speed up kl div loss by li-roy · Pull Request #10336 · pytorch/pytorch

li-roy · 2018-08-07T23:33:18Z

Moved kl div loss to aten.

benchmarks for 5000 iterations on input size (1000,100)

New

cuda:
forward [0.9736350309103727, 0.9922929517924786, 0.9694818360731006]
input requires_grad=True:
backward [0.5595634011551738, 0.558339926879853, 0.5546616851352155]
double backward [1.2445648494176567, 1.2245905152522027, 1.2349751549772918]
target requires_grad=True:
backward (new C++) [0.9489959231577814, 0.9553070571273565, 0.9556351029314101]
double backward (new C++) [1.8184774098917842, 1.8164670099504292, 1.845708406995982]

cpu:
forward (new C++) [7.892430987209082, 8.3068826389499, 7.985283812973648]
input requires_grad=True:
backward (new C++) [4.328460982069373, 4.45323242014274, 4.27946363389492]
double backward (new C++) [5.153504415880889, 4.629372010007501, 4.712803596165031]
target requires_grad=True:
backward (new C++) [3.4181493939831853, 3.3771288259886205, 3.7086612950079143]
double backward (new C++) [0.21922698011621833, 0.1858532396145165, 0.19477044604718685]

Old

cuda:
forward [3.101281268056482, 3.068499860819429, 3.0527669726870954]
input requires_grad=True:
backward [0.5650290949270129, 0.5730433077551425, 0.5588279226794839]
double backward [1.1287697306834161, 1.13834543293342, 1.1298578432761133]
target requires_grad=True:
backward [0.9470391101203859, 0.9560198178514838, 0.9750375030562282]
double backward [1.85760727385059, 1.7989214668050408, 1.788982989732176]

cpu:
forward (new C++) [12.474591840058565, 12.511441555805504, 12.666544185951352]
input requires_grad=True:
backward (new C++) [7.660991386976093, 7.449987292289734, 7.513917901087552]
double backward (new C++) [4.073225498665124, 4.264980792999268, 4.429787891916931]
target requires_grad=True:
backward (new C++) [3.448499082121998, 3.9072313378565013, 3.2433970272541046]
double backward (new C++) [2.126378359273076, 1.9045450473204255, 1.7932004742324352]

ssnl · 2018-08-08T00:20:09Z

Nice. Is the benchmark on cpu or cuda?

li-roy · 2018-08-08T04:37:08Z

updated with more complete benchmark info

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li-roy · 2018-08-09T19:22:33Z

@pytorchbot retest this please

aten/src/ATen/nn.yaml

aten/src/ATen/native/Loss.cpp

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ssnl

Looks good. But please make sure that maths is correct before merging.

aten/src/ATen/native/Loss.cpp


 namespace at { namespace native {

+Tensor apply_loss_reduction(const Tensor& unreduced, int64_t reduction) {


aten/src/ATen/native/Loss.cpp

+}
+
+Tensor kl_div_backward_cpu(const Tensor& grad, const Tensor& input, const Tensor& target, int64_t reduction) {
+  auto grad_input = grad.type().zeros_like(input);


aten/src/ATen/native/Loss.cpp

-    return output.sum() / output.numel();
-  } else if (reduction == Reduction::Sum) {
-    return output.sum();
+    return grad_input / input.numel();


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li-roy · 2018-08-26T07:15:50Z

@pytorchbot retest this please

Summary: Moved kl div loss to aten. benchmarks for 5000 iterations on input size (1000,100) New ``` cuda: forward [0.9736350309103727, 0.9922929517924786, 0.9694818360731006] input requires_grad=True: backward [0.5595634011551738, 0.558339926879853, 0.5546616851352155] double backward [1.2445648494176567, 1.2245905152522027, 1.2349751549772918] target requires_grad=True: backward (new C++) [0.9489959231577814, 0.9553070571273565, 0.9556351029314101] double backward (new C++) [1.8184774098917842, 1.8164670099504292, 1.845708406995982] cpu: forward (new C++) [7.892430987209082, 8.3068826389499, 7.985283812973648] input requires_grad=True: backward (new C++) [4.328460982069373, 4.45323242014274, 4.27946363389492] double backward (new C++) [5.153504415880889, 4.629372010007501, 4.712803596165031] target requires_grad=True: backward (new C++) [3.4181493939831853, 3.3771288259886205, 3.7086612950079143] double backward (new C++) [0.21922698011621833, 0.1858532396145165, 0.19477044604718685] ``` Old ``` cuda: forward [3.101281268056482, 3.068499860819429, 3.0527669726870954] input requires_grad=True: backward [0.5650290949270129, 0.5730433077551425, 0.5588279226794839] double backward [1.1287697306834161, 1.13834543293342, 1.1298578432761133] target requires_grad=True: backward [0.9470391101203859, 0.9560198178514838, 0.9750375030562282] double backward [1.85760727385059, 1.7989214668050408, 1.788982989732176] cpu: forward (new C++) [12.474591840058565, 12.511441555805504, 12.666544185951352] input requires_grad=True: backward (new C++) [7.660991386976093, 7.449987292289734, 7.513917901087552] double backward (new C++) [4.073225498665124, 4.264980792999268, 4.429787891916931] target requires_grad=True: backward (new C++) [3.448499082121998, 3.9072313378565013, 3.2433970272541046] double backward (new C++) [2.126378359273076, 1.9045450473204255, 1.7932004742324352] ``` Pull Request resolved: pytorch/pytorch#10336 Differential Revision: D9213636 Pulled By: li-roy fbshipit-source-id: 27cc530f6276f58d35dc7a1d56dfc758a0fc4a7b

Summary: Moved kl div loss to aten. benchmarks for 5000 iterations on input size (1000,100) New ``` cuda: forward [0.9736350309103727, 0.9922929517924786, 0.9694818360731006] input requires_grad=True: backward [0.5595634011551738, 0.558339926879853, 0.5546616851352155] double backward [1.2445648494176567, 1.2245905152522027, 1.2349751549772918] target requires_grad=True: backward (new C++) [0.9489959231577814, 0.9553070571273565, 0.9556351029314101] double backward (new C++) [1.8184774098917842, 1.8164670099504292, 1.845708406995982] cpu: forward (new C++) [7.892430987209082, 8.3068826389499, 7.985283812973648] input requires_grad=True: backward (new C++) [4.328460982069373, 4.45323242014274, 4.27946363389492] double backward (new C++) [5.153504415880889, 4.629372010007501, 4.712803596165031] target requires_grad=True: backward (new C++) [3.4181493939831853, 3.3771288259886205, 3.7086612950079143] double backward (new C++) [0.21922698011621833, 0.1858532396145165, 0.19477044604718685] ``` Old ``` cuda: forward [3.101281268056482, 3.068499860819429, 3.0527669726870954] input requires_grad=True: backward [0.5650290949270129, 0.5730433077551425, 0.5588279226794839] double backward [1.1287697306834161, 1.13834543293342, 1.1298578432761133] target requires_grad=True: backward [0.9470391101203859, 0.9560198178514838, 0.9750375030562282] double backward [1.85760727385059, 1.7989214668050408, 1.788982989732176] cpu: forward (new C++) [12.474591840058565, 12.511441555805504, 12.666544185951352] input requires_grad=True: backward (new C++) [7.660991386976093, 7.449987292289734, 7.513917901087552] double backward (new C++) [4.073225498665124, 4.264980792999268, 4.429787891916931] target requires_grad=True: backward (new C++) [3.448499082121998, 3.9072313378565013, 3.2433970272541046] double backward (new C++) [2.126378359273076, 1.9045450473204255, 1.7932004742324352] ``` Pull Request resolved: pytorch#10336 Differential Revision: D9213636 Pulled By: li-roy fbshipit-source-id: 27cc530f6276f58d35dc7a1d56dfc758a0fc4a7b

li-roy requested review from apaszke, colesbury, ezyang, gchanan, soumith and zdevito as code owners August 7, 2018 23:33

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ailzhang added the ready for review (this tag is deprecated) All PRs are ready for review unless they are draft, WIP, or have undismissed requested changes label Aug 21, 2018

Roy Li added 5 commits August 23, 2018 16:13

speed up kl div loss

773ef1d

try to fix compile

0376459

define cuda kernel separately

1a2c6b8

fix backwards

7241711

fix name

02418d9

li-roy force-pushed the kldiv branch from 76bf3b0 to 02418d9 Compare August 24, 2018 00:08

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ssnl approved these changes Aug 24, 2018

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address comments

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facebook-github-bot closed this in f2bb9f0 Aug 27, 2018

ezyang added the merged label Jun 26, 2019


		namespace at { namespace native {

		Tensor apply_loss_reduction(const Tensor& unreduced, int64_t reduction) {

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li-roy commented Aug 7, 2018 •

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