01bcd367d42e40ff1a6d9bf079
2,080
e457dadfe64218aee902cc33865b91ed8dba9276
d7ab101f3b126b43d36c5800e34615bb9854bae6
/docs/1.6.0/_sources/generated/torch.dist.rst.txt
c03090acb806ac01bcd367d42e40ff1a6d9bf079
71
fa59ea9daf23a68e9aef642ae47538bf9a8e3f5a
5708af2710ea13bdc82b6342b0c9d15667f66a20
/conda/cuda92/meta.yaml
c04c1c77939af6e6942942310a87a0e9d7b4b318
80
2d4a84a8ae72f5be3782eee01193f89fcc51b7ed
7489640f49a118d377157c36c886709c1ba0434c
/packaging/windows/internal/clean.bat
c04c1c77939af6e6942942310a87a0e9d7b4b318
56
ba3593b093110c41c0c5ddef793d0daa5dc6411a
a26fa9baec7c7b3c7e38e71877da7fbf09cd1318
/torch_glow/tests/nodes/shape_as_tensor_test.py
c042abf1798519f4aaa5f4bd57f8bcbdeb923ab2
1,600
fb5c5376d09ae6a5e9e17133b9dfa6f398f7e512
3460fa1226ed256750409a501a8ebb3a6c0806c2
/fairseq/optim/lr_scheduler/tri_stage_lr_scheduler.py
c06375434c0985a65dad2a14f0d2c97cadc05586
5,062
7602fdd34d1917c880ae1a6860d903e761080677
e2dbb5afbabaf90f14e289d6b1042f5e808b91be
/website/package.json
c065479280e2aec500a042b8c3afe3f12b029360
375
b3e95c550298d324a8c5e720a09e874da1acb1f0
9d2c35e104598b7f418db9fdb75805ff6f976ede
/docs/1.7.1/generated/torch.nn.Softmin.html
c068ba3f5eb8c47fd0730905dc313c776fb4fc12
38,049
eb8a36bcb32669f212c4c4ba31aa64315c0d15be
6b57fcad8da44dadaaf731f48918d808cd162e5a
/docs/1.7.1/generated/torch.cholesky_solve.html
c068ba3f5eb8c47fd0730905dc313c776fb4fc12
44,048
696f298f232727882634542f55e417e0f6cda001
61865f424eefdd0714433bf3f3e04d7c533cccbf
/docs/1.8.0/generated/torch.quasirandom.SobolEngine.html
c068ba3f5eb8c47fd0730905dc313c776fb4fc12
41,804
51b152bdb0b92a23a233b2e2aaa3629f7d95a713
31c8df06d230db086b24a2a86c7fa3dd06a5c71f
/docs/1.9.0/generated/torch.nn.AdaptiveAvgPool1d.html
c068ba3f5eb8c47fd0730905dc313c776fb4fc12
33,233
ac1674c75c4d5df09cc3be58c36cbfbc4ec93846
3141a931618847f05fe0870f2e4bf128ec513f41
/docs/1.9.0/generated/torch.rsqrt.html
c068ba3f5eb8c47fd0730905dc313c776fb4fc12
37,157
db41cf7e7a6bbb403cb0f674725182f43934ad01
0eb924d7faaad1fede57e86678466fb0d4bc30b5
/docs/master/generated/torch.Tensor.fmod_.html
c068ba3f5eb8c47fd0730905dc313c776fb4fc12
32,477
6dd2a381fdf501a007e3ddf06f6b7a5894ed339b
7ad89ca335f17ee83d37fa610a3e197b0c56c7c2
/docs/master/generated/torch.Tensor.masked_scatter_.html
c068ba3f5eb8c47fd0730905dc313c776fb4fc12
34,082
bb11dd087b3fada19b1808a2dd01c8abf6f61fcd
be17d1dc27c72cd251daf02bdcc81a70e55a7792
/docs/master/generated/torch.Tensor.logdet.html
c068ba3f5eb8c47fd0730905dc313c776fb4fc12
32,390
8c72697a9e0d8de2b1fce77aa8b8a333fbdcbdce
26012c4002706da7e250399046277b1d8fa685a3
/docs/1.10.0/_sources/generated/torch.nn.CrossEntropyLoss.rst.txt
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
263
971e6990d1633556ff9da0f09ca30d2031042d7a
ee5ae2f98bb00531f428b1b49365421c681e6dca
/docs/1.10.0/_sources/generated/torch.is_storage.rst.txt
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
94
5317d03f2ee5e58a26c627d19b1254d233a977f5
1b19ab04880f6ddd6c5e5c0b36e7f8698ab205ac
/docs/1.11/_sources/generated/torch.atanh.rst.txt
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
77
103d626ed8f66df3ee0987ac933229e18d6e5599
47eed18b7eb172b2429fd6aa69b5a96b7c3cabfe
/docs/1.11/_sources/generated/torch.qr.rst.txt
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
68
a103669ad3235f2e825698295e604a212b0a8996
72278e49449df6adb93464786a31bdf7dec5b5ee
/docs/1.11/_sources/generated/torch.optim.Adamax.rst.txt
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
217
e367d2d900c0f27db9f817a6b25398d652d4c690
b75ac3781313fb54e627a45fa5f6719b63ade130
/docs/1.11/generated/torch.Tensor.q_scale.html
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
32,870
0913ee39625e4c30a888c4f0945c965a35e20811
c64a611a36622a28f6a0e03ca5694f7cb63da930
/docs/1.5.1/_modules/torchvision/models/mnasnet.html
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
72,010
b3fcecbed6ec6fa8af2576937566670559400b36
e0818c2804461744bc3da92163bc644894d3326c
/docs/1.6.0/_modules/torchvision/ops/feature_pyramid_network.html
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
51,822
5a68c2ce15a06cc198886bc96c792bdedb115954
5c39c4907f7527c63b10e69d3c09847eda43f927
/docs/1.8.1/_modules/torch/optim/sgd.html
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
45,129
65e58ca7f689fd63de57438d1961241ddcddfc7c
7511bfcc6c3249fa7077b081ae54343086f246bd
/docs/1.8.1/generated/torch.ge.html
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
34,604
f330d33c490c1d4bd303dd8e0f9b3dbcdb170000
f4ee0ae7ad4c43ec93d49770e823c30f89123bc5
/docs/1.9.0/_sources/generated/torch.nn.CELU.rst.txt
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
224
a1283e9e2d3e6bbc361ac56e8a779e6c892ca261
737bbbd123f304a01ea9c22c189f18afc88deafb
/docs/1.9.0/_sources/generated/torch.nn.functional.conv3d.rst.txt
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
119
0ecababebeef539bb5ec11334cad7699259f8edf
d7f749a8c02c303290c8788bb8383d67aad25757
/docs/master/generated/torch.ao.nn.quantized.functional.upsample_nearest.html
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
36,448
007ef25fa5d1ad37e8590259ef0e4b2f8bf072e0
6c2b07bf87bca7676a9f36f7066f929eb1f66ff4
/docs/master/generated/torch.row_stack.html
c0750d40ebc5b33b5e10745a1d58e63a9a98c69a
33,809
8b307876b50675b6be47710a9b81503b245181c5
af891363be1a213807aee26ee1978b6184c577e9
/docs/1.6.0/_modules/torch/distributions/multivariate_normal.html
c08b357454dbccbcd2bca6c7eea0524b90188377
68,929
f871b6d3f18eb0d068768905288ca101cd8c5ec9
c0ca7d6379dc2021723403a11adfcc6f60aa4214
/docs/1.5.1/_sources/notes/cpu_threading_torchscript_inference.rst.txt
c08b357454dbccbcd2bca6c7eea0524b90188377
9,684
3fa5798429eae36aa9fb187e09e93ca06471c1e1
bce1581daf7f4c81274fa5fa471fe8d02bdedb80
/docs/1.6.0/generated/torch.logsumexp.html
c08b357454dbccbcd2bca6c7eea0524b90188377
34,375
fc72a5984ebdf0f5b607d8b413922f25b78d8c22
58997434e0bda0dfead49756207e707448451743
/docs/1.7.0/_sources/generated/torch.less.rst.txt
c08b357454dbccbcd2bca6c7eea0524b90188377
71
e183f1e4f1471a60c8424ad992713205e92c2876
7a5c45a389a7f83e322d0e51be3ae2b487cd7bdb
/docs/1.7.0/_sources/generated/torch.erfinv.rst.txt
c08b357454dbccbcd2bca6c7eea0524b90188377
77
d772a656bf4f52565a8ff20b57d040a7e2eae576
457569d6a9f7595fed33a07e62ea15917491787c
/docs/1.7.1/_sources/generated/torch.hamming_window.rst.txt
c08d4c0b069145cddd093ee4d2b22ce08b919cdb
103
dedfee2938962e097901e5e54cb04e8fc891cf9f
9b20a085c95c36740e0aed857b5c0ffd451c399b
/docs/1.7.1/_sources/generated/torch.i0.rst.txt
c08d4c0b069145cddd093ee4d2b22ce08b919cdb
65
7c672be2b66c6f966ce9209ecc8c69331d733d58
d7e409137ad35792000eb158c834dff1de2a69fb
/docs/1.8.0/_sources/generated/torch.is_tensor.rst.txt
c08d4c0b069145cddd093ee4d2b22ce08b919cdb
88
e183f1e4f1471a60c8424ad992713205e92c2876
7a5c45a389a7f83e322d0e51be3ae2b487cd7bdb
/docs/1.8.0/_sources/generated/torch.erfinv.rst.txt
c08d4c0b069145cddd093ee4d2b22ce08b919cdb
77
225fccf82bd3a2a76e7c2c5d5df1f57d31cbb468
685bf5513fbc72cfed1c58f461c45c7efd78356b
/docs/1.7.1/generated/torch.triangular_solve.html
c08d4c0b069145cddd093ee4d2b22ce08b919cdb
43,380
daabd01313de5c4d0f94d7bf9242528699365387
9bcdd715af4fbafefb62c91d0c327025de278d0c
/docs/1.9.0/elastic/train_script.html
c08d4c0b069145cddd093ee4d2b22ce08b919cdb
36,000
f4c8b9e7b6b2f7b278f68ec94892d24d29853705
68fe4c3f890a99e01a096a266ac843becfbbabc5
/docs/1.9.0/generated/torch.matrix_rank.html
c08d4c0b069145cddd093ee4d2b22ce08b919cdb
37,221
363ddbdcc7adc27b7e6626ade831ce69d035533c
3fe971c422e4d129768950aec7a963d25c42b67c
/docs/master/_sources/generated/torch.quantization.fake_quantize.FakeQuantize.rst.txt
c08d4c0b069145cddd093ee4d2b22ce08b919cdb
275
d038142f1a2a288845645f3b0464748726c0a194
16f6edd2c620e97f3ce498bd4f41f22b597e6252
/docs/1.4.0/_modules/torch/distributions/half_normal.html
c09be51a284c5f0d2366d331f2df56990005d1fe
34,826
527757e2370e09bfb32f9c0054f50ec07ebb6672
586673f3ea166e8a2ca1435abc4f1f0c92102a06
/docs/1.5.0/_modules/torch/nn/quantized/modules/functional_modules.html
c09be51a284c5f0d2366d331f2df56990005d1fe
50,519
ec9435e5e58781b2dbf070d67112e557f07542e0
35cb1de97fe6314b7d08db58d585d09310db3a08
/docs/1.8.1/_sources/generated/torch.nn.utils.prune.CustomFromMask.rst.txt
c09be51a284c5f0d2366d331f2df56990005d1fe
247
95170096982f600bc86272a10ed3577d85751d4c
416076fbf4d11a7ae40fad011c66aa46a4301b5e
/docs/1.9.0/_sources/generated/torch.cuda.memory_cached.rst.txt
c09be51a284c5f0d2366d331f2df56990005d1fe
115
e4911595d33821101dade849cd6cf5b15df56dea
a6ac9313fed1b0cc233f1021de16ae3a59305d8c
/docs/1.9.0/_sources/generated/torch.clamp.rst.txt
c09be51a284c5f0d2366d331f2df56990005d1fe
74
144a0067ceb2c61ae3298c6901f91d658f856730
fd2b5adf94531c912bfee8aa69cf6be4af7a08db
/docs/1.9.0/generated/torch.Tensor.isneginf.html
c09be51a284c5f0d2366d331f2df56990005d1fe
31,791
a892854f6ae86dfc10c16b6765c15603b145a73a
fa5136bdf86b9c755e1214662ba4a03585551baa
/docs/1.9.0/generated/torch.Tensor.new_tensor.html
c09be51a284c5f0d2366d331f2df56990005d1fe
37,764
227095aa50286c0cb30c26ec3f56b31021fd698b
0f98edd4b56147f15336d273efffee6feed2ae44
/docs/1.9.0/_sources/generated/torch.nn.functional.feature_alpha_dropout.rst.txt
c14f85a8c043900a71231d8a8e128c407071c90f
168
bdfabbf5e9b31051100cc6932f67ade58fe3e836
1e92f0a46dcec62ca4a8e1596f83105f49566d70
/docs/1.9.0/_sources/generated/torch.nn.SiLU.rst.txt
c14f85a8c043900a71231d8a8e128c407071c90f
224
b479459c62f8287f26b4ca6a7717416b28907061
c0461a38972525b7099785a51cc74317a461b99b
/docs/master/_sources/generated/torch.nn.intrinsic.quantized.ConvReLU1d.rst.txt
c14f85a8c043900a71231d8a8e128c407071c90f
265
9617f983ad4e9d54d96caeabc112cc0ba4ab7e91
bf669d4d06526b3418c261def7c71df826e25a50
/docs/master/_sources/generated/torch.equal.rst.txt
c14f85a8c043900a71231d8a8e128c407071c90f
77
f313fd8515b10fd806452b5ad65afbf96455aa1a
717a3ce942f8915a8ace66a0b4b78f2e2f6177ca
/docs/source/_static/img/pytorch-logo-dark.svg
c15b60473f84c78124f1e15c07e14bb85c4a146d
1,745
1407428949dbac5489eef49aa5fb04d3bf0f3710
da319bbe72e498a64b3ac1ca07fad36cf5bf17c5
/android/pytorch_android/src/main/java/org/pytorch/DType.java
c15c6d2438d10eede2b4e698d9d2a5ef3c29d619
759
0fc5b23d2f962bd5739809198cc65af56cbbb2de
5abaac479a7521451f9eb800617c2c91f4ca188d
/NOTICE
c15c6d2438d10eede2b4e698d9d2a5ef3c29d619
21,804
380822f5baabefb20397842e095ac988d00cc39f
ac9897e8ad964459f81f6b3cfaf6cd68e46db85d
/torch/csrc/utils/cpp_stacktraces.cpp
c16936fe4b1f023574d5caf52d477424199167b2
697
efffe752b18f5022a83aad89747f442d1e251c72
c365cd969189e42d752c55a0e62a8bd7fe35b5c1
/torch/csrc/jit/ir/alias_analysis.h
c16936fe4b1f023574d5caf52d477424199167b2
12,772
5300a1ebd65e2dfc18d3a6e7d59ac379c61ff15f
b8b927f3923958cee26c625a87039d4340205de1
/docs/1.10.1/generated/torch.atan.html
c170d6aefbb1eb2d54103e8fdbffef08c6ade1fc
36,340
e0640b562a8d5d3fd816b017068cbdfaf9d02dd2
57b316cc3e9a550efd1d1b8c020910547a4bdfc2
/docs/1.10.1/generated/torch.quantized_max_pool2d.html
c170d6aefbb1eb2d54103e8fdbffef08c6ade1fc
36,530
c6a756b3f663594533c4491fa56e479e2ea53e55
140b9ae95ec10f3ca7323984aa87dbd9883eefd1
/docs/1.12/_sources/generated/torch.quantization.get_observer_dict.rst.txt
c170d6aefbb1eb2d54103e8fdbffef08c6ade1fc
276
2124d62cfe392bc42bb5cd7f5b0049da8aa02177
312e0de2ef4312abca55fedc9c0b0f04e94eec7b
/docs/1.5.0/_modules/torch/nn/utils/prune.html
c170d6aefbb1eb2d54103e8fdbffef08c6ade1fc
165,357
898eadcb47acf5b00a824a3ce89a66f1d12b59f5
21c2fe9c777de06bf5817d17e29697519c6272bb
/docs/1.5.1/search.html
c170d6aefbb1eb2d54103e8fdbffef08c6ade1fc
24,901
0739d8a7eba4554da98e424954f62219aae9eefd
a9450a9dde2c597e19d44fdb6025b0e0fb2ccdf7
/docs/1.9.1/generated/torch.Tensor.swapaxes.html
c170d6aefbb1eb2d54103e8fdbffef08c6ade1fc
31,890
f7b5109c2d826fb384a03536bac4d8d649dde1bb
70c505f7ccbf0a4d12fa0d9e19e0925cba4a3fc8
/docs/1.9.1/generated/torch.cholesky_solve.html
c170d6aefbb1eb2d54103e8fdbffef08c6ade1fc
45,501
4cc73fbc3f4f93d4209717f3ce0da422e966d355
254b836c6e6cbb7d26481903dac94d9f251edda2
/docs/master/generated/torch.Tensor.tan_.html
c170d6aefbb1eb2d54103e8fdbffef08c6ade1fc
36,896
d361c54f5fc3c3526256c0dd1723f7d31a30e7e2
2a72624bf57c8991887b8b0445ab46bf0e8cbe69
/docs/master/generated/torch.ao.nn.quantized.functional.upsample_bilinear.html
c170d6aefbb1eb2d54103e8fdbffef08c6ade1fc
39,743
cd6494b4c1ebe5a6a06225ae0acc7416567e7d4b
fcb3e9ed2fea879bed877cc11e835777254a6411
/datasets/squad_kor_v1/dataset_infos.json
c171267ba256afb69a6f9e6cd7337064a5934c83
2,394
31914cace6cbede9fda35d606bdc2bfeb0f8440d
84a998806e8361ae3f6a1f4cb0a7a22cc4ecb962
/datasets/hard/README.md
c171267ba256afb69a6f9e6cd7337064a5934c83
3,313
5cdf011cfa60a3b739e1b4e53469e9d8a6938d17
9998226cece07256c92ec031f866ef2ac400b609
/datasets/wmt20_mlqe_task1/dataset_infos.json
c171267ba256afb69a6f9e6cd7337064a5934c83
26,166
09c93b0d453a1528c84d9f9625d43a034c05a85e
a3484b6b44eaba6a4163e9f32d8e428870e32c28
/src/datasets/utils/__init__.py
c171267ba256afb69a6f9e6cd7337064a5934c83
1,062
a4fddd5c4dfabca39bfab0115607a8714eeff216
8d2a4bae5dcb4a700a085b7b861cee6466b114b5
/datasets/movie_rationales/movie_rationales.py
c182c0b298272625d1b909e139f6105c02f8e207
3,980
4aa3d884b34e910ea57b56592538b194aeef1df5
2ca223ebc850f8e8164516c8bf838e5fbabfa8dd
/conda/vs2017/install_activate.bat
c180f18c845a24e8d7c98be37d83d526e2a5ea08
1,257
9c4ce77b38534c57ad45c0f97d07b738d62a92d6
6793ef54e6383d8cb3bba804997497708a3b334c
/fairseq/logging/meters.py
c17f10b6d835b6ed65d0e415a5dbf9dcd90c5bfa
7,927
e4e078c47592e7d346a174cdd258867ea37812ae
b3043022d18b661611aad6792078c2c9c7b81377
/caffe2/quantization/server/conv_relu_op.cc
c194a03ab2ef05b7ac93fbc4a5151526c2be9b35
2,360
4c6e28354b04645fc178f88e3f41004d4bc9a0e7
187328f9e4841687fdf484445158c68f3e990be0
/caffe2/python/operator_test/utility_ops_test.py
c194a03ab2ef05b7ac93fbc4a5151526c2be9b35
15,054
e267e74544351e581625f5c228fde5b943fecc55
564f2665d054835293ca2f7ef6170168db969c2c
/caffe2/operators/reduce_front_back_mean_ops.cc
c194a03ab2ef05b7ac93fbc4a5151526c2be9b35
8,600
b61b891eab990ab367d0e8e3bbdd040c1fdef9af
e2d788c8cc100e2ccfcd98a0406111c0df102411
/docs/source/en/model_doc/bart.mdx
c19c07c75704bf22335fb21529fce0fe9b9cd3f6
9,361
6e9b96b173ac13e542717ea2920fed5d83699075
3b04dad33d171d8eca427abcd5601c1b0ff793b5
/src/GenerateKernelU8S8S32ACC16.cc
c19b9a8d64b1a5985547b5b8b4966b64e4cce496
11,285
f101fdb65fd0997868cde7f710febbd12b7375b4
920f4323cf368f8309ae9701b467f11bb913d26a
/caffe2/core/nomnigraph/tests/test_util.cc
c2c2d97577d2c9f4f1c88382273a884017ace748
4,321
7f2c8594b9968d6b4cd919d11a09e870d3fd166d
0c5f2569ec272928aaaae2480c0cc9a5f0f30a8e
/c10/util/complex.h
c2c2d97577d2c9f4f1c88382273a884017ace748
17,970
7833381ed7760316414557d760cdbdac6ef710aa
18f74f49333f481e32a55c52337f1b8e68bc55c5
/caffe2/opt/custom/cc_amrc.cc
c2c2d97577d2c9f4f1c88382273a884017ace748
267
6df47813b698ade64880bf18cc424dd623323722
fd0f8f2acc1484c1be9bdf99ca91102a60125e81
/caffe2/operators/quantized/int8_sigmoid_op.cc
c2c2d97577d2c9f4f1c88382273a884017ace748
987
18121cd8f226007b260fdf326496a4701b8db9d0
d16bce8f3b6e58c63940f63decfcddf2c81aad04
/torch/csrc/autograd/profiler_python.h
c2c2d97577d2c9f4f1c88382273a884017ace748
186
289eed632b4be3978ee0503b9a1e43e5143642ef
178e8f5961246f880ebef45ef77d722ebbe1c344
/torch/csrc/distributed/rpc/testing/faulty_tensorpipe_agent.cpp
c2c2d97577d2c9f4f1c88382273a884017ace748
6,090
c35b9d287a4596ea344059d197bd629f4bce7fa0
02e00acac08d2d1b625c02524eb51c68569515d4
/torch/csrc/jit/passes/symbolic_shape_cache.h
c2c2d97577d2c9f4f1c88382273a884017ace748
1,599
ec53dedc327fb4f149975eb92a14a315a880a6b6
dce25669bf32387cd9d732539af035708d4f98c1
/torch/csrc/jit/tensorexpr/hash_provider.cpp
c2c2d97577d2c9f4f1c88382273a884017ace748
8,728
ac9badedd85a2a57d7ec9dc6bb84e4f3f5c305ff
56ca21f123ed6669a088de3e729188715f1f1754
/torch/csrc/jit/tensorexpr/operators/norm.cpp
c2c2d97577d2c9f4f1c88382273a884017ace748
2,122
193c745e422f38759710edb4af7d97506e9d6904
4ec56f28cdac9d3d066c9ab8e075eedd886f3d98
/datasets/cnn_dailymail/dataset_infos.json
c2c8c28d504404d0cb436bb42680db4fae257728
9,500