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" @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "3200850a-b8fb-4f50-9815-16ae8da0f942", "metadata": { "tags": [] @@ -30,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 7, "id": "90887faa-1601-4c4c-9c44-d16731471d7f", "metadata": { "scrolled": true, @@ -41,15 +41,23 @@ "name": "stdout", "output_type": "stream", "text": [ - "========== MACE-OFF(M) ==========\n", - "Selected GPU cuda:0 with 40338.06 MB free memory from 4 GPUs\n", - "Default dtype float32 does not match model dtype float64, converting models to float32.\n" + "========== eSCN(OC20) ==========\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:root:Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.\n", + "WARNING:root:Couldn't modify the submission pickle with error: [Errno 2] No such file or directory: '/checkpoint/zitnick/ocp_logs/4486283/30683411_submitted.pkl'\n", + "/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/fairchem/core/modules/normalization/normalizer.py:69: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n", + " \"mean\": torch.tensor(state_dict[\"mean\"]),\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "60f14aee9df9484997239ace3de2e101", + "model_id": "24eab286853845a9adc00bf1b005fe96", "version_major": 2, "version_minor": 0 }, @@ -70,7 +78,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "01f85ac837a44f64950df4fbe5f108f1", + "model_id": "9ccd4691d8444d92aee01824ac31c279", "version_major": 2, "version_minor": 0 }, @@ -91,7 +99,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ab613d7a045e45bd939214bfc6ff0b3f", + "model_id": "021844151e0748cab81beb127dce87d9", "version_major": 2, "version_minor": 0 }, @@ -106,14 +114,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "2 is not in list\n", "Atoms(symbols='Li2', pbc=True, cell=[13.144000000000002, 13.145000000000001, 13.146000000000003])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a44cf4d8d9af41ea98901956c5b2e800", + "model_id": "0351d3f8e0234361ae62ab84d59a625a", "version_major": 2, "version_minor": 0 }, @@ -128,14 +135,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "3 is not in list\n", "Atoms(symbols='Be2', pbc=True, cell=[12.276, 12.277, 12.278])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e3a16426d1cb4f9785fcfc1fd83dd8cd", + "model_id": "1af3ab5e3cfa470597b1b0b00f4ea89e", "version_major": 2, "version_minor": 0 }, @@ -150,14 +156,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "4 is not in list\n", "Atoms(symbols='B2', pbc=True, cell=[11.842, 11.843, 11.844000000000001])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0b96202a2c594947b6093ecab0d89a25", + "model_id": "cd070b6565634a87bac75970ac988db9", "version_major": 2, "version_minor": 0 }, @@ -172,14 +177,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "5 is not in list\n", "Atoms(symbols='C2', pbc=True, cell=[10.974, 10.975, 10.976])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "55e1867137bb450f8c31b378ddcf5f2b", + "model_id": "ad1a090228244cd89a40f0dcae83baac", "version_major": 2, "version_minor": 0 }, @@ -200,7 +204,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0c71c7705dbc428d81308cdc16942921", + "model_id": "2d15b033ce7e463ca30c1edf770e554d", "version_major": 2, "version_minor": 0 }, @@ -221,7 +225,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "52a86764001b45cab2fef7af36f4d16a", + "model_id": "a47ba796ac0d43f49bb9a6a372533408", "version_major": 2, "version_minor": 0 }, @@ -242,7 +246,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "34a2485e76cd4acc8c5d4caa724037ae", + "model_id": "641dfc50acee41d89321000de0472249", "version_major": 2, "version_minor": 0 }, @@ -263,7 +267,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "da6bf461ce4849ef8b723a140aee5e46", + "model_id": "0fb90f08d0114d66b42e277570075867", "version_major": 2, "version_minor": 0 }, @@ -278,14 +282,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "10 is not in list\n", "Atoms(symbols='Na2', pbc=True, cell=[15.5, 15.501, 15.502])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "07b8b95e8418423193b3eb48a1c3197a", + "model_id": "0e301092e4a441f9b1bd88b0612d4fa7", "version_major": 2, "version_minor": 0 }, @@ -300,14 +303,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "11 is not in list\n", "Atoms(symbols='Mg2', pbc=True, cell=[15.562, 15.562999999999999, 15.564])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1032c8118d4e4da6b9ea753d152490b2", + "model_id": "3da0910f4f7648c4a2698da360d606c7", "version_major": 2, "version_minor": 0 }, @@ -322,14 +324,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "12 is not in list\n", "Atoms(symbols='Al2', pbc=True, cell=[13.950000000000001, 13.951, 13.952000000000002])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a907fe3e32644eaa884b9c11b80e503e", + "model_id": "4fb4bcc42863455698e74a6543d13797", "version_major": 2, "version_minor": 0 }, @@ -344,14 +345,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "13 is not in list\n", "Atoms(symbols='Si2', pbc=True, cell=[13.578, 13.578999999999999, 13.58])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fd88635852dc4d2ca1c3cd298a760a2e", + "model_id": "7973fdc719574ca2ab1097efacc35bfb", "version_major": 2, "version_minor": 0 }, @@ -366,14 +366,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "14 is not in list\n", "Atoms(symbols='P2', pbc=True, cell=[11.78, 11.780999999999999, 11.782])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "12bf703b946a4f038142fb8531dbdd44", + "model_id": "dccf29b383d64c0cb120c8f72763bd98", "version_major": 2, "version_minor": 0 }, @@ -394,7 +393,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "84232451800944dd931a9cc1a3f7c76a", + "model_id": "ea09c6aac7d84c339dbaddda3853b9e2", "version_major": 2, "version_minor": 0 }, @@ -415,7 +414,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "49a6bc3910244f04b9a74e8d2e8c4142", + "model_id": "5026400e316b4f9db2f641893c267440", "version_major": 2, "version_minor": 0 }, @@ -436,7 +435,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ebb843c27f634344bd10a526081ca13c", + "model_id": "017a69b355da4410ae25801d630ac39b", "version_major": 2, "version_minor": 0 }, @@ -451,14 +450,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "18 is not in list\n", "Atoms(symbols='K2', pbc=True, cell=[16.926000000000002, 16.927000000000003, 16.928])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c3cee6fcc4894e5085ce78549feb9177", + "model_id": "0d1e6e0bb1274281a3c4923583d5ef26", "version_major": 2, "version_minor": 0 }, @@ -473,14 +471,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "19 is not in list\n", "Atoms(symbols='Ca2', pbc=True, cell=[16.244, 16.245, 16.246])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "df8ca2be9bfd496ca5cabda54ab5c6fc", + "model_id": "83db27472a2b4b7c90b0ec38981cf8a0", "version_major": 2, "version_minor": 0 }, @@ -495,14 +492,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "20 is not in list\n", "Atoms(symbols='Sc2', pbc=True, cell=[15.996, 15.997, 15.998000000000001])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4861cf3841bf4bce95c6f28db390c90c", + "model_id": "282ef294f8a442068d4a29e7b7c28333", "version_major": 2, "version_minor": 0 }, @@ -517,14 +513,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "21 is not in list\n", "Atoms(symbols='Ti2', pbc=True, cell=[15.252, 15.253, 15.254000000000001])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b8de0654f19c406da7709f59f4d5ab46", + "model_id": "3afef0afbfaa49438e4aa91c171db434", "version_major": 2, "version_minor": 0 }, @@ -539,14 +534,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "22 is not in list\n", "Atoms(symbols='V2', pbc=True, cell=[15.004, 15.004999999999999, 15.006])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "436311045ab541f3b42f9e3082c888c4", + "model_id": "aaecbf8fa3a04c8098655912e69a6b8d", "version_major": 2, "version_minor": 0 }, @@ -561,14 +555,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "23 is not in list\n", "Atoms(symbols='Cr2', pbc=True, cell=[15.190000000000001, 15.191, 15.192000000000002])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "790a63d1478f4313b967ca5ac646b60e", + "model_id": "e70fa07b40274cd78d97888cf325187e", "version_major": 2, "version_minor": 0 }, @@ -583,14 +576,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "24 is not in list\n", "Atoms(symbols='Mn2', pbc=True, cell=[15.190000000000001, 15.191, 15.192000000000002])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "842404aaf77046fb95be4886c3c6b204", + "model_id": "c31f32587a7b4785a5ae8fc57a67a6a8", "version_major": 2, "version_minor": 0 }, @@ -605,14 +597,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "25 is not in list\n", "Atoms(symbols='Fe2', pbc=True, cell=[15.128, 15.129, 15.13])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "421357cb56af4b589fdeafc354559700", + "model_id": "56bd67b330db46d1b2c2a061a91382f4", "version_major": 2, "version_minor": 0 }, @@ -627,14 +618,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "26 is not in list\n", "Atoms(symbols='Co2', pbc=True, cell=[14.879999999999999, 14.880999999999998, 14.882])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c0a0dc53185143dc99d99695bc93ffbc", + "model_id": "255f15d5e8e54211b9df002198d5edd2", "version_major": 2, "version_minor": 0 }, @@ -649,14 +639,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "27 is not in list\n", "Atoms(symbols='Ni2', pbc=True, cell=[14.879999999999999, 14.880999999999998, 14.882])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "686f870641b645e19ab34b492285d65b", + "model_id": "7506a894ef4e4837b1be7361c35171d9", "version_major": 2, "version_minor": 0 }, @@ -671,14 +660,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "28 is not in list\n", "Atoms(symbols='Cu2', pbc=True, cell=[14.756, 14.757, 14.758000000000001])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "af3aa8ccc84a4e9c90cf7be3058f8974", + "model_id": "9dd100e193014415a7246477fb6510fd", "version_major": 2, "version_minor": 0 }, @@ -693,14 +681,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "29 is not in list\n", "Atoms(symbols='Zn2', pbc=True, cell=[14.818000000000001, 14.819, 14.820000000000002])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1663ce2f57b94ba58726f1807ace289f", + "model_id": "62fb70fb1d1d40d080778d91f4e72586", "version_major": 2, "version_minor": 0 }, @@ -715,14 +702,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "30 is not in list\n", "Atoms(symbols='Ga2', pbc=True, cell=[14.383999999999999, 14.384999999999998, 14.386])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b4101abb835e446ba361c5f4b8347f75", + "model_id": "904220ce9932428fa052402e69ffdcad", "version_major": 2, "version_minor": 0 }, @@ -737,14 +723,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "31 is not in list\n", "Atoms(symbols='Ge2', pbc=True, cell=[14.198, 14.199, 14.200000000000001])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3f974765427c4cb5ac7eea72a57cfa58", + "model_id": "ff0fe051c4044ace8fbeb5d2e94db0c6", "version_major": 2, "version_minor": 0 }, @@ -759,14 +744,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "32 is not in list\n", "Atoms(symbols='As2', pbc=True, cell=[11.655999999999999, 11.656999999999998, 11.658])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a8e033dbae494467a5028eab97e28bbe", + "model_id": "bda6526e6fa04bad9b69112c7b73ada7", "version_major": 2, "version_minor": 0 }, @@ -781,14 +765,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "33 is not in list\n", "Atoms(symbols='Se2', pbc=True, cell=[11.284, 11.285, 11.286000000000001])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c430c0fe2a6a4f45a6b15cf6a6266c70", + "model_id": "8e77fbc41d244195b742bffa2670e945", "version_major": 2, "version_minor": 0 }, @@ -803,14 +786,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "34 is not in list\n", "Atoms(symbols='Br2', pbc=True, cell=[11.532000000000002, 11.533000000000001, 11.534000000000002])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "adc60afc577747f4ab184e8bc4ec889e", + "model_id": "8789d10a86d843b79ba4523da889f04b", "version_major": 2, "version_minor": 0 }, @@ -831,7 +813,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a7c29ad28c4148e8899542b0dbf542a4", + "model_id": "a0de3c3adc534efd94770361755963a6", "version_major": 2, "version_minor": 0 }, @@ -846,14 +828,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "36 is not in list\n", "Atoms(symbols='Rb2', pbc=True, cell=[19.902, 19.903000000000002, 19.904])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "54d89e170cca451c8c3f04f7c921c1c4", + "model_id": "fd8192ac694d4b3a99ca48302393790e", "version_major": 2, "version_minor": 0 }, @@ -868,14 +849,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "37 is not in list\n", "Atoms(symbols='Sr2', pbc=True, cell=[17.608, 17.609, 17.61])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3108baf3f8ae40069fb5c5d282eb45f0", + "model_id": "3e9cbac78b434f2196bb066f61bba487", "version_major": 2, "version_minor": 0 }, @@ -890,14 +870,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "38 is not in list\n", "Atoms(symbols='Y2', pbc=True, cell=[17.05, 17.051000000000002, 17.052])\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f83629d595504b658a703122591784a1", + "model_id": "17e1466cb09e422fb146edd954eb4db9", "version_major": 2, "version_minor": 0 }, @@ -912,36 +891,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "39 is not in list\n", - "Atoms(symbols='Zr2', pbc=True, cell=[15.624, 15.625, 15.626000000000001])\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "31f0e507a3414cde8f21821b16eae5ca", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/623 [00:00