diff --git "a/mlip_arena/tasks/diatomics/run.ipynb" "b/mlip_arena/tasks/diatomics/run.ipynb" --- "a/mlip_arena/tasks/diatomics/run.ipynb" +++ "b/mlip_arena/tasks/diatomics/run.ipynb" @@ -2,18 +2,17 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "3200850a-b8fb-4f50-9815-16ae8da0f942", "metadata": { "tags": [] }, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "WARNING:root:Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.\n", - "WARNING:root:Skipping scheduler setup. No training set found.\n" + "Selected GPU cuda:0 with 40240.80 MB free memory from 1 GPUs\n" ] } ], @@ -32,14 +31,14 @@ "\n", "from mlip_arena.models.utils import REGISTRY, MLIPEnum\n", "\n", - "model_name = \"EquiformerV2(OC20)\"\n", + "model_name = \"ORB\"\n", "\n", "calc = MLIPEnum[model_name].value()" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 14, "id": "90887faa-1601-4c4c-9c44-d16731471d7f", "metadata": { "scrolled": true, @@ -49,7 +48,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "369887c2a75d4a839bb9e2856f43c4bf", + "model_id": "2a34049b06f74c64beb33d2e401fa32e", "version_major": 2, "version_minor": 0 }, @@ -70,7 +69,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "49c313763b7b4ca78dd0e9c76ccc8c09", + "model_id": "82a52529ce86432f95a5f463447066e6", "version_major": 2, "version_minor": 0 }, @@ -91,7 +90,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9b3dfaec15854b0e8ac1e96edeef9a64", + "model_id": "de8eaef64c274ea9a8607c7fbe100600", "version_major": 2, "version_minor": 0 }, @@ -112,7 +111,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b9f5ad4ab8864959844f563b0ba9426d", + "model_id": "d3b9908cae0a48a7b1bbf70ee1129f32", "version_major": 2, "version_minor": 0 }, @@ -133,7 +132,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0061e8fee6824e5194fc230b55b157b0", + "model_id": "134edb09bf614ca384bad4f62341f253", "version_major": 2, "version_minor": 0 }, @@ -154,7 +153,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "94a0585840ac452a83808f93a1c81c9d", + "model_id": "34ec8e0c4e0440869b2e9cc10a019940", "version_major": 2, "version_minor": 0 }, @@ -175,7 +174,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9b33f7d35250471b8dae290ed5e2e0db", + "model_id": "023b7694e482409ba2049511c8fc9e9c", "version_major": 2, "version_minor": 0 }, @@ -196,7 +195,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7d99182316b446948f9ef57319c1e1d5", + "model_id": "f65690a50033416ca3bdd85087894165", "version_major": 2, "version_minor": 0 }, @@ -217,7 +216,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1ed9abdb5acf4eb68061f9013de27a3c", + "model_id": "de08977d3ae4425e83498967cfa75a38", "version_major": 2, "version_minor": 0 }, @@ -238,7 +237,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "139f068533694029aeb8c2aa65585d24", + "model_id": "328152e659c246a4983ea98310ecbc78", "version_major": 2, "version_minor": 0 }, @@ -259,7 +258,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c62aece4979148eb8f97652dc13ecf03", + "model_id": "ae4e8aae854f46a18d087f483f73a7c2", "version_major": 2, "version_minor": 0 }, @@ -280,7 +279,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9d51da0db0d04cf69640cbe2543be19a", + "model_id": "08c7355cb19043dfbadcc35489aff0f9", "version_major": 2, "version_minor": 0 }, @@ -301,7 +300,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5a93839d81694e368d9f0397a85f8349", + "model_id": "ba8a4514d18b4168896ced34ecdc8afc", "version_major": 2, "version_minor": 0 }, @@ -322,7 +321,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7081441204f7428f95a90d8ea77fd887", + "model_id": "60f622615590415a811160bec79d6a46", "version_major": 2, "version_minor": 0 }, @@ -343,7 +342,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "639b989121de47a593e026b969d5d364", + "model_id": "8654d0c23c4f451eb723962d2e188c9e", "version_major": 2, "version_minor": 0 }, @@ -364,7 +363,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ed98f022c8be424cb1ab6ec6b3202ebb", + "model_id": "3fa40b18a2c74573968416cecc7ea826", "version_major": 2, "version_minor": 0 }, @@ -385,7 +384,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "bd45b179f2e44f4196652916c7a6e1b3", + "model_id": "3a3bfd6b13fc4543a01fa9794d5e82e1", "version_major": 2, "version_minor": 0 }, @@ -406,7 +405,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "94cc6eb0ca684a66862e3fa8bbde6486", + "model_id": "9e74d0f257dc4d3eb3700a3d012964fe", "version_major": 2, "version_minor": 0 }, @@ -427,7 +426,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2b240937ac0840b1baeae1e6640f65e1", + "model_id": "6a5081c2749d426cb53aeedcdf42c1a1", "version_major": 2, "version_minor": 0 }, @@ -448,7 +447,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "107431445bc449fa8e05d76f38e24ba5", + "model_id": "7ba965cf95b64a2db36f9a18696b1328", "version_major": 2, "version_minor": 0 }, @@ -469,7 +468,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5dd6f8e61d914bb29575b7c8787a2d8f", + "model_id": "6ef0ca32999c4c12acc0f51200b0f463", "version_major": 2, "version_minor": 0 }, @@ -490,7 +489,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3a104bae76f449e49596fefbe8622510", + "model_id": "7c8a9067bfde4538b94f60d1379e1c81", "version_major": 2, "version_minor": 0 }, @@ -511,7 +510,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8d06a848b8954ef89f249ab0ff2c050a", + "model_id": "c6a89e9e33334225a37e323430599fb1", "version_major": 2, "version_minor": 0 }, @@ -532,7 +531,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6533c1992bd145498b914eddaa439458", + "model_id": "b94b011139e2485b8edfdf8eae5b3a96", "version_major": 2, "version_minor": 0 }, @@ -553,7 +552,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "99e05bc1d56240ff9eba9fdaadffe5a9", + "model_id": "a34a7474b2424d6da2415eedc4eb5ed5", "version_major": 2, "version_minor": 0 }, @@ -574,7 +573,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9b8186d0950d42f490afb1a0b1992a7f", + "model_id": "3a1385681aa34d50830e1786b375dc1b", "version_major": 2, "version_minor": 0 }, @@ -595,7 +594,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4da0b4b0f44842ed8c0f3a5bc930748d", + "model_id": "96a14120762b41edbbe5fa2801465c00", "version_major": 2, "version_minor": 0 }, @@ -616,7 +615,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1c763f1cc7fc41a3ab9229c09bef82b2", + "model_id": "50c01502939f4a089e240a32a19e4715", "version_major": 2, "version_minor": 0 }, @@ -637,7 +636,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "116ff3d8d56543bfbcfd2ae5765b0086", + "model_id": "8318f5bea5b34eebbe3fa62d46a6ddd3", "version_major": 2, "version_minor": 0 }, @@ -658,7 +657,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fde036093cce48b9b92bf4d6d36d2153", + "model_id": "7b4fb01265f6484f8e5da57da648cad6", "version_major": 2, "version_minor": 0 }, @@ -679,7 +678,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c1e073cd73cf4aa3bbc0d41575d7a9ee", + "model_id": "d5466219b42644beaa44933e080d97fd", "version_major": 2, "version_minor": 0 }, @@ -700,7 +699,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "cb7a2e3600c143c38b665167002a16ea", + "model_id": "76173ffef24649ca9cb3db75d342bf39", "version_major": 2, "version_minor": 0 }, @@ -721,7 +720,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4a4b22ca606240feb7a9eca83b320e2d", + "model_id": "d23e93b476eb423992f0622482c31028", "version_major": 2, "version_minor": 0 }, @@ -742,7 +741,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "70b7afef2a6b4f13b0d0a557ddd9391f", + "model_id": "71e6eba6689441159c1143cd674822b3", "version_major": 2, "version_minor": 0 }, @@ -763,7 +762,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "017886f6220b4fdeb2e5eb51eba5c12a", + "model_id": "d2a6fe20ec5b4031a34d4f7ba890facd", "version_major": 2, "version_minor": 0 }, @@ -784,7 +783,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6e162d579cd1479694acbbe1ad202503", + "model_id": "af11139f3eaa4484a53bee33ea7a2d35", "version_major": 2, "version_minor": 0 }, @@ -805,7 +804,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f6cec4bd4b3d4749a7a6a4014028681e", + "model_id": "d5b8a887e947405bb2a62f9e6b2bb73c", "version_major": 2, "version_minor": 0 }, @@ -826,7 +825,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d22ac8f63a54423b8dad61c55baf1032", + "model_id": "eedd87ebf0f842a7ad71c077be48d83a", "version_major": 2, "version_minor": 0 }, @@ -847,7 +846,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "da596918a05b4aad9264eef3bc4e024a", + "model_id": "7d1c3e21586343279bbad3b96c8440d0", "version_major": 2, "version_minor": 0 }, @@ -868,7 +867,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a0b9d0292c014223b7f953679a677a45", + "model_id": "2d24c0b823ba4e2e8192dbd27cc9b94c", "version_major": 2, "version_minor": 0 }, @@ -889,7 +888,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "cf7503a77d7c4c9fa9d0d08ae15f2a57", + "model_id": "4a2829b006444ac8a1e75f6ace407e24", "version_major": 2, "version_minor": 0 }, @@ -910,7 +909,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5af26a7030844b7a996830c02d4b2861", + "model_id": "891b7f1a99ae46efb7b197409abf5a1a", "version_major": 2, "version_minor": 0 }, @@ -931,7 +930,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "37b9826d0190435b859d0bc4d29de6e6", + "model_id": "7f91c52d6a5d47c99bea0e6ff2fc3b07", "version_major": 2, "version_minor": 0 }, @@ -952,7 +951,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "611b052c1d2342a4a3632da18d52875e", + "model_id": "c8725491bc944e128ef800c09fdb45f9", "version_major": 2, "version_minor": 0 }, @@ -973,7 +972,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0ec2367a8b5e4d2fb902d34d0325b0c9", + "model_id": "4a622084126e4e26957372e5b3915a21", "version_major": 2, "version_minor": 0 }, @@ -994,7 +993,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c3fa28bcfc984e498c9ab2202850c2c3", + "model_id": "e0fc5917c77142db9ffa1d028442e0d4", "version_major": 2, "version_minor": 0 }, @@ -1015,7 +1014,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4b88ed0ec46e47b5b004221d3532c44a", + "model_id": "7b4b74b817aa4acf9795a23df0a91cd4", "version_major": 2, "version_minor": 0 }, @@ -1036,7 +1035,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f68f0da24d21425b8bdd283312c5f97e", + "model_id": "48b1a2a0c7174dfa8e00e77d1a96ca72", "version_major": 2, "version_minor": 0 }, @@ -1057,7 +1056,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "57aaef9090124d4e9ad4773fb5b51aa5", + "model_id": "2b186742556b41cdb6b7948ea28a290f", "version_major": 2, "version_minor": 0 }, @@ -1078,7 +1077,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "bf525a58cdd546df8f0fa77fa85b3147", + "model_id": "65d7f43323ed4f98855be84066f0fe09", "version_major": 2, "version_minor": 0 }, @@ -1099,7 +1098,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8b01be04509d44dda671f8d58b7d64c8", + "model_id": "9cbb5d7d967e4419816693ec9b4ece4c", "version_major": 2, "version_minor": 0 }, @@ -1120,7 +1119,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b8d5afa02f9d4383a034df1d4b49070f", + "model_id": "5ae79add3902404fa215a6af7a2525df", "version_major": 2, "version_minor": 0 }, @@ -1141,7 +1140,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5f36557b54824fdba14ece96998c9f17", + "model_id": "0dde4914cef24d40b375684cc2530dbe", "version_major": 2, "version_minor": 0 }, @@ -1162,7 +1161,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fb940fa44873430987cf4150e59d087a", + "model_id": "a8fc22c9ac874ea8bba2762e015227e1", "version_major": 2, "version_minor": 0 }, @@ -1183,7 +1182,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "01212c06ff9e4529b99b8aa1e9956927", + "model_id": "c1a5cdf4a14e407380b0370c2b7ccece", "version_major": 2, "version_minor": 0 }, @@ -1204,7 +1203,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "03218e5e76e14550b977f793b2e94b09", + "model_id": "50310e69a76a42629828e76a6198f01a", "version_major": 2, "version_minor": 0 }, @@ -1225,7 +1224,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1237189041bc4a55858d0d2dad04f907", + "model_id": "72dac368f194409a8595141ae1a4b0da", "version_major": 2, "version_minor": 0 }, @@ -1246,7 +1245,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c7ede19e9cfe44a99086e5d6d8d85378", + "model_id": "f216bf02086744428c860dece5094292", "version_major": 2, "version_minor": 0 }, @@ -1267,7 +1266,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"model_id": "4491b20d4f054bb885cd023e45edcab9", + "model_id": "070005a27b7e4d9fb2fc838d08d26575", "version_major": 2, "version_minor": 0 }, @@ -1393,7 +1392,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0d8e5a1fb31b4903915d064b3abddd1d", + "model_id": "ef0047d15224430c971153c153b99a2f", "version_major": 2, "version_minor": 0 }, @@ -1414,7 +1413,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1f29a2fe75db45a7997c53aa69211019", + "model_id": "1bcbffde6a8e429daef279876b528c15", "version_major": 2, "version_minor": 0 }, @@ -1435,7 +1434,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c7ff46e89cc246d18f16108fe482b9ad", + "model_id": "baa9e8204ab143f787b3db78b268b198", "version_major": 2, "version_minor": 0 }, @@ -1456,7 +1455,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8230046992aa40d9929cc2f4a9d4dd77", + "model_id": "aeaaaa130724471e84166b101554192b", "version_major": 2, "version_minor": 0 }, @@ -1477,7 +1476,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "40d79b7eace04cfc9fdc3361ec797601", + "model_id": "cec839ccce844caf88528ae86ba2988d", "version_major": 2, "version_minor": 0 }, @@ -1498,7 +1497,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6765a52d1f8a47b28ec3de0e7621c799", + "model_id": "c377eb86adc64ff2a9caa0a3b307b8c2", "version_major": 2, "version_minor": 0 }, @@ -1519,7 +1518,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "30a8b6e7bf92478f922c6b613306663f", + "model_id": "deeda8d098944f8eaca1eba6c6b32288", "version_major": 2, "version_minor": 0 }, @@ -1540,7 +1539,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0cd262da6a9c4720b46c3dce5b8afc99", + "model_id": "0eafdf00a5534fecb2a6be1c98a991bc", "version_major": 2, "version_minor": 0 }, @@ -1561,7 +1560,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "dc722b3adcb44aa19049128fafb1293e", + "model_id": "7cba930fba06420bbfecc1357fd3a4ab", "version_major": 2, "version_minor": 0 }, @@ -1582,7 +1581,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "15b62992baab460a864cf48ff6b04a62", + "model_id": "abb74d6cfb6042919cacd1228aec58ad", "version_major": 2, "version_minor": 0 }, @@ -1603,7 +1602,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "652b98f46fa64dbb94756fa6cb72b7cc", + "model_id": "d70dbc8e95384c039ff8e3bb1191fe57", "version_major": 2, "version_minor": 0 }, @@ -1624,7 +1623,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7658a847edea48ed8aab550746e6c0fe", + "model_id": "ee4825239873471aac483700d05c1222", "version_major": 2, "version_minor": 0 }, @@ -1645,7 +1644,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3294a2f27aa44b86b514e249c132452a", + "model_id": "cc26928d75c3476e9b39eb5bac2d9472", "version_major": 2, "version_minor": 0 }, @@ -1666,7 +1665,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1650a56edea4439793a6ed110fb855fb", + "model_id": "7f40117d28f04444aa429f7a10dd5cd4", "version_major": 2, "version_minor": 0 }, @@ -1687,7 +1686,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "268d39ea2f944c56aca353a30d0cad45", + "model_id": "3c1960e73e1c456082bee5393a71801f", "version_major": 2, "version_minor": 0 }, @@ -1708,7 +1707,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "59627551ccdc44c9bef5aeefb1a363ad", + "model_id": "0235be83a65e4d39b38dd35401179c22", "version_major": 2, "version_minor": 0 }, @@ -1729,7 +1728,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "95c45dcefe6548fca2885aed13cd0031", + "model_id": "6dcc2b5f98fc4a769beac804b2afd144", "version_major": 2, "version_minor": 0 }, @@ -1750,7 +1749,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "438dabde17a143e8b836acb46c1d3918", + "model_id": "bb02da9759604c0dad39a437f604ca91", "version_major": 2, "version_minor": 0 }, @@ -1771,7 +1770,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e56bf056e1a541b2b3f71847696d87ee", + "model_id": "49b61d82fd1345409b2f47fd4507223a", "version_major": 2, "version_minor": 0 }, @@ -1792,7 +1791,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "12f8e167f3e3482cba465ed54e4e6887", + "model_id": "24ed62c8edf647f0821eb4004c234b4e", "version_major": 2, "version_minor": 0 }, @@ -1813,7 +1812,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "15c104b3c60a4702a511325c99879c28", + "model_id": "c2be9e98155543f3a6a4f8bec99bd2c9", "version_major": 2, "version_minor": 0 }, @@ -1834,7 +1833,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a5789d2825aa4a6a87baf47cb096f3fc", + "model_id": "a938d13dece2456d8aeb82cd524902ec", "version_major": 2, "version_minor": 0 }, @@ -1855,7 +1854,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "03063b4d44254a729a7405a9a8d84c70", + "model_id": "a0ca829d42a64a06a8476a6d93c8641e", "version_major": 2, "version_minor": 0 }, @@ -1876,7 +1875,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2dba6c81a7c4420ba1c73111d26dc5ee", + "model_id": "92894d34168947f7a03b08063857d16e", "version_major": 2, "version_minor": 0 }, @@ -1897,7 +1896,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7eafe5778fe142019719bc6a602b3b45", + "model_id": "ef8fff721aeb4c629f8b37f299d0813e", "version_major": 2, "version_minor": 0 }, @@ -1918,7 +1917,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "feeb303d262042f48740e09e9ee6e63c", + "model_id": "5633492231744858b422ace8e571d088", "version_major": 2, "version_minor": 0 }, @@ -1933,13 +1932,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "Atoms(symbols='Th2', pbc=True, cell=[18.166, 18.167, 18.168])\n" + "Atoms(symbols='Th2', pbc=True, cell=[18.166, 18.167, 18.168], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1714311ae6f541b8af396ba929619b56", + "model_id": "4d226c069546431d9c5639f918280b45", "version_major": 2, "version_minor": 0 }, @@ -1954,18 +1953,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Pa2', pbc=True, cell=[17.855999999999998, 17.857, 17.857999999999997])\n" + "Atoms(symbols='Pa2', pbc=True, cell=[17.855999999999998, 17.857, 17.857999999999997], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ab7d607c7217458eb53eaa7b7accf6b7", + "model_id": "de82b91e0fe947768e3cbad6beef09ff", "version_major": 2, "version_minor": 0 }, @@ -1980,152 +1974,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='U2', pbc=True, cell=[16.802, 16.803, 16.804])\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "../aten/src/ATen/native/cuda/Indexing.cu:1237: indexSelectSmallIndex: block: [0,0,0], thread: [64,0,0] Assertion `srcIndex < srcSelectDimSize` failed.\n", - "../aten/src/ATen/native/cuda/Indexing.cu:1237: indexSelectSmallIndex: block: [0,0,0], thread: [65,0,0] Assertion `srcIndex < srcSelectDimSize` failed.\n", - "../aten/src/ATen/native/cuda/Indexing.cu:1237: indexSelectSmallIndex: block: [0,0,0], thread: [66,0,0] Assertion `srcIndex < srcSelectDimSize` failed.\n", - "../aten/src/ATen/native/cuda/Indexing.cu:1237: indexSelectSmallIndex: block: [0,0,0], thread: [67,0,0] Assertion `srcIndex < srcSelectDimSize` failed.\n", - "../aten/src/ATen/native/cuda/Indexing.cu:1237: indexSelectSmallIndex: block: [0,0,0], thread: [68,0,0] Assertion `srcIndex < srcSelectDimSize` failed.\n", - "../aten/src/ATen/native/cuda/Indexing.cu:1237: indexSelectSmallIndex: block: [0,0,0], thread: [69,0,0] Assertion `srcIndex < srcSelectDimSize` failed.\n", - 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"../aten/src/ATen/native/cuda/Indexing.cu:1237: indexSelectSmallIndex: block: [0,0,0], thread: [29,0,0] Assertion `srcIndex < srcSelectDimSize` failed.\n", - "../aten/src/ATen/native/cuda/Indexing.cu:1237: indexSelectSmallIndex: block: [0,0,0], thread: [30,0,0] Assertion `srcIndex < srcSelectDimSize` failed.\n", - "../aten/src/ATen/native/cuda/Indexing.cu:1237: indexSelectSmallIndex: block: [0,0,0], thread: [31,0,0] Assertion `srcIndex < srcSelectDimSize` failed.\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "ca1f8486169847478d779ce93faa155c", + "Atoms(symbols='U2', pbc=True, cell=[16.802, 16.803, 16.804], calculator=SinglePointCalculator(...))\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ecf428438fa14adc95d1d8d6c87d3f86", "version_major": 2, "version_minor": 0 }, @@ -2140,18 +1995,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Np2', pbc=True, cell=[17.483999999999998, 17.485, 17.485999999999997])\n" + "Atoms(symbols='Np2', pbc=True, cell=[17.483999999999998, 17.485, 17.485999999999997], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "55494155d4cb4c8d9ba701f95a005999", + "model_id": "6141a244d68b47ee94d3f6725aabd00e", "version_major": 2, "version_minor": 0 }, @@ -2166,18 +2016,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Pu2', pbc=True, cell=[17.422, 17.423000000000002, 17.424])\n" + "Atoms(symbols='Pu2', pbc=True, cell=[17.422, 17.423000000000002, 17.424], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9e8141fdafc24ab4943e51129c13c0fd", + "model_id": "dd7486db81714c829be58ddf04afc6c5", "version_major": 2, "version_minor": 0 }, @@ -2192,18 +2037,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Am2', pbc=True, cell=[17.546, 17.547, 17.548])\n" + "Atoms(symbols='Am2', pbc=True, cell=[17.546, 17.547, 17.548], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f8021cbe5a42488798642d455ac5bf4d", + "model_id": "d436f7dbd6e14bc4a79344d94fe52b92", "version_major": 2, "version_minor": 0 }, @@ -2218,18 +2058,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Cm2', pbc=True, cell=[18.91, 18.911, 18.912])\n" + "Atoms(symbols='Cm2', pbc=True, cell=[18.91, 18.911, 18.912], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9c86275b258549d482b9718465820cb3", + "model_id": "83af10bc76cf4945b7b0489087b51bb4", "version_major": 2, "version_minor": 0 }, @@ -2244,18 +2079,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Bk2', pbc=True, cell=[21.08, 21.081, 21.081999999999997])\n" + "Atoms(symbols='Bk2', pbc=True, cell=[21.08, 21.081, 21.081999999999997], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b236798ee57d4100a904c7d163ca41a8", + "model_id": "4585f52e7d9c4fefa214d38d7bcd8b9f", "version_major": 2, "version_minor": 0 }, @@ -2270,18 +2100,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Cf2', pbc=True, cell=[18.91, 18.911, 18.912])\n" + "Atoms(symbols='Cf2', pbc=True, cell=[18.91, 18.911, 18.912], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "eb0068e5944c48729646c6577ed60e08", + "model_id": "a2a0f75c35504493898e5a25259e1cf1", "version_major": 2, "version_minor": 0 }, @@ -2296,18 +2121,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Es2', pbc=True, cell=[16.740000000000002, 16.741000000000003, 16.742])\n" + "Atoms(symbols='Es2', pbc=True, cell=[16.740000000000002, 16.741000000000003, 16.742], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "07fd96a912874a83a8bae27cc0a569f0", + "model_id": "f6264b273b3d4b7da3d9127481cc147f", "version_major": 2, "version_minor": 0 }, @@ -2322,18 +2142,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Fm2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Fm2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "34f8d1058783470aa891409656ed75d2", + "model_id": "2fff45788c714d22894016ec421bc9c1", "version_major": 2, "version_minor": 0 }, @@ -2348,18 +2163,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Md2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Md2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9f8f687c8bab45869b749aa3e668c890", + "model_id": "a0d11546c972482fbaf72c0d1bdd5909", "version_major": 2, "version_minor": 0 }, @@ -2374,18 +2184,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='No2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='No2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "bd017f1152934ce79927791ec7374f4b", + "model_id": "523a52d6a2754c779d1c34c9ec989ee8", "version_major": 2, "version_minor": 0 }, @@ -2400,18 +2205,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Lr2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Lr2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "96349229e8964cb1a9f8696060668b62", + "model_id": "4005b9314214460bb1b8d8fdf333e97c", "version_major": 2, "version_minor": 0 }, @@ -2426,18 +2226,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Rf2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Rf2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9b67bbbd67bd4b87834f93f665ff09a4", + "model_id": "984ae8c9227c4f4997e2b48f66442741", "version_major": 2, "version_minor": 0 }, @@ -2452,18 +2247,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Db2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Db2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "39b4c6459b854896b884307ea152c9e9", + "model_id": "e631f9c040734f4899b6a16c76bd6075", "version_major": 2, "version_minor": 0 }, @@ -2478,18 +2268,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Sg2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Sg2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "10cf6e57435a4d85a7a49c3e2c28a9ae", + "model_id": "37ea9f9896024a388372df4ee9b9dba4", "version_major": 2, "version_minor": 0 }, @@ -2504,18 +2289,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Bh2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Bh2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "76ca1aa2e3404667987c12e22682db0b", + "model_id": "d09b73fd71814937941284b6779a5642", "version_major": 2, "version_minor": 0 }, @@ -2530,18 +2310,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Hs2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Hs2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fb00cd19567e436b8db802bcabf71398", + "model_id": "02209c3512954bb89ec77c445bcd1d97", "version_major": 2, "version_minor": 0 }, @@ -2556,18 +2331,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Mt2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Mt2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0dbce3e07cb148ad94681b70caa30ffc", + "model_id": "403cd6bb5bb74e129282c009a3ba79f5", "version_major": 2, "version_minor": 0 }, @@ -2582,18 +2352,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Ds2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Ds2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "89e11f0bdbf34d15aa117ea96a31cb93", + "model_id": "fed1c883a54a4c6099604b0e433f9d03", "version_major": 2, "version_minor": 0 }, @@ -2608,18 +2373,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Rg2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Rg2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7e45470145cc420a9e2ec8c742ae531d", + "model_id": "bf6641d9621447c384c11e1ee72e3229", "version_major": 2, "version_minor": 0 }, @@ -2634,18 +2394,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Cn2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Cn2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ee9036f26458472786c7e0ac9d08e746", + "model_id": "f605d4c0b41b4804b6ce05bd11fbe5b2", "version_major": 2, "version_minor": 0 }, @@ -2660,18 +2415,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Nh2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Nh2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7a708943975a40678d2202c43c3ef691", + "model_id": "ef68b0a7eba34028af3a4baf7e993764", "version_major": 2, "version_minor": 0 }, @@ -2686,18 +2436,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Fl2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Fl2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "afb2a3a6e58b4b6595b90170e74eabe2", + "model_id": "c1bd7668bc214f5c8ac2bd2ca93c7ef0", "version_major": 2, "version_minor": 0 }, @@ -2712,18 +2457,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Mc2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Mc2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "056fc56c2899412cbe291513d1f82dbe", + "model_id": "fa49282444cc46a6ac5c3cb9a58bd0a7", "version_major": 2, "version_minor": 0 }, @@ -2738,18 +2478,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Lv2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Lv2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "967172d7e9d1410d9a4efc015f039dbe", + "model_id": "827aa304e18444aa9afd464617e2eb3f", "version_major": 2, "version_minor": 0 }, @@ -2764,18 +2499,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", - "Atoms(symbols='Ts2', pbc=True, cell=[12.0, 12.001, 12.002])\n" + "Atoms(symbols='Ts2', pbc=True, cell=[12.0, 12.001, 12.002], calculator=SinglePointCalculator(...))\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8035c83802ee4e19a4ce004470b50ea4", + "model_id": "b8fcbecd77da495587a22cf4683d8af6", "version_major": 2, "version_minor": 0 }, @@ -2790,18 +2520,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n", "Atoms(symbols='Og2', pbc=True, cell=[12.0, 12.001, 12.002])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "195236ad3f85477598ed2c118f2939d1", + "model_id": "1ecca992966c450ba52ab1484fce4f45", "version_major": 2, "version_minor": 0 }, @@ -2816,11 +2541,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "CUDA error: device-side assert triggered\n", - "CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.\n", - "For debugging consider passing CUDA_LAUNCH_BLOCKING=1.\n", - "Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.\n", - "\n" + "Class values must be smaller than num_classes.\n" ] } ], @@ -2889,8 +2610,6 @@ "\n", " print(atoms)\n", "\n", - " calc = calc\n", - "\n", " atoms.calc = calc\n", "\n", " for i, r in enumerate(tqdm(rs)):\n", @@ -2916,7 +2635,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 16, "id": "a0ac2c09-370b-4fdd-bf74-ea5c4ade0215", "metadata": { "tags": [] @@ -2925,7 +2644,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d47aae6dd71642049e2784e703609b0a", + "model_id": "6adfb4c128c0413b8f70054e3241979d", "version_major": 2, "version_minor": 0 }, @@ -3010,12 +2729,292 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "e0dd4367-3dca-440f-a7a9-7fdd84183f2c", "metadata": { "tags": [] }, - 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namemethodREFS^2spearman-repulsionspearman-attractionspearman-descending-forcespearman-ascending-forcespearman-repulsion-energyspearman-attraction-energy
0HHORB[0.1549999999999998, 0.16504226000000033, 0.17...[-2.6258459091186523, -2.755453109741211, -1.8...[0.26894104, -0.0038066, 2.37577677, 7.8109564...[]NaNNaN-0.9080970.579246-0.8585280.504446
1HeHeORB[0.13999999999999968, 0.15003038000000046, 0.1...[-0.37155914306640625, -0.4051551818847656, 0....[0.02356668, -2.673e-05, 0.45423254, 1.2784304...[]NaNNaN-0.911505-0.046725-0.8666690.340055
2LiLiORB[0.6400000000000006, 0.6500202799999997, 0.660...[8.477561950683594, 8.438533782958984, 8.38090...[86.12041473, 84.16366577, 82.23960876, 80.216...[]NaNNaN-0.9959870.999664-0.9998580.948886
3BeBeORB[0.4800000000000004, 0.49003191999999984, 0.50...[7.427803039550781, 7.338706970214844, 7.19796...[116.66287994, 120.23416138, 123.43974304, 126...[]NaNNaN-0.9983460.972891-0.9588270.691532
4BBORB[0.41999999999999993, 0.4300200399999996, 0.44...[1.7283554077148438, 1.9046106338500977, 2.040...[118.15281677, 121.52095032, 124.86712646, 127...[]NaNNaN-0.9706580.922968-0.8087020.816218
.......................................
112NhNhORB[0.09999999999999964, 0.11001697999999926, 0.1...[-2.2965879440307617, -2.30364990234375, -2.30...[-0.01143722, -0.01140489, -0.01082459, 0.1164...[]NaNNaN-0.5880280.989775-0.2157460.963378
113FlFlORB[0.09999999999999964, 0.11001697999999926, 0.1...[-3.702641487121582, -3.683434009552002, -3.65...[-2.14600778, -2.05312586, -1.91521156, 0.2045...[]NaNNaNNaN-0.539312-0.4575060.870783
114McMcORB[0.09999999999999964, 0.11001697999999926, 0.1...[-1.6017036437988281, -1.5843744277954102, -1....[-0.02472172, 0.00170199, 0.0667266, 0.4929885...[]NaNNaN-0.7396830.998949-0.4346330.999944
115LvLvORB[0.09999999999999964, 0.11001697999999926, 0.1...[-8.688143730163574, -8.684117317199707, -8.66...[-2.57541442, -2.43290496, -2.19691253, 1.7867...[]NaNNaNNaN-0.762006-0.8641030.903459
116TsTsORB[0.09999999999999964, 0.11001697999999926, 0.1...[-0.1275949478149414, -0.09642791748046875, -0...[-1.2110672, -1.19077206, -1.1051929, 0.515652...[]NaNNaNNaN-0.868446-0.6205340.919588
\n", + "

117 rows × 12 columns

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[] NaN \n", + "1 [0.02356668, -2.673e-05, 0.45423254, 1.2784304... [] NaN \n", + "2 [86.12041473, 84.16366577, 82.23960876, 80.216... [] NaN \n", + "3 [116.66287994, 120.23416138, 123.43974304, 126... [] NaN \n", + "4 [118.15281677, 121.52095032, 124.86712646, 127... [] NaN \n", + ".. ... .. ... \n", + "112 [-0.01143722, -0.01140489, -0.01082459, 0.1164... [] NaN \n", + "113 [-2.14600778, -2.05312586, -1.91521156, 0.2045... [] NaN \n", + "114 [-0.02472172, 0.00170199, 0.0667266, 0.4929885... [] NaN \n", + "115 [-2.57541442, -2.43290496, -2.19691253, 1.7867... [] NaN \n", + "116 [-1.2110672, -1.19077206, -1.1051929, 0.515652... 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