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Pascal
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Posts: 47
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Message 60374 - Posted: 7 May 2023 | 17:04:33 UTC
Last modified: 7 May 2023 | 17:38:23 UTC

bonjour.
Quelqu'un pourrait il m'aider car j'ai des erreurs a répétition avec gpugrid sur les calculs ATM et autres.
j'ai essayé avec windows 10 et 11 avec une rtx 3050 8gb,une gtx 1050 ti 4gb
une gtx 1050 et une gtx 750ti.
c'est toujours pareil même en changeant les pilotes nvidia.
j'ai formaté mon pc 2 fois en pensant que cela résoudrait le probleme mais non.
Je trouve une erreur cuda out of memory mais aucune solution en cherchant.
J'ai testé mes barrettes de ram avec memtest mais rien a signaler.elles sont bonnes.J'ai réglé le swap files sur 50000 mégas.
Merci d'avance
mon pc-i5 11400f-40 gigas ddr 2666-ssd 240 gigas-hdd 2 téras-MPG Z590 GAMING EDGE WIFI

Stderr output
<core_client_version>7.20.2</core_client_version>
<![CDATA[
<message>
(unknown error) - exit code 195 (0xc3)</message>
<stderr_txt>
00:40:20 (12464): wrapper (7.9.26016): starting
00:40:20 (12464): wrapper: running .\7za.exe (x pythongpu_windows_x86_64__cuda102.txz -y)

7-Zip (a) 22.01 (x86) : Copyright (c) 1999-2022 Igor Pavlov : 2022-07-15

Scanning the drive for archives:
1 file, 1395331172 bytes (1331 MiB)

Extracting archive: pythongpu_windows_x86_64__cuda102.txz
--
Path = pythongpu_windows_x86_64__cuda102.txz
Type = xz
Physical Size = 1395331172
Method = LZMA2:22 CRC64
Streams = 1203
Blocks = 1203
Cluster Size = 4210688

Everything is Ok

Size: 5063219200
Compressed: 1395331172
00:42:54 (12464): .\7za.exe exited; CPU time 121.593750
00:42:54 (12464): wrapper: running C:\Windows\system32\cmd.exe (/C "del pythongpu_windows_x86_64__cuda102.txz")
00:42:55 (12464): C:\Windows\system32\cmd.exe exited; CPU time 0.000000
00:42:55 (12464): wrapper: running .\7za.exe (x pythongpu_windows_x86_64__cuda102.tar -y)

7-Zip (a) 22.01 (x86) : Copyright (c) 1999-2022 Igor Pavlov : 2022-07-15

Scanning the drive for archives:
1 file, 5063219200 bytes (4829 MiB)

Extracting archive: pythongpu_windows_x86_64__cuda102.tar
--
Path = pythongpu_windows_x86_64__cuda102.tar
Type = tar
Physical Size = 5063219200
Headers Size = 9415168
Code Page = UTF-8
Characteristics = GNU LongName ASCII

Everything is Ok

Files: 18039
Size: 5049287251
Compressed: 5063219200
00:44:08 (12464): .\7za.exe exited; CPU time 19.718750
00:44:08 (12464): wrapper: running C:\Windows\system32\cmd.exe (/C "del pythongpu_windows_x86_64__cuda102.tar")
00:44:09 (12464): C:\Windows\system32\cmd.exe exited; CPU time 0.000000
00:44:09 (12464): wrapper: running python.exe (run.py)
Windows fix executed.
Detected GPUs: 1
Define environment factory
Define algorithm factory
Define storage factory
Define scheme
Created CWorker with worker_index 0
Created GWorker with worker_index 0
Created UWorker with worker_index 0
Created training scheme.
Define learner
Created Learner.
Look for a progress_last_chk file - if exists, adjust target_env_steps
Define train loop
Traceback (most recent call last):
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\pytorchrl\scheme\gradients\g_worker.py", line 196, in get_data
self.next_batch = self.batches.__next__()
AttributeError: 'GWorker' object has no attribute 'batches'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "run.py", line 471, in <module>
main()
File "run.py", line 136, in main
learner.step()
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\pytorchrl\learner.py", line 46, in step
info = self.update_worker.step()
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\pytorchrl\scheme\updates\u_worker.py", line 118, in step
self.updater.step()
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\pytorchrl\scheme\updates\u_worker.py", line 259, in step
grads = self.local_worker.step(self.decentralized_update_execution)
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\pytorchrl\scheme\gradients\g_worker.py", line 178, in step
self.get_data()
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\pytorchrl\scheme\gradients\g_worker.py", line 226, in get_data
self.storage.before_gradients()
File "C:\Users\pascal\Desktop\boinc\slots\27\python_dependencies\buffer.py", line 216, in before_gradients
self.apply_rebel_logic()
File "C:\Users\pascal\Desktop\boinc\slots\27\python_dependencies\buffer.py", line 248, in apply_rebel_logic
ref_value = self.predict_reference_value()
File "C:\Users\pascal\Desktop\boinc\slots\27\python_dependencies\buffer.py", line 260, in predict_reference_value
return self.actor.predictor.reward_predictor(
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\pytorchrl\agent\actors\feature_extractors\cnn.py", line 121, in forward
out = self.feature_extractor(inputs)
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\torch\nn\modules\container.py", line 141, in forward
input = module(input)
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\torch\nn\modules\conv.py", line 446, in forward
return self._conv_forward(input, self.weight, self.bias)
File "C:\Users\pascal\Desktop\boinc\slots\27\lib\site-packages\torch\nn\modules\conv.py", line 442, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: CUDA out of memory. Tried to allocate 202.00 MiB (GPU 0; 2.00 GiB total capacity; 915.50 MiB already allocated; 99.26 MiB free; 938.00 MiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
00:51:17 (12464): python.exe exited; CPU time 1205.953125
00:51:17 (12464): app exit status: 0x1
00:51:17 (12464): called boinc_finish(195)
0 bytes in 0 Free Blocks.
570 bytes in 9 Normal Blocks.
1144 bytes in 1 CRT Blocks.
0 bytes in 0 Ignore Blocks.
0 bytes in 0 Client Blocks.
Largest number used: 0 bytes.
Total allocations: 7319403 bytes.
Dumping objects ->
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{56} normal block at 0x000002A15E00A350, 16 bytes long.
Data: < &#192;&#182;&#242;&#247; > 18 C0 B6 F2 F7 7F 00 00 00 00 00 00 00 00 00 00
Object dump complete.

</stderr_txt>[/img]

exemple 2


Nom p38_mln_m2i_1-QUICO_ATM_Sage_xTB-3-5-RND6956_0
Unité de travail (WU) 27490043
Créé 6 May 2023 | 11:40:42 UTC
Envoyé 6 May 2023 | 12:34:07 UTC
Reçu 6 May 2023 | 12:43:26 UTC
État du serveur Sur
Résultats Erreur de calcul
État du client Erreur de calcul
État à la sortie 195 (0xc3) EXIT_CHILD_FAILED
ID de l'ordinateur 604688
Date limite de rapport 11 May 2023 | 12:34:07 UTC
Temps de fonctionnement 89.39
Temps de CPU 0.00
Valider l'état Invalide
Crédit 0.00
Version de l'application ATMbeta: Free energy calculations of protein-ligand binding v1.09 (cuda1121)
Stderr output
<core_client_version>7.20.2</core_client_version>
<![CDATA[
<message>
(unknown error) - exit code 195 (0xc3)</message>
<stderr_txt>
14:41:52 (8792): wrapper (7.9.26016): starting
14:41:52 (8792): wrapper: running python.exe (bin/conda-unpack)
14:41:56 (8792): python.exe exited; CPU time 0.000000
14:41:56 (8792): wrapper: running Library/usr/bin/tar.exe (xjvf input.tar.bz2)
p38_mln_m2i_0.xml
p38_mln_m2i_asyncre.cntl
p38_mln_m2i.inpcrd
p38_mln_m2i.prmtop
run.bat
run.sh
14:41:57 (8792): Library/usr/bin/tar.exe exited; CPU time 0.000000
14:41:57 (8792): wrapper: running C:/Windows/system32/cmd.exe (/c call run.bat)
14:41:58 (8792): C:/Windows/system32/cmd.exe exited; CPU time 0.000000
14:41:58 (8792): app exit status: 0x1
14:41:58 (8792): called boinc_finish(195)
0 bytes in 0 Free Blocks.
330 bytes in 4 Normal Blocks.
1144 bytes in 1 CRT Blocks.
0 bytes in 0 Ignore Blocks.
0 bytes in 0 Client Blocks.
Largest number used: 0 bytes.
Total allocations: 339276 bytes.
Dumping objects ->
{3078503} normal block at 0x00000223F636CA60, 64 bytes long.
Data: <PATH=C:\Users\pa> 50 41 54 48 3D 43 3A 5C 55 73 65 72 73 5C 70 61
{3078482} normal block at 0x00000223F47F2E30, 141 bytes long.
Data: <<project_prefere> 3C 70 72 6F 6A 65 63 74 5F 70 72 65 66 65 72 65
..\api\boinc_api.cpp(309) : {3078479} normal block at 0x00000223F47C9590, 8 bytes long.
Data: < y&#244;# > 00 00 79 F4 23 02 00 00
{3077838} normal block at 0x00000223F47F3170, 141 bytes long.
Data: <<project_prefere> 3C 70 72 6F 6A 65 63 74 5F 70 72 65 66 65 72 65
{3077229} normal block at 0x00000223F47C95E0, 8 bytes long.
Data: <&#240;&#234;&#138;&#244;# > F0 EA 8A F4 23 02 00 00
..\zip\boinc_zip.cpp(122) : {276} normal block at 0x00000223F47C8710, 260 bytes long.
Data: < > 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
{261} normal block at 0x00000223F47CE570, 16 bytes long.
Data: <&#216; &#244;# > D8 00 81 F4 23 02 00 00 00 00 00 00 00 00 00 00
{260} normal block at 0x00000223F47CEDE0, 16 bytes long.
Data: <&#176; &#244;# > B0 00 81 F4 23 02 00 00 00 00 00 00 00 00 00 00
{259} normal block at 0x00000223F47CE660, 16 bytes long.
Data: < &#244;# > 88 00 81 F4 23 02 00 00 00 00 00 00 00 00 00 00
{258} normal block at 0x00000223F47CE700, 16 bytes long.
Data: <` &#244;# > 60 00 81 F4 23 02 00 00 00 00 00 00 00 00 00 00
{257} normal block at 0x00000223F47CF1A0, 16 bytes long.
Data: <8 &#244;# > 38 00 81 F4 23 02 00 00 00 00 00 00 00 00 00 00
{256} normal block at 0x00000223F47CF150, 16 bytes long.
Data: < &#244;# > 10 00 81 F4 23 02 00 00 00 00 00 00 00 00 00 00
{255} normal block at 0x00000223F480E8B0, 32 bytes long.
Data: <CUDA_DEVICE=0 PU> 43 55 44 41 5F 44 45 56 49 43 45 3D 30 00 50 55
{254} normal block at 0x00000223F47CEE80, 16 bytes long.
Data: <P&#207;|&#244;# > 50 CF 7C F4 23 02 00 00 00 00 00 00 00 00 00 00
{253} normal block at 0x00000223F47CCF50, 40 bytes long.
Data: < &#238;|&#244;# &#176;&#232; &#244;# > 80 EE 7C F4 23 02 00 00 B0 E8 80 F4 23 02 00 00
{252} normal block at 0x00000223F47CF100, 16 bytes long.
Data: <&#240;&#255; &#244;# > F0 FF 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{251} normal block at 0x00000223F47CE610, 16 bytes long.
Data: <&#200;&#255; &#244;# > C8 FF 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{250} normal block at 0x00000223F480F150, 32 bytes long.
Data: <C:/Windows/syste> 43 3A 2F 57 69 6E 64 6F 77 73 2F 73 79 73 74 65
{249} normal block at 0x00000223F47CF330, 16 bytes long.
Data: <&#160;&#255; &#244;# > A0 FF 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{248} normal block at 0x00000223F480F450, 32 bytes long.
Data: <xjvf input.tar.b> 78 6A 76 66 20 69 6E 70 75 74 2E 74 61 72 2E 62
{247} normal block at 0x00000223F47CF3D0, 16 bytes long.
Data: <&#232;&#254; &#244;# > E8 FE 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{246} normal block at 0x00000223F47CF0B0, 16 bytes long.
Data: <&#192;&#254; &#244;# > C0 FE 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{245} normal block at 0x00000223F47CF240, 16 bytes long.
Data: < &#254; &#244;# > 98 FE 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{244} normal block at 0x00000223F47CF060, 16 bytes long.
Data: <p&#254; &#244;# > 70 FE 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{243} normal block at 0x00000223F47CF010, 16 bytes long.
Data: <H&#254; &#244;# > 48 FE 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{242} normal block at 0x00000223F47CECA0, 16 bytes long.
Data: < &#254; &#244;# > 20 FE 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{240} normal block at 0x00000223F47CEE30, 16 bytes long.
Data: <0&#208;|&#244;# > 30 D0 7C F4 23 02 00 00 00 00 00 00 00 00 00 00
{239} normal block at 0x00000223F47CD030, 40 bytes long.
Data: <0&#238;|&#244;# `&#202;6&#246;# > 30 EE 7C F4 23 02 00 00 60 CA 36 F6 23 02 00 00
{238} normal block at 0x00000223F47CF290, 16 bytes long.
Data: < &#254; &#244;# > 00 FE 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{237} normal block at 0x00000223F47CED90, 16 bytes long.
Data: <&#216;&#253; &#244;# > D8 FD 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{236} normal block at 0x00000223F480E970, 32 bytes long.
Data: <Library/usr/bin/> 4C 69 62 72 61 72 79 2F 75 73 72 2F 62 69 6E 2F
{235} normal block at 0x00000223F47CEED0, 16 bytes long.
Data: <&#176;&#253; &#244;# > B0 FD 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{234} normal block at 0x00000223F480EA90, 32 bytes long.
Data: <bin/conda-unpack> 62 69 6E 2F 63 6F 6E 64 61 2D 75 6E 70 61 63 6B
{233} normal block at 0x00000223F47CEFC0, 16 bytes long.
Data: <&#248;&#252; &#244;# > F8 FC 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{232} normal block at 0x00000223F47CEF20, 16 bytes long.
Data: <&#208;&#252; &#244;# > D0 FC 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{231} normal block at 0x00000223F47CE7A0, 16 bytes long.
Data: <&#168;&#252; &#244;# > A8 FC 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{230} normal block at 0x00000223F47CF420, 16 bytes long.
Data: < &#252; &#244;# > 80 FC 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{229} normal block at 0x00000223F47CED40, 16 bytes long.
Data: <X&#252; &#244;# > 58 FC 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{228} normal block at 0x00000223F47CF4C0, 16 bytes long.
Data: <0&#252; &#244;# > 30 FC 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{227} normal block at 0x00000223F47CF470, 16 bytes long.
Data: < &#252; &#244;# > 10 FC 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{226} normal block at 0x00000223F47CEF70, 16 bytes long.
Data: <&#232;&#251; &#244;# > E8 FB 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{225} normal block at 0x00000223F47C94F0, 16 bytes long.
Data: <&#192;&#251; &#244;# > C0 FB 80 F4 23 02 00 00 00 00 00 00 00 00 00 00
{224} normal block at 0x00000223F480FBC0, 1488 bytes long.
Data: <&#240;&#148;|&#244;# python.e> F0 94 7C F4 23 02 00 00 70 79 74 68 6F 6E 2E 65
{88} normal block at 0x00000223F480ECD0, 32 bytes long.
Data: <windows_x86_64__> 77 69 6E 64 6F 77 73 5F 78 38 36 5F 36 34 5F 5F
{87} normal block at 0x00000223F47C9400, 16 bytes long.
Data: <p&#206;|&#244;# > 70 CE 7C F4 23 02 00 00 00 00 00 00 00 00 00 00
{86} normal block at 0x00000223F47CCE70, 40 bytes long.
Data: < &#148;|&#244;# &#208;&#236; &#244;# > 00 94 7C F4 23 02 00 00 D0 EC 80 F4 23 02 00 00
{65} normal block at 0x00000223F47C97C0, 16 bytes long.
Data: < &#234;&#161; &#247; > 80 EA A1 1C F7 7F 00 00 00 00 00 00 00 00 00 00
{64} normal block at 0x00000223F47C9860, 16 bytes long.
Data: <@&#233;&#161; &#247; > 40 E9 A1 1C F7 7F 00 00 00 00 00 00 00 00 00 00
{63} normal block at 0x00000223F47C9180, 16 bytes long.
Data: <&#248;W&#158; &#247; > F8 57 9E 1C F7 7F 00 00 00 00 00 00 00 00 00 00
{62} normal block at 0x00000223F47C9770, 16 bytes long.
Data: <&#216;W&#158; &#247; > D8 57 9E 1C F7 7F 00 00 00 00 00 00 00 00 00 00
{61} normal block at 0x00000223F47C9C70, 16 bytes long.
Data: <P &#158; &#247; > 50 04 9E 1C F7 7F 00 00 00 00 00 00 00 00 00 00
{60} normal block at 0x00000223F47C9540, 16 bytes long.
Data: <0 &#158; &#247; > 30 04 9E 1C F7 7F 00 00 00 00 00 00 00 00 00 00
{59} normal block at 0x00000223F47C99A0, 16 bytes long.
Data: <&#224; &#158; &#247; > E0 02 9E 1C F7 7F 00 00 00 00 00 00 00 00 00 00
{58} normal block at 0x00000223F47C9BD0, 16 bytes long.
Data: < &#158; &#247; > 10 04 9E 1C F7 7F 00 00 00 00 00 00 00 00 00 00
{57} normal block at 0x00000223F47C8F50, 16 bytes long.
Data: <p &#158; &#247; > 70 04 9E 1C F7 7F 00 00 00 00 00 00 00 00 00 00
{56} normal block at 0x00000223F47C8DC0, 16 bytes long.
Data: < &#192;&#156; &#247; > 18 C0 9C 1C F7 7F 00 00 00 00 00 00 00 00 00 00
Object dump complete.

</stderr_txt>
]]>
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