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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<meta name="generator" content="pandoc" />
<meta http-equiv="X-UA-Compatible" content="IE=EDGE" />
<meta name="author" content="Alexandra Strassmann, Samuel Pawel" />
<title>Session 5: Self-Supervised Learning</title>
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yr6EIj+LzNj/mfR2vhhRlx0BILZoAYruF0caWQ7YxO66UmeguDREAFHYuC7HJviRgVO6ruJH59h/C/PkgSle8xNzZJULLWq9JMDTE2fjGE146a1Us6PZDGYle6ldWRqn/pdpgHKNGrGIdkRK+KPETT9nKT6kLyDI8xd9A1FgWmXWRAIHwZ37WyZHOVyCadJEmMVz0MadMjDrPho+EIochkVC2xgGiwwsQ6DMv2P7UXqT4x7CdcYGId2BJQQa85EQKmCmwcRejQ9Bm4oATENFPkxPXILHpMPUyWTI5rjNOsIlmEeMbcOCEqInpXACYQ9DDxmFo9vcmsDblcMtg4tqBerNngkIKaFJmrQAPnq1dEzsMXcwjcHdfdCibcAxxA+q/j9m3LM/O7WJka4tSidVCjsvo2lQ/2ewyoYyXwAYyr2PlRoR5MpgVmSUIrM3PQxXPbgjBOaDQFIyFMJvx3Pc5RSYj12ySVF9fwFPQu2e2KWVoL9q3Ayv3IzpGHUdvdPdrNUdicjsTQ2ISy7QU3DrEytIjvbzJnAkmANXjAFERA0MUoPF3/5KFmW14bBNOhwircYgMqoDpUMcDtCmBE82QM2YtdjVLB4kBuKho/bcwQdeboqfQartuU3CsCf+cXkgYAqp/0Ee3RorAZt0AvvOCSI4JICIlGlsV0bsSid/NIEALAAzb6HAgyWHBps6xAOwkJIGcB82CxRQq4sJf3FzA70A+TRqcqjEMETCoez3mkPcpnoALs0ugJY8kQwrC+JE5ik3w9rzrvDRjAQnqgEVvdGrNwlanR0SOKWzxOJOvLJhcd8Cl4AshACUkv9czdMkJCVQSQhp6kp7StAlpVRpK0t0SW6LHeBJnE2QchB5Ccu8kxRghZXGIgZIiSj7gEKMJDClcnX6hgoqJMwiQDigIXg3ioFLCgDgjPtYHYpsF5EiA4kcnN18MZtOrY866dEQAb0FB34OGKHGZQjwW/WDHA60cYFaI/PjpzquUqdaYGcIq+mLez3WLFFCtNBN2QJcrlcoELgiPku5R5dSlJFaCEqEZle1AQzAKC+1SotMcBNyQUFuRHRF6OlimSBgjZeTBCwLyc6A+P/oFRchXTz5ADknYJHxzrJ5pGuIKRQISU6WyKTBBjD8WozmVYWIsto1AS5rxzKlvJu4E/vwOiKxRtCWsDM+eTHUrmwrCK5BIfMzGkD+0Fk5LzBs0jMYXktNDblB06LMNJ09U8pzSLmo14MS0OMjcdrZ31pyQqxJJpRImlSvfYAK8inkYU52QY2FPEVsjoWewpwhRp5yAuNpkqhdb7ku9Seefl2D0B8SMTFD90xi4CSOwwZy9IKkpMtI3FmFUg3/kFutpQGNc3pCR7gvC4sgwbupDu3DyEN+W6YGLNM21jpB49irxy9BSlHrVDlnihGKHwPrbVFtc+h1rVQKZduxIyojccZIIcOCmhEnC7UkY68WXKQgLi2JCDQkQWJRQuk60hZp0D3rtCTINSeY9Ej2kIKYfGxwOs4j9qMM7fYZiipzgcf7TamnehqdhsiMiCawXnz4xAbyCkLAx5EGbo3Ax1u3dUIKnTxIaxwQTHehPl3V491H0+bC5zgpGz7Io+mjdhKlPJ01EeMpM7UsRJMi1nGjmJg35i6bQBAAxjO/ENJubU2mg3ONySEoWklCwdABETcs7ck3jgiuU9pcKKpbgn+3YlzV1FzIkB6pmEDOSSyDfPPlQskznctFji0kpgZjW5RZe6x9kYT4KJcXg0bNiCyif+pZACCyRMmYsfiKmN9tSO65F0R2OO6ytlEhY5Sj6uRKfFxw0ijJaAx/k3QgnAFSq27/2i4GEBA+UvTJKK/9eISNvG46Em5RZfjTYLdeD8kdXHyrwId/DQZUaMCY4gGbke2C8vfjgV/Y9kkRQOJIn/xM9INZSpiBnqX0Q9GlQPpPKAyO5y+W5NMPSRdBCUlmuxl40ZfMCnf2Cp044uI9WLFtCi4YVxKjuRCOBWIb4XbIsGdbo4qtMQnNOQz4XDSui7W/N6l54qOynCqD3DpWQ+mpD7C40D8BZEWGJX3tlAaZBMj1yjvDYKwCJBa201u6nBKE5UE+7QSEhCwrXfbRZylAaAkplhBWX50dumrElePyNMRYUrC99UmcSSNgImhFhDI4BXjMtiqkgizUGCrZ8iwFxU6fQ8GEHCFdLewwxYWxgScAYMdMLmcZR6b7rZl95eQVDGVoUKcRMM1ixXQtXNkBETZkVVPg8LoSrdetHzkuM7DjZRHP02tCxA1fmkXKF3VzfN1pc1cv/8lbTIkkYpqKM9VOhp65ktYk+Q46myFWBapDfyWUCnsnI00QTBQmuFjMZTcd0V2NQ768Fhpby04k2IzNR1wKabuGJqYWwSly6ocMFGTeeI+ejsWDYgEvr66QgqdcIbFYDNgsm0x9UHY6SCd5+7tpsLpKdvhahIDyYmEJQCqMqtCF6UlrE5GXRmbu+vtm3BFSxI6ND6UxIE7GsGMgWqghXxSnaRJuGFveTcK5ZVSPJyjUxe1dKgI6kNF7EZhIZs8y8FVqwEfbM0Xk2ltORVDKZZM40SD3qQoQe0orJEKwPfZwm3YPqwixhUMOndis6MhbmfvLBKjC8sKKIZKbJk8L11oNkCQzCgvjhyyEiQSuJcgCQSG4Mocfgc0Hkwcjal1UNgP0CBPikYqBIk9tONv4kLtBswH07vUCjEaHiFGlLf8MgXKzSgjp2HolRRccAOh0ILHz9qlGgIFkwAnzHJRjWFhlA7ROwINyB5HFj59PRZHFor6voq7l23EPNRwdWhgawqbivLSjRA4htEYUFkjESu67icTg5S0aW1sOkCiIysfJ9UnIWevOOLGpepcBxy1wEhd2WI3AZg7sr9WBmHWyasxMcvY/iOmsLtHSWNUWEGk9hScMPShasUA1AcHOtRZlqMeQ0OzYS9vQvYUjOLrzP07BUAFikcJNMi7gIxEw4pL1G54TcmmmoAQ5s7TGWErJZ2Io4yQ0ljRYhL8H5e62oDtLF8aDpnIvZ5R3GWJyAugdiiJW9hQAVTsnCBHhwu7rkBlBX6r3b7ejEY0k5GGeyKv66v+6dg7mcJTrWHbtMywbedYqCQ0FPwoytmSWsL8WTtChZCKKzEF7vP6De4x2BJkkniMgSdWhbeBSLtJZR9CTHetK1xb34AYIJ37OegYIoPVbXgJ/qDQK+bfCtxQRVKQu77WzOoM6SGL7MaZwCGJVk46aImai9fmam+WpHG+0BtQPWUgZ7RIAlPq6lkECUhZQ2gqWkMYKcYMYaIc4gYCDFHYa2d1nzp3+J1eCBay8IYZ0wQRKGAqvCuZ/UgbQPyllosq+XtfKIZOzmeJqRazpmmoP/76YfkjzV2NlXTDSBYB04SVlNQsFTbGPk1t/I4Jktu0XSgifO2ozFOiwd/0SssJDn0dn4xqk4GDTTKX73/wQyBLdqgJ+Wx6AQaba3BA9CKEzjtQYIfAsiYamapq80LAamYjinlKXUkxdpIDk0puXUEYzSalfRibAeDAKpNiqQ0FTwoxuGYzRnisyTotdVTclis1LHRQCy/qqL8oUaQzWRxilq5Mi0IJGtMY02cGLD69vGjkj3p6pGePKI8bkBv5evq8SjjyU04vJR2cQXQwSJyoinDsUJHCQ50jrFTT7yRdbdYQMB3MYCb6uBzJ9ewhXYPAIZSXfeEQBZZ3GPN3Nbhh/wkvAJLXnQMdi5NYYZ5GHE400GS5rXkOZSQsdZgIbzRnF9ueLnsfQ47wHAsirITnTlkCcuWWIUhJSbpM3wWhXNHvt2xUsKKMpdBSbJnBMcihkoDqAd1Zml/R4yrzow1Q2A5G+kzo/RhRxQS2lCSDRV8LlYLBOOoo1bF4jwJAwKMK1tWLHlu9i0j4Ig8qVm6wE1DxXwAwQwsaBWUg2pOOol2dHxyt6npwJEdLDDVYyRc2D0HbcbLUJQj8gPevQBUBOUHXPrsAPBERICpnYESeu2OHotpXQxRGlCCtLdIsu23MhZVEoJg8Qumj/UMMc34IBqTKLDTp76WzL/dMjCxK7MjhiGjeYAC/kj/jY/Rde7hpSM1xChrog6yZ7OWTuD56xBJnGFE+pT2ElSyCnJcwVzCjkqeNLfMEJqKW0G7OFIp0G+9mh50I9o8k1tpCY0xYqFNIALgIfc2me4n1bmJnRZ89oepgLPT0NTMLNZsvSCZAc3TXaNB07vail36/dBySis4m9/DR8izaLJW6bWCkVgm5T+ius3ZXq4xI+GnbveLbdRwF2mNtsrE0JjYc1AXknCOrLSu7Te/r4dPYMCl5qtiHNTn+TPbh1jCBHH+dMJNhwNgs3nT+OhQoQ0vYif56BMG6WowAcHR3DjQolxLzyVekHj00PBAaW7IIAF1EF+uRIWyXjQMAs2chdpaKPNaB+kSezYt0+CA04sOg5vx8Fr7Ofa9sUv87h7SLAUFSzbetCCZ9pmyLt6l6/TzoA1/ZBG9bIUVHLAbi/kdBFgYGyGwRQGBpkqCEg2ah9UD6EedEcEL3j4y0BQQCiExEnocA3SZboh+epgd3YsOkHskZwPuQ5OoyA0fTA5AXrHcUOQF+zkJHIA7PwCDk1gGVmGUZSSoPhNf+Tklauz98QofOlCIQ/tCD4dosHYPqtPCXB3agggQQIqQJsSkB+qn0rkQ1toJjON/OtCIB9RYv3PqRA4C4U68ZMlZn6BdgEvi2ziU+TQ6NIw3ej+AtDwMGEZk7e2IjxUWKdAxyaw9OCwSmeADTPPleyk6UhGDNXQb++W6Uk4q6F7/rg6WVTo82IoCxSIsFDrav4EPHphD3u4hR53WKVvYZUwNCCeM4PMBWzK+EfIthZOkuAwPo5C5jgoZgn6dUdvx5rIDmd58cXXdKNfw3l+wM2UjgrDJeQHhbD7HW2QDoZMCujgIUkk5Fg8VCsdyjOtnGRx8wgKRPZN5dR0zPUyfGZFVihbFRniXZFOZGKPnEQzU3AnD1KfR6weHW2XS6KbPJxUkOTZsAB9vTVp3Le1F8q5l+DMcLiIq78jxAImD2pGFw0VHfRatScGlK6SMu8leTmhUSMy8Uhdd6xBiH3Gdman4tjQGLboJfqz6fL2WKHTmrfsKZRYX6BTDjDldKMosaSTLdQS7oDisJNqAUhw1PfTlnacCO8vl8706Km1FROgLDmudzxg+EWTiArtHgLsRrAXYWdB0NmToNCJdKm0KWycZQqb+Mw76Qy29iQ5up/X7oyw8QZ75kP5F6iJAJz6KCmqxz8fEa/xnsMYcIO/vEkGRuMckhr4rIeLrKaXnmIzlNLxbFspOphkcnJdnz/Chp/Vlpj2P7jJQmQRwGnltkTV5dbF9fE3/fxoSqTROgq9wFUlbuYzYcasE0ouzBo+dDCDzxKAfhbAZYxQiHrLzV2iVexnDX/QnT1fsT/xuhu1ui5qIytgbGmRoQkeQooO8eJNNZsf0iALur8QxZFH0nCMnjerYQqG1pIfjyVZWxhVRznmmfLG00BcBWJE6hzQWRyFknuJnXuk8A5FRDCulwrWASSNoBtR+CtGdkPwYN2o7DOw/VGlCZPusRBFXODQdUM5zeHDIVuAJBLqbO/f9Qua+pDqEPk230Sob9lEZ8BHiCorjVghuI0lI4JDgHGRDD/prQ84B1pVGkIpVUAHCG+iz3Bn3qm2AVrYcYWhock4jso5+J7HfHVj4WMIQdGctq3psBCVVzupQOEioBGA2Bk+UILT7+VoX5mdxxA5fS42gISQVi/HTzrgMxu0fY6hE1ocUwwbsbWcezrY2n6S8/6cxXkOH4prpmPuFoikTzY7T85C4T2XYlbxLglSv2uLCgFv8Quk/wdesUdWPeHYIH0R729JIisN9Apdd4eB10aqwXrPt+Su9mA8k8n1sjMwnfsfF2j3jMUzXepSHmZ/BfqXvzgUNQQWOXO8YEuFBh4QTYCkOAPxywpYu1VxiDyJmKVcmJPGWk/gc3Pov02StyYDahwmzw3E1gYC9wkupyWfDqDSUMpCTH5e5N8B//lHiMuIkTNw4USHrJU67bjXGqNav6PBuQSoqTxc8avHoGmvqNtXzIaoyMIQIiiUHIM64cXieouplhNYln7qgc4wBVAYR104kO+CvKqsg4yIUlFNThVUAKZxZt1XA34h3TCUUiXVkZ0w8Hh2R0Z5L0b4LZvPd/p1gi/07h8qfwHrByuSxglc9cI4QIg2oqvC/qm0i7tjPLTgDhoWTAKDO2ONW5oe+/eKB9vZB8K6C25yCZ9RFVMnb6NRdRjyVK57CHHSkJBfnM2/j4ODUwRkqrtBBCrDsDpt8jhZdXoy/1BCqw3sSGhgGGy0a5Jw6BP/TExoCmNFYjZl248A0osgPyGEmRA+fAsqPVaNAfytu0vuQJ7rk3J4kTDTR2AlCHJ5cls26opZM4w3jMULh2YXKpcqGBtuleAlOZnaZGbD6DHzMd6i2oFeJ8z9XYmalg1Szd/ocZDc1C7Y6vcALJz2lYnTXiWEr2wawtoR4g3jvWUU2Ngjd1cewtFzEvM1NiHZPeLlIXFbBPawxNgMwwAlyNSuGF3zizVeOoC9bag1qRAQKQE/EZBWC2J8mnXAN2aTBboZ7HewnObE8CwROudZHmUM5oZ/Ugd/JZQK8lvAm43uDRAbyW8gZ+ZGq0EVerVGUKUSm/Idn8AQHdR4m7bue88WBwft9mSCeMOt1ncBwziOmJYI2ZR7ewNMPiCugmSsE4EyQ+QATJG6qORMGd4snEzc6B4shPIo4G1T7PgSm8PY5eUkPdF8JZ0VBtadbHXoJgnEhZQaODPj2gpODKJY5Yp4DOsLBFxWbvXN755KWylJm+oOd4zEL9Hpubuy2gyyfxh8oEfFutnYWdfB8PdESLWYvSqbElP9qo3u6KTmkhoacDauMNNjj0oy40DFV7Ql0aZj77xfGl7TJNHnIwgqOkenruYYNo6h724+zUQ7+vkCpZB+pGA562hYQiDxHVWOq0oDQl/QsoiY+cuI7iWq/ZIBtHcXJ7kks+h2fCNUPA82BzjnqktNts+RLdk1VSu+tqEn7QZCCsvEqk6FkfiOYkrsw092J8jsfIuEKypNjLxrKA9kiA19mxBD2suxQKCzwXGws7kEJvlhUiV9tArLIdZW0IORcxEzdzKmjtFhsjKy/44XYXdI5noQoRcvjZ1RMPACRqYg2V1+OwOepcOknRLLFdYgTkT5UApt/JhLM3jeFYprZV+Zow2g8fP+U68hkKFWJj2yBbKqsrp25xkZX1DAjUw52IMYWaOhab8Kp05VrdNftqwRrymWF4OQSjbdfzmRZirK8FMJELEgER2PHjEAN9pGfLhCUiTJFbd5LBkOBMaxLr/A1SY9dXFz4RjzoU9ExfJCmx/I9FKEGT3n2cmzl2X42L3Jh+AbQq6sA+Ss1kitoa4TAYgKHaoybHUDJ51oETdeI/9ThSmjWGkyLi5QAGWhL0BG1UsTyRGRJOldKBrYJeB8ljLJHfATWTEQBXBDnQexOHTB+Un44zExFE4vLytcu5NwpWrUxO/0ZICUGM7hGABXym0V6ZvDST0E370St9MIWQOTWngeoQHUTdCJUP04spMBMS8LSker9cReVQkULFDIZDFPrhTzBl6sed9wcZQTbL+BDqMyaN3RJPh/anbx+Iv+qgQdAa3M9Z5JmvYlh4qop+Ho1F1W5gbOE9YKLgAnWytXElU4G8GtW47lhgFE6gaSs+gs37sFvi0PPVvA5dnCBgILTwoKd/+DoL9F6inlM7H4rOTzD79KJgKlZO/Zgt22UsKhrAaXU5ZcLrAglTVKJEmNJvORGN1vqrcfSMizfpsgbIe9zno+gBoKVXgIL/VI8dB1O5o/R3Suez/gD7M781ShjKpIIORM/nxG+jjhhgPwsn2IoXsPGPqYHXA63zJ07M2GPEykQwJBYLK808qYxuIew4frk52nhCsnCYmXiR6CuapvE1IwRB4/QftDbEn+AucIr1oxrLabRj9q4ae0+fXkHnteAJwXRbVkR0mctVSwEbqhJiMSZUp9DNbEDMmjX22m3ABpkrPQQTP3S1sib5pD2VRKRd+eNAjLYyT0hGrdjWJZy24OYXRoWQAIhGBZRxuBFMjjZQhpgrWo8SiFYbojcHO8V5DyscJpLTHyx9Fimassyo5U6WNtquUMYgccaHY5amgR3PQzq3ToNM5ABnoB9kuxsebqmYZm0R9qxJbFXCQ1UPyFIbxoUraTJFDpCk0Wk9GaYJKz/6oHwEP0Q14lMtlddQsOAU9zlYdMVHiT7RQP3XCmWYDcHCGbVRHGnHuwzScA0BaSBOGkz3lM8CArjrBsyEoV6Ys4qgDK3ykQQPZ3hCRGNXQTNNXbEb6tDiTDLKOyMzRhCFT+mAUmiYbV3YQVqFVp9dorv+TsLeCykS2b5yyu8AV7IS9cxcL8z4Kfwp+xJyYLv1OsxQCZwTB4a8BZ/5EdxTBJthApqyfd9u3ifr/WILTqq5VqgwMT9SOxbSGWLQJUUWCVi4k9tho9nEsbUh7U6NUsLmkYFXOhZ0kmamaJLRNJzSj/qn4Mso6zb6iLLBXoaZ6AqeWCjHQm2lztnejYYM2eubnpBdKVLORZhudH3JF1waBJKA9+W8EhMj3Kzf0L4vi4k6RoHh3Z5YgmSZmk6ns4fjScjAoL8GoOECgqgYEBYUGFVO4FUv4/YtowhEmTs0vrvlD/CrisnoBNDAcUi/teY7OctFlmARQzjOItrrlKuPO6E2Ox93L4O/4DcgV/dZ7qR3VBwVQxP1GCieA4RIpweYJ5FoYrHxqRBdJjnqbsikA2Ictbb8vE1GYIo9dacK0REgDX4smy6GAkxlH1yCGGsk+tgiDhNKuKu3yNrMdxafmKTF632F8Vx4BNK57GvlFisrkjN9WDAtjsWA0ENT2e2nETUb/n7qwhvGnrHuf5bX6Vh/n3xffU3PeHdR+FA92i6ufT3AlyAREoNDh6chiMWTvjKjHDeRhOa9YkOQRq1vQXEMppAQVwHCuIcV2g5rBn6GmZZpTR7vnSD6ZmhdSl176gqKTXu5E+YbfL0adwNtHP7dT7t7b46DVZIkzaRJOM+S6KcrzYVg+T3wSRFRQashjfU18NutrKa/7PXbtuJvpIjbgPeqd+pjmRw6YKpnANFSQcpzTZgpSNJ6J7uiagAbir/8tNXJ/OsOnRh6iuIexxrmkIneAgz8QoLmiaJ8sLQrELVK2yn3wOHp57BAZJhDZjTBzyoRAuuZ4eoxHruY1pSb7qq79cIeAdOwin4GdgMeIMHeG+FZWYaiUQQyC5b50zKjYw97dFjAeY2I4Bnl105Iku1y0lMA1ZHolLx19uZnRdILcXKlZGQx/GdEqSsMRU1BIrFqRcV1qQOOHyxOLXEGcbRtAEsuAC2V4K3p5mFJ22IDWaEkk9ttf5Izb2LkD1MnrSwztXmmD/Qi/EmVEFBfiKGmftsPwVaIoZanlKndMZsIBOskFYpDOq3QUs9aSbAAtL5Dbokus2G4/asthNMK5UQKCOhU97oaOYNGsTah+jfCKsZnTRn5TbhFX8ghg8CBYt/BjeYYYUrtUZ5jVij/op7V5SsbA4mYTOwZ46hqdpbB6Qvq3AS2HHNkC15pTDIcDNGsMPXaBidXYPHc6PJAkRh29Vx8KcgX46LoUQBhRM+3SW6Opll/wgxxsPgKJKzr5QCmwkUxNbeg6Wj34SUnEzOemSuvS2OetRCO8Tyy+QbSKVJcqkia+GvDefFwMOmgnD7h81TUtMn+mRpyJJ349HhAnoWFTejhpYTL9G8N2nVg1qkXBeoS9Nw2fB27t7trm7d/QK7Cr4uoCeOQ7/8JfKT77KiDzLImESHw/0wf73QeHu74hxv7uihi4fTX+XEwAyQG3264dwv17aJ5N335Vt9sdrAXhPOAv8JFvzqyYXwfx8WYJaef1gMl98JRFyl5Mv5Uo/oVH5ww5OzLFsiTPDns7fS6EURSSWd/92BxMYQ8sBaH+j+wthQPdVgDGpTfi+JQIWMD8xKqULliRH01rTeyF8x8q/GBEEEBrAJMPf25UQwi0b8tmqRXY7kIvNkzrkvRWLnxoGYEJsz8u4oOyMp8cHyaybb1HdMCaLApUE+/7xLIZGP6H9xuSEXp1zLIdjk5nBaMuV/yTDRRP8Y2ww5RO6d2D94o+6ucWIqUAvgHIHXhZsmDhjVLczmZ3ca0Cb3PpKwt2UtHVQ0BgFJsqqTsnzZPlKahRUkEu4qmkJt+kqdae76ViWe3STan69yaF9+fESD2lcQshLHWVu4ovItXxO69bqC5p1nZLvI8NdQB9s9UNaJGlQ5mG947ipdDA0eTIw/A1zEdjWquIsQXXGIVEH0thC5M+W9pZe7IhAVnPJkYCCXN5a32HjN6nsvokEqRS44tGIs7s2LVTvcrHAF+RVmI8L4HUYk4x+67AxSMJKqCg8zrGOgvK9kNMdDrNiUtSWuHFpC8/p5qIQrEo/H+1l/0cAwQ2nKmpWxKcMIuHY44Y6DlkpO48tRuUGBWT0FyHwSKO72Ud+tJUfdaZ4CWNijzZtlRa8+CkmO/EwHYfPZFU/hzjFWH7vnzHRMo+aF9u8qHSAiEkA2HjoNQPEwHsDKOt6hOoK3Ce/+/9boMWDa44I6FrQhdgS7OnNaSzwxWKZMcyHi6LN4WC6sSj0qm2PSOGBTvDs/GWJS6SwEN/ULwpb4LQo9fYjUfSXRwZkynUazlSpvX9e+G2zor8l+YaMxSEomDdLHGcD6YVQPegTaA74H8+V4WvJkFUrjMLGLlvSZQWvi8/QA7yzQ8GPno//5SJHRP/OqKObPCo81s/+6WgLqykYpGAgQZhVDEBPXWgU/WzFZjKUhSFInufPRiMAUULC6T11yL45ZrRoB4DzOyJShKXaAJIBS9wzLYIoCEcJKQW8GVCx4fihqJ6mshBUXSw3wWVj3grrHQlGNGhIDNNzsxQ3M+GWn6ASobIWC+LbYOC6UpahVO13Zs2zOzZC8z7FmA05JhUGyBsF4tsG0drcggIFzgg/kpf3+CnAXKiMgIE8Jk/Mhpkc8DUJEUzDSnWlQFme3d0sHZDrg7LavtsEX3cHwjCYA17pMTfx8Ajw9hHscN67hyo+RJQ4458RmPywXykkVcW688oVUrQhahpPRvTWPnuI0B+SkQu7dCyvLRyFYlC1LG1gRCIvn3rwQeINzZQC2KXq31FaR9UmVV2QeGVqBHjmE+VMd3b1fhCynD0pQNhCG6/WCDbKPyE7NRQzL3BzQAJ0g09aUzcQA6mUp9iZFK6Sbp/YbHjo++7/Wj8S4YNa+ZdqAw1hDrKWFXv9+zaXpf8ZTDSbiqsxnwN/CzK5tPkOr4tRh2kY3Bn9JtalbIOI4b3F7F1vPQMfoDcdxMS8CW9m/NCW/HILTUVWQIPiD0j1A6bo8vsv6P1hCESl2abrSJWDrq5sSzUpwoxaCU9FtJyYH4QFMxDBpkkBR6kn0LMPO+5EJ7Z6bCiRoPedRZ/P0SSdii7ZnPAtVwwHUidcdyspwncz5uq6vvm4IEDbJVLUFCn/LvIHfooUBTkFO130FC7CmmcrKdgDJcid9mvVzsDSibOoXtIf9k6ABle3PmIxejodc4aob0QKS432srrCMndbfD454q52V01G4q913mC5HOsTzWF4h2No1av1VbcUgWAqyoZl+11PoFYnNv2HwAODeNRkHj+8SF1fcvVBu6MrehHAZK1Gm69ICcTKizykHgGFx7QdowTVAsYEF2tVc0Z6wLryz2FI1sc5By2znJAAmINndoJiB4sfPdPrTC8RnkW7KRCwxC6YvXg5ahMlQuMpoCSXjOlBy0Kij+bsCYPbGp8BdCBiLmLSAkEQRaieWo1SYvZIKJGj9Ur/eWHjiB7SOVdqMAVmpBvfRiebsFjger7DC+8kRFGtNrTrnnGD2GAJb8rQCWkUPYHhwXsjNBSkE6lGWUj5QNhK0DMNM2l+kXRZ0KLZaGsFSIdQz/HXDxf3/TE30+DgBKWGWdxElyLccJfEpjsnszECNoDGZpdwdRgCixeg9L4EPhH+RptvRMVRaahu4cySjS3P5wxAUCPkmn+rhyASpmiTaiDeggaIxYBmtLZDDhiWIJaBgzfCsAGUF1Q1SFZYyXDt9skCaxJsxK2Ms65dmdp5WAZyxik/zbrTQk5KmgxCg/f45L0jywebOWUYFJQAJia7XzCV0x89rpp/f3AVWhSPyTanqmik2SkD8A3Ml4NhIGLAjBXtPShwKYfi2eXtrDuKLk4QlSyTw1ftXgwqA2jUuopDl+5tfUWZNwBpEPXghzbBggYCw/dhy0ntds2yeHCDKkF/YxQjNIL/F/37jLPHCKBO9ibwYCmuxImIo0ijV2Wbg3kSN2psoe8IsABv3RNFaF9uMyCtCYtqcD+qNOhwMlfARQUdJ2tUX+MNJqOwIciWalZsmEjt07tfa8ma4cji9sqz+Q9hWfmMoKEbIHPOQORbhQRHIsrTYlnVTNvcq1imqmmPDdVDkJgRcTgB8Sb6epCQVmFZe+jGDiNJQLWnfx+drTKYjm0G8yH0ZAGMWzEJhUEQ4Maimgf/bkvo8PLVBsZl152y5S8+HRDfZIMCbYZ1WDp4yrdchOJw8k6R+/2pHmydK4NIK2PHdFPHtoLmHxRDwLFb7eB+M4zNZcB9NrAgjVyzLM7xyYSY13ykWfIEEd2n5/iYp3ZdrCf7fL+en+sIJu2W7E30MrAgZBD1rAAbZHPgeAMtKCg3NpSpYQUDWJu9bT3V7tOKv+NRiJc8JAKqqgCA/PNRBR7ChpiEulyQApMK1AyqcWnpSOmYh6yLiWkGJ2mklCSPIqN7UypWj3dGi5MvsHQ87MrB4VFgypJaFriaHivwcHIpmyi5LhNqtem4q0n8awM19Qk8BOS0EsqGscuuydYsIGsbT5GHnERUiMpKJl4ON7qjB4fEqlGN/hCky89232UQCiaeWpDYCJINXjT6xl4Gc7DxRCtgV0i1ma4RgWLsNtnEBRQFqZggCLiuyEydmFd7WlogpkCw5G1x4ft2psm3KAREwVwr1Gzl6RT7FDAqpVal34ewVm3VH4qn5mjGj+bYL1NgfLNeXDwtmYSpwzbruDKpTjOdgiIHDVQSb5/zBgSMbHLkxWWgghIh9QTFSDILixVwg0Eg1puooBiHAt7DzwJ7m8i8/i+jHvKf0QDnnHVkVTIqMvIQImOrzCJwhSR7qYB5gSwL6aWL9hERHCZc4G2+JrpgHNB8eCCmcIWIQ6rSdyPCyftXkDlErUkHafHRlkOIjxGbAktz75bnh50dU7YHk+Mz7wwstg6RFZb+TZuSOx1qqP5C66c0mptQmzIC2dlpte7vZrauAMm/7RfBYkGtXWGiaWTtwvAQiq2oD4YixPLXE2khB2FRaNRDTk+9sZ6K74Ia9VntCpN4BhJGJMT4Z5c5FhSepRCRWmBXqx+whVZC4me4saDs2iNqXMuCl6iAZflH8fscC1sTsy4PHeC+XYuqMBMUun5YezKbRKmEPwuK+CLzijPEQgfhahQswBBLfg/GBgBiI4QwAqzJkkyYAWtjzSg2ILgMAgqxYfwERRo3zruBL9WOryUArSD8sQOcD7fvIODJxKFS615KFPsb68USBEPPj1orNzFY2xoTtNBVTyzBhPbhFH0PI5AtlJBl2aSgNPYzxYLw7XTDBDinmVoENwiGzmngrMo8OmnRP0Z0i0Zrln9DDFcnmOoBZjABaQIbPOJYZGqX+RCMlDDbElcjaROLDoualmUIQ88Kekk3iM4OQrADcxi3rJguS4MOIBIgKgXrjd1WkbCdqxJk/4efRIFsavZA7KvvJQqp3Iid5Z0NFc5aiMRzGN3vrpBzaMy4JYde3wr96PjN90AYOIbyp6T4zj8LoE66OGcX1Ef4Z3KoWLAUF4BTg7ug/AbkG5UNQXAMkQezujSHeir2uTThgd3gpyzDrbnEdDRH2W7U6PeRvBX1ZFMP5RM+Zu6UUZZD8hDPHldVWntTCNk7To8IeOW9yn2wx0gmurwqC60AOde4r3ETi5pVMSDK8wxhoGAoEX9NLWHIR33VbrbMveii2jAJlrxwytTHbWNu8Y4N8vCCyZjAX/pcsfwXbLze2+D+u33OGBoJyAAL3jn3RuEcdp5If8O+a4NKWvxOTyDltG0IWoHhwVGe7dKkCWFT++tm+haBCikRUUMrMhYKZJKYoVuv/bsJzO8DwfVIInQq3g3BYypiz8baogH3r3GwqCwFtZnz4xMjAVOYnyOi5HWbFA8n0qz1OjSpHWFzpQOpvkNETZBGpxN8ybhtqV/DMUxd9uFZmBfKXMCn/SqkWJyKPnT6lq+4zBZni6fYRByJn6OK+OgPBGRAJluwGSk4wxjOOzyce/PKODwRlsgrVkdcsEiYrqYdXo0Er2GXi2GQZd0tNJT6c9pK1EEJG1zgDJBoTVuCXGAU8BKTvCO/cEQ1Wjk3Zzuy90JX4m3O5IlxVFhYkSUwuQB2up7jhvkm+bddRQu5F9s0XftGEJ9JSuSk+ZachCbdU45fEqbugzTIUokwoAKvpUQF/CvLbWW5BNQFqFkJg2f30E/48StNe5QwBg8zz3YAJ82FZoXBxXSv4QDooDo79NixyglO9AembuBcx5Re3CwOKTHebOPhkmFC7wNaWtoBhFuV4AkEuJ0J+1pT0tLkvFVZaNzfhs/Kd3+A9YsImlO4XK4vpCo/elHQi/9gkFg07xxnuXLt21unCIpDV+bbRxb7FC6nWYTsMFF8+1LUg4JFjVt3vqbuhHmDKbgQ4e+RGizRiO8ky05LQGMdL2IKLSNar0kNG7lHJMaXr5mLdG3nykgj6vB/KVijd1ARWkFEf3yiUw1v/WaQivVUpIDdSNrrKbjO5NPnxz6qTTGgYg03HgPhDrCFyYZTi3XQw3HXCva39mpLNFtz8AiEhxAJHpWX13gCTAwgm9YTvMeiqetdNQv6IU0hH0G+ZManTqDLPjyrOse7WiiwOJCG+J0pZYULhN8NILulmYYvmVcV2MjAfA39sGKqGdjpiPo86fecg65UPyXDIAOyOkCx5NQsLeD4gGVjTVDwOHWkbbBW0GeNjDkcSOn2Nq4cEssP54t9D749A7M1AIOBl0Fi0sSO5v3P7LCBrM6ZwFY6kp2FX6AcbGUdybnfChHPyu6WlRZ2Fwv9YM0RMI7kISRgR8HpQSJJOyTfXj/6gQKuihPtiUtlCQVPohUgzfezTg8o1b3n9pNZeco1QucaoXe40Fa5JYhqdTspFmxGtW9h5ezLFZs3j/N46f+S2rjYNC2JySXrnSAFhvAkz9a5L3pza8eYKHNoPrvBRESpxYPJdKVUxBE39nJ1chrAFpy4MMkf0qKgYALctGg1DQI1kIymyeS2AJNT4X240d3IFQb/0jQbaHJ2YRK8A+ls6WMhWmpCXYG5jqapGs5/eOJErxi2/2KWVHiPellTgh/fNl/2KYPKb7DUcAg+mCOPQFCiU9Mq/WLcU1xxC8aLePFZZlE+PCLzf7ey46INWRw2kcXySR9FDgByXzfxiNKwDFbUSMMhALPFSedyjEVM5442GZ4hTrsAEvZxIieSHGSgkwFh/nFNdrrFD4tBH4Il7fW6ur4J8Xaz7RW9jgtuPEXQsYk7gcMs2neu3zJwTyUerHKSh1iTBkj2YJh1SSOZL5pLuQbFFAvyO4k1Hxg2h99MTC6cTUkbONQIAnEfGsGkNFWRbuRyyaEZInM5pij73EA9rPIUfU4XoqQpHT9THZkW+oKFLvpyvTBMM69tN1Ydwv1LIEhHsC+ueVG+w+kyCPsvV3erRikcscHjZCkccx6VrBkBRusTDDd8847GA7p2Ucy0y0HdSRN6YIBciYa4vuXcAZbQAuSEmzw+H/AuOx+aH+tBL88H57D0MsqyiZxhOEQkF/8DR1d2hSPMj/sNOa5rxcUnBgH8ictv2J+cb4BA4v3MCShdZ2vtK30vAwkobnEWh7rsSyhmos3WC93Gn9C4nnAd/PjMMtQfyDNZsOPd6XcAsnBE/mRHtHEyJMzJfZFLE9OvQa0i9kUmToJ0ZxknTgdl/XPV8xoh0K7wNHHsnBdvFH3sv52lU7UFteseLG/VanIvcwycVA7+BE1Ulyb20BvwUWZcMTKhaCcmY3ROpvonVMV4N7yBXTL7IDtHzQ4CCcqF66LjF3xUqgErKzolLyCG6Kb7irP/MVTCCwGRxfrPGpMMGvPLgJ881PHMNMIO09T5ig7AzZTX/5PLlwnJLDAPfuHynSGhV4tPqR3gJ4kg4c06c/F1AcjGytKm2Yb5jwMotF7vro4YDLWlnMIpmPg36NgAZsGA0W1spfLSue4xxat0Gdwd0lqDBOgIaMANykwwDKejt5YaNtJYIkrSgu0KjIg0pznY0SCd1qlC6R19g97UrWDoYJGlrvCE05J/5wkjpkre727p5PTRX5FGrSBIfJqhJE/IS876PaHFkx9pGTH3oaY3jJRvLX9Iy3Edoar7cFvJqyUlOhAEiOSAyYgVEGkzHdug+oRHIEOXAExMiTSKU9A6nmRC8mp8iYhwWdP2U/5EkFAdPrZw03YA3gSyNUtMZeh7dDCu8pF5x0VORCTgKp07ehy7NZqKTpIC4UJJ89lnboyAfy5OyXzXtuDRbtAFjZRSyGFTpFrXwkpjSLIQIG3N0Vj4BtzK3wdlkBJrO18MNsgseR4BysJilI0wI6ZahLhBFA0XBmV8d4LUzEcNVb0xbLjLTETYN8OEVqNxkt10W614dd1FlFFVTIgB7/BQQp1sWlNolpIu4ekxUTBV7NmxOFKEBmmN+nA7pvF78/RII5ZHA09OAiE/66MF6HQ+qVEJCHxwymukkNvzqHEh52dULPbVasfQMgTDyBZzx4007YiKdBuUauQOt27Gmy8ISclPmEUCIcuLbkb1mzQSqIa3iE0PJh7UMYQbkpe+hXjTJKdldyt2mVPwywoODGJtBV1lJTgMsuSQBlDMwhEKIfrvsxGQjHPCEfNfMAY2oxvyKcKPUbQySkKG6tj9AQyEW3Q5rpaDJ5Sns9ScLKeizPRbvWYAw4bXkrZdmB7CQopCH8NAmqbuciZChHN8lVGaDbCnmddnqO1PQ4ieMYfcSiBE5zzMz+JV/4eyzrzTEShvqSGzgWimkNxLvUj86iAwcZuIkqdB0VaIB7wncLRmzHkiUQpPBIXbDDLHBlq7vp9xwuC9AiNkIptAYlG7Biyuk8ILdynuUM1cHWJgeB+K3wBP/ineogxkvBNNQ4AkW0hvpBOQGFfeptF2YTR75MexYDUy7Q/9uocGsx41O4IZhViw/2FvAEuGO5g2kyXBUijAggWM08bRhXg5ijgMwDJy40QeY/cQpUDZiIzmvskQpO5G1zyGZA8WByjIQU4jRoFJt56behxtHUUE/om7Rj2psYXGmq3llVOCgGYKNMo4pzwntITtapDqjvQtqpjaJwjHmDzSVGLxMt12gEXAdLi/caHSM3FPRGRf7dB7YC+cD2ho6oL2zGDCkjlf/DFoQVl8GS/56wur3rdV6ggtzZW60MRB3g+U1W8o8cvqIpMkctiGVMzXUFI7FacFLrgtdz4mTEr4aRAaQ2AFQaNeG7GX0yOJgMRYFziXdJf24kg/gBQIZMG/YcPEllRTVNoDYR6oSJ8wQNLuihfw81UpiKPm714bZX1KYjcXJdfclCUOOpvTxr9AAJevTY4HK/G7F3mUc3GOAKqh60zM0v34v+ELyhJZqhkaMA8UMMOU90f8RKEJFj7EqepBVwsRiLbwMo1J2zrE2UYJnsgIAscDmjPjnzI8a719Wxp757wqmSJBjXowhc46QN4RwKIxqEE6E5218OeK7RfcpGjWG1jD7qND+/GTk6M56Ig4yMsU6LUW1EWE+fIYycVV1thldSlbP6ltdC01y3KUfkobkt2q01YYMmxpKRvh1Z48uNKzP/IoRIZ/F6buOymSnW8gICitpJjKWBscSb9JJKaWkvEkqinAJ2kowKoqkqZftRqfRQlLtKoqvTRDi2vg/RrPD/d3a09J8JhGZlEkOM6znTsoMCsuvTmywxTCDhw5dd0GJOHCMPbsj3QLkTE3MInsZsimDQ3HkvthT7U9VA4s6G07sID0FW4SHJmRGwCl+Mu4xf0ezqeXD2PtPDnwMPo86sbwDV+9PWcgFcARUVYm3hrFQrHcgMElFGbSM2A1zUYA3baWfheJp2AINmTJLuoyYD/OwA4a6V0ChBN97E8YtDBerUECv0u0TlxR5yhJCXvJxgyM73Bb6pyq0jTFJDZ4p1Am1SA6sh8nADd1hAcGBMfq4d/UfwnmBqe0Jun1n1LzrgKuZMAnxA3NtCN7Klf4BH+14B7ibBmgt0TGUafVzI4uKlpF7v8NmgNjg90D6QE3tbx8AjSAC+OA1YJvclyPKgT27QpIEgVYpbPYGBsnyCNrGz9XUsCHkW1QAHgL2STZk12QGqmvAB0NFteERkvBIH7INDsNW9KKaAYyDMdBEMzJiWaJHZALqDxQDWRntumSDPcplyFiI1oDpT8wbwe01AHhW6+vAUUBoGhY3CT2tgwehdPqU/4Q7ZLYvhRl/ogOvR9O2+wkkPKW5vCTjD2fHRYXONCoIl4Jh1bZY0ZE1O94mMGn/dFSWBWzQ/VYk+Gezi46RgiDv3EshoTmMSlioUK6MQEN8qeyK6FRninyX8ZPeUWjjbMJChn0n/yJvrq5bh5UcCAcBYSafTFg7p0jDgrXo2QWLb3WpSOET/Hh4oSadBTvyDo10IufLzxiMLAnbZ1vcUmj3w7BQuIXjEZXifwukVxrGa9j+DXfpi12m1RbzYLg9J2wFergEwOxFyD0/JstNK06ZN2XdZSGWxcJODpQHOq4iKqjqkJUmPu1VczL5xTGUfCgLEYyNBCCbMBFT/cUP6pE/mujnHsSDeWxMbhrNilS5MyYR0nJyzanWXBeVcEQrRIhQeJA6Xt4f2eQESNeLwmC10WJVHqwx8SSyrtAAjpGjidcj1E2FYN0LObUcFQhafUKTiGmHWRHGsFCB+HEXgrzJEB5bp0QiF8ZHh11nFX8AboTD0PS4O1LqF8XBks2MpjsQnwKHF6HgaKCVLJtcr0XjqFMRGfKv8tmmykhLRzu+vqQ02+KpJBjaLt9ye1Ab+BbEBhy4EVdIJDrL2naV0o4wU8YZ2Lq04FG1mWCKC+UwkXOoAjneU/xHplMQo2cXUlrVNqJYczgYlaOEczVCs/OCgkyvLmTmdaBJc1iBLuKwmr6qtRnhowngsDxhzKFAi02tf8bmET8BO27ovJKF1plJwm3b0JpMh38+xsrXXg7U74QUM8ZCIMOpXujHntKdaRtsgyEZl5MClMVMMMZkZLNxH9+b8fH6+b8Lev30A9TuEVj9CqAdmwAAHBPbfOBFEATAPZ2CS0OH1Pj/0Q7PFUcC8hDrxESWdfgFRm+7vvWbkEppHB4T/1ApWnlTIqQwjcPl0VgS1yHSmD0OdsCVST8CQVwuiew1Y+g3QGFjNMzwRB2DSsAk26cmA8lp2wIU4p93AUBiUHFGOxOajAqD7Gm6NezNDjYzwLOaSXRBYcWipTSONHjUDXCY4mMI8XoVCR/Rrs/JLKXgEx+qkmeDlFOD1/yTQNDClRuiUyKYCllfMiQiyFkmuTz2vLsBNyRW+xz+5FElFxWB28VjYIGZ0Yd+5wIjkcoMaggxswbT0pCmckRAErbRlIlcOGdBo4djTNO8FAgQ+lT6vPS60BwTRSUAM3ddkEAZiwtEyArrkiDRnS7LJ+2hwbzd2YDQagSgACpsovmjil5wfPuXq3GuH0CyE7FK3M4FgRaFoIkaodORrPx1+JpI9psyNYIFuJogZa0/1AhOWdlHQxdAgbwacsHqPZo8u/ngAH2GmaTdhYnBfSDbBfh8CHq6Bx5bttP2+RdM+MAaYaZ0Y/ADkbNCZuAyAVQa2OcXOeICmDn9Q/eFkDeFQg5MgHEDXq/tVjj+jtd26nhaaolWxs1ixSUgOBwrDhRIGOLyOVk2/Bc0UxvseQCO2pQ2i+Krfhu/WeBovNb5dJxQtJRUDv2mCwYVpNl2efQM9xQHnK0JwLYt/U0Wf+phiA4uw8G91slC832pmOTCAoZXohg1fewCZqLBhkOUBofBWpMPsqg7XEXgPfAlDo2U5WXjtFdS87PIqClCK5nW6adCeXPkUiTGx0emOIDQqw1yFYGHEVx20xKjJVYe0O8iLmnQr3FA9nSIQilUKtJ4ZAdcTm7+ExseJauyqo30hs+1qSW211A1SFAOUgDlCGq7eTIcMAeyZkV1SQJ4j/e1Smbq4HcjqgFbLAGLyKxlMDMgZavK5NAYH19Olz3la/QCTiVelFnU6O/GCvykqS/wZJDhKN9gBtSOp/1SP5VRgJcoVj+kmf2wBgv4gjrgARBWiURYx8xENV3bEVUAAWWD3dYDKAIWk5opaCFCMR5ZjJExiCAw7gYiSZ2rkyTce4eNMY3lfGn+8p6+vBckGlKEXnA6Eota69OxDO9oOsJoy28BXOR0UoXNRaJD5ceKdlWMJlOFzDdZNpc05tkMGQtqeNF2lttZqNco1VtwXgRstLSQ6tSPChgqtGV5h2DcDReIQadaNRR6AsAYKL5gSFsCJMgfsaZ7DpKh8mg8Wz8V7H+gDnLuMxaWEIUPevIbClgap4dqmVWSrPgVYCzAoZHIa5z2Ocx1D/GvDOEqMOKLrMefWIbSWHZ6jbgA8qVBhYNHpx0P+jAgN5TB3haSifDcApp6yymEi6Ij/GsEpDYUgcHATJUYDUAmC1SCkJ4cuZXSAP2DEpQsGUjQmKJfJOvlC2x/pChkOyLW7KEoMYc5FDC4v2FGqSoRWiLsbPCiyg1U5yiHZVm1XLkHMMZL11/yxyw0UnGig3MFdZklN5FI/qiT65T+jOXOdO7XbgWurOAZR6Cv9uu1cm5LjkXX4xi6mWn5r5NjBS0gTliHhMZI2WNqSiSphEtiCAwnafS11JhseDGHYQ5+bqWiAYiAv6Jsf79/VUs4cIl+n6+WOjcgB/2l5TreoAV2717JzZbQIR0W1cl/dEqCy5kJ3ZSIHuU0vBoHooEpiHeQWVkkkOqRX27eD1FWw4BfO9CJDdKoSogQi3hAAwsPRFrN5RbX7bqLdBJ9JYMohWrgJKHSjVl1sy2xAG0E3sNyO0oCbSGOxCNBRRXTXenYKuwAoDLfnDcQaCwehUOIDiHAu5m5hMpKeKM4sIo3vxACakIxKoH2YWF2QM84e6F5C5hJU4g8uxuFOlAYnqtwxmHyNEawLW/PhoawJDrGAP0JYWHgAVUByo/bGdiv2T2EMg8gsS14/rAdzlOYazFE7w4OzxeKiWdm3nSOnQRRKXSlVo8HEAbBfyJMKqoq+SCcTSx5NDtbFwNlh8VhjGGDu7JG5/TAGAvniQSSUog0pNzTim8Owc6QTuSKSTXlQqwV3eiEnklS3LeSXYPXGK2VgeZBqNcHG6tZHvA3vTINhV0ELuQdp3t1y9+ogD8Kk/W7QoRN1UWPqM4+xdygkFDPLoTaumKReKiLWoPHOfY54m3qPx4c+4pgY3MRKKbljG8w4wvz8pxk3AqKsy4GMAkAtmRjRMsCxbb4Q2Ds0Ia9ci8cMT6DmsJG00XaHCIS+o3F8YVVeikw13w+OEDaCYYhC0ZE54kA4jpjruBr5STWeqQG6M74HHL6TZ3lXrd99ZX++7LhNatQaZosuxEf5yRA15S9gPeHskBIq3Gcw81AGb9/O53DYi/5CsQ51EmEh8Rkg4vOciClpy4d04eYsfr6fyQkBmtD+P8sNh6e+XYHJXT/lkXxT4KXU5F2sGxYyzfniMMQkb9OjDN2C8tRRgTyL7GwozH14PrEUZc6oz05Emne3Ts5EG7WolDmU8OB1LDG3VrpQxp+pT0KYV5dGtknU64JhabdqcVQbGZiAxQAnvN1u70y1AnmvOSPgLI6uB4AuDGhmAu3ATkJSw7OtS/2ToPjqkaq62/7WFG8advGlRRqxB9diP07JrXowKR9tpRa+jGJ91zxNTT1h8I2PcSfoUPtd7NejVoH03EUcqSBuFZPkMZhegHyo2ZAITovmm3zAIdGFWxoNNORiMRShgwdYwFzkPw5PA4a5MIIQpmq+nsp3YMuXt/GkXxLx/P6+ZJS0lFyz4MunC3eWSGE8xlCQrKvhKUPXr0hjpAN9ZK4PfEDrPMfMbGNWcHDzjA7ngMxTPnT7GMHar+gMQQ3NwHCv4zH4BIMYvzsdiERi6gebRmerTsVwZJTRsL8dkZgxgRxmpbgRcud+YlCIRpPwHShlUSwuipZnx9QCsEWziVazdDeKSYU5CF7UVPAhLer3CgJOQXl/zh575R5rsrmRnKAzq4POFdgbYBuEviM4+LVC15ssLNFghbTtHWerS1hDt5s4qkLUha/qpZXhWh1C6lTQAqCNQnaDjS7UGFBC6wTu8yFnKJnExCnAs3Ok9yj5KpfZESQ4lTy5pTGTnkAUpxI+yjEldJfSo4y0QhG4i4IwkRFGcjWY8+EzgYYJUK7BXQksLxAww/YYWBMhJILB9e8ePEJ4OP7z+4/wOQDl64iOYDp26DaONPxpKtBxq/aTzRGarm3VkPYTLJKx6Z/Mw2YbBGseJhPMwhhNswrIkyvV2BYzrvZbxLpKwcWJhYmFtVZ+lPEq91FzVp1HlQY1bZVLqeNR9SAUn6n0E28k/UuGkNpP1DBI5ch/EehZfjUQ9aE41NhETExoPT2gGQz0IhWJbEOvTQ4wgcXCHHFBhewYUiFHuhRSAUVmEHeCRQHQkXGFwkAgyzREJCVN7TRnTon36Zw3tPhx4EALwNdwDv+J41YSP4B2CQqz0EFgARZ4ESgBHQgROwAVn9GTI+HYexTUevLUeta4/DqKrbMVS+Yqb8hUwYCrlgKtmAq1YCrFgKrd4qpXiqZcKn1oqdWipjYKpWwVPVYqW6xUpVipKqFR3QKjagVEtAqHpxUMTitsnFaJOKx2cVhswq35RVpyiq9lFVNIKnOQVMkgqtYxVNxiqQjFS7GKlSIVIsQqPIhUWwioigFQ++KkN8VHr49HDw9Ebo9EDo9DTo9Crg9BDg9/Wx7gWx7YWwlobYrOGxWPNisAaAHEyALpkAVDIAeWAArsABVXACYuAD5cAF6wAKFQAQqgAbVAAsoAAlQAUaYAfkwAvogBWQACOgAD9AAHSAAKT4GUdMiOvFngBTwCn2AZ7Dv6B6k/90B8+yRnkV144AIBoAMTQATGgAjNAA4YABgwABZgB/mQCwyAVlwCguASlwCEuAQFwB4uAMlwBYuAJlQAUVAAhUD2KgdpUDaJgaRMDFJgX5MC1JgWJEAokQCWRAHxEAWkQBMRADpEAMkQAYROAEecC484DRpwBDTnwNOdw05tjTmiNOYwtswhYFwLA7BYG4LA2BYGOLAwRYFuLAsxYFQJAohIEyJAMwkAwiQC0JAJgkAeiQBkJAFokAPCQA0JABwcD4Dgc4cDdDgaYcDIDgYgUC6CgWgUClCgUYUAVBQBOFAEYMALgwAgDA9QYAdIn8AZzeBB2L5EcWrenUT1KXienEsuJJ7x5U8XlTjc1NVzUyXFTGb1LlpUtWlTDIjqwE4LsagowoCi2gJLKAkpoBgJQNpAIhNqaEoneI6kiiqQ6Go/n6j0cS+a2gEU8gIHJ+BwfgZX4GL+Bd/gW34FZ+BS/gUH4FN6BTegTvoEv6BJegRnYEF2A79gOvYDl2BdEjCkqkGtwXp0LNToIskOTXzh/F062yJ7AAAAEDAWAAABWhJ+KPEIJgBFxMVP7w2QJBGHASQnOBKXKFIdUK4igKA9IEaYJg) 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<h1 class="title toc-ignore">Session 5: Self-Supervised Learning</h1>
<h4 class="author">Alexandra Strassmann, Samuel Pawel</h4>
<h4 class="date">29. April 2020</h4>
</div>
<div id="plan" class="section level2">
<h2>Plan</h2>
<ul>
<li><p><strong>Supervised learning</strong></p>
<ol style="list-style-type: decimal">
<li><p><em>Benchmark</em>: Fit a neural network to classify images on a large data set with 60000 labelled images as a benchmark</p></li>
<li><p><em>Benchmark with few labels</em>: Mimic situation where only very few labels (150 images) are available and fit same model again</p></li>
</ol></li>
<li><p><strong>Self-supervised learning</strong></p>
<ol style="list-style-type: decimal">
<li><p><em>Pretext task</em>: Perform rotation task on full, unlabelled data set (60000 images). Use random rotation of image as pseudo-label.</p></li>
<li><p><em>Downstream task with few labels</em>: Transfer weights from rotation task and try classification again with small data set (150 images)</p></li>
</ol></li>
</ul>
</div>
<div id="libraries-and-data" class="section level2">
<h2>Libraries and data</h2>
<pre class="r"><code>## Libraries
## ------------------------------------------------------------------
library(keras)
library(OpenImageR) # for rotation of images with rotateImage()
set.seed(42)
## Data
## ------------------------------------------------------------------
## loading data
mnist <- dataset_mnist()
str(mnist)</code></pre>
<pre><code>## List of 2
## $ train:List of 2
## ..$ x: int [1:60000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
## ..$ y: int [1:60000(1d)] 5 0 4 1 9 2 1 3 1 4 ...
## $ test :List of 2
## ..$ x: int [1:10000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
## ..$ y: int [1:10000(1d)] 7 2 1 0 4 1 4 9 5 9 ...</code></pre>
<pre class="r"><code>ntrain <- length(mnist$train$y)
ntest <- length(mnist$test$y)
## normalize and reshape images
mnist$train$x <- mnist$train$x / 255
mnist$train$x <- array(mnist$train$x, dim = c(ntrain, 28, 28, 1))
mnist$test$x <- mnist$test$x / 255
mnist$test$x <- array(mnist$test$x, dim = c(ntest, 28, 28, 1))
## one-hot encode labels
mnist$train$yBin <- to_categorical(mnist$train$y, 10)
mnist$test$yBin <- to_categorical(mnist$test$y, 10)
## some plots of the data
par(mfrow = c(4, 4), mai = rep(0.15, 4))
for (i in seq(1, 16)) {
image(t(apply(mnist$train$x[i,,,1], 2, rev)),
col = hcl.colors(256, palette = "inferno"),
axes = FALSE, main = mnist$train$y[i])
}</code></pre>
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" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="fitting-a-convolutional-neural-network-model-cnn-to-all-training-data" class="section level2">
<h2>Fitting a convolutional neural network model (CNN) to all training data</h2>
<pre class="r"><code>## CNN model
## ------------------------------------------------------------------
## adapted from:
## https://blog.tensorflow.org/2018/04/fashion-mnist-with-tfkeras.html
model <- keras_model_sequential(name = "MNIST-CNN") %>%
layer_conv_2d(filters = 64, kernel_size = 2, padding = "same",
activation = "relu", input_shape = c(28, 28, 1)) %>%
layer_max_pooling_2d(pool_size = 2) %>%
layer_dropout(rate = 0.3) %>%
layer_conv_2d(filters = 32, kernel_size = 2, padding = "same",
activation = "relu") %>%
layer_max_pooling_2d(pool_size = 2) %>%
layer_dropout(rate = 0.3) %>%
layer_flatten() %>%
layer_dense(units = 256, activation = "relu") %>%
layer_dropout(rate = 0.5) %>%
layer_dense(units = 10, activation = "softmax")
summary(model)</code></pre>
<pre><code>## Model: "MNIST-CNN"
## ________________________________________________________________________________
## Layer (type) Output Shape Param #
## ================================================================================
## conv2d (Conv2D) (None, 28, 28, 64) 320
## ________________________________________________________________________________
## max_pooling2d (MaxPooling2D) (None, 14, 14, 64) 0
## ________________________________________________________________________________
## dropout (Dropout) (None, 14, 14, 64) 0
## ________________________________________________________________________________
## conv2d_1 (Conv2D) (None, 14, 14, 32) 8224
## ________________________________________________________________________________
## max_pooling2d_1 (MaxPooling2D) (None, 7, 7, 32) 0
## ________________________________________________________________________________
## dropout_1 (Dropout) (None, 7, 7, 32) 0
## ________________________________________________________________________________
## flatten (Flatten) (None, 1568) 0
## ________________________________________________________________________________
## dense (Dense) (None, 256) 401664
## ________________________________________________________________________________
## dropout_2 (Dropout) (None, 256) 0
## ________________________________________________________________________________
## dense_1 (Dense) (None, 10) 2570
## ================================================================================
## Total params: 412,778
## Trainable params: 412,778
## Non-trainable params: 0
## ________________________________________________________________________________</code></pre>
<pre class="r"><code>## compile model
model %>%
compile(loss = "categorical_crossentropy",
optimizer = "adam",
metrics = c("accuracy"))
## fit model
history <- model %>%
fit(x = mnist$train$x,
y = mnist$train$yBin,
batch_size = 64,
epochs = 10,
validation_split = 0.2)
## plot change of loss/accuracy over course of optimization
plot(history)</code></pre>
<p><img 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" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>## evaluate on test data
model %>%
evaluate(x = mnist$test$x,
y = mnist$test$yBin,
verbose = 0)</code></pre>
<pre><code>## $loss
## [1] 0.02752205
##
## $accuracy
## [1] 0.9915</code></pre>
</div>
<div id="fitting-same-model-on-only-small-part-of-training-data" class="section level2">
<h2>Fitting same model on only small part of training data</h2>
<pre class="r"><code>## only taking the first 0.25% training samples to fit model
smallData <- function(perc = 0.0025) {
smallerN <- 0.0025*ntrain
ind <- sample(x = seq(1, ntrain), size = smallerN, replace = FALSE)
x <- array(mnist$train$x[ind,,,], dim = c(smallerN, 28, 28, 1))
yBin <- mnist$train$yBin[ind,]
return(list(x = x, yBin = yBin))
}
## formulating same model
modelSmall <- keras_model_sequential(name = "MNIST-CNN-Small") %>%
layer_conv_2d(filters = 64, kernel_size = 2, padding = "same",
activation = "relu", input_shape = c(28, 28, 1)) %>%
layer_max_pooling_2d(pool_size = 2) %>%
layer_dropout(rate = 0.3) %>%
layer_conv_2d(filters = 32, kernel_size = 2, padding = "same",
activation = "relu") %>%
layer_max_pooling_2d(pool_size = 2) %>%
layer_dropout(rate = 0.3) %>%
layer_flatten() %>%
layer_dense(units = 256, activation = "relu") %>%
layer_dropout(rate = 0.5) %>%
layer_dense(units = 10, activation = "softmax")
## compile model
modelSmall %>%
compile(loss = "categorical_crossentropy",
optimizer = "adam",
metrics = c("accuracy"))
## fit model M times with different small data sets and get test error
M <- 20
weightsModelSmall <- get_weights(modelSmall)
testerrSuper <- t(replicate(n = M, expr = {
## overwrite weights with initialization weights
modelSmall %>%
set_weights(weights = weightsModelSmall)
## fit to a small data set
sdat <- smallData(perc = 0.0025)
modelSmall %>%
fit(x = sdat$x,
y = sdat$yBin,
batch_size = 1,
epochs = 10,
validation_split = 0.2,
verbose = FALSE)
## get test error
testErr <- modelSmall %>%
evaluate(x = mnist$test$x,
y = mnist$test$yBin,
verbose = 0)
return(c(loss = testErr$loss, accuracy = testErr$accuracy))
}, simplify = TRUE))
par(mfrow = c(1, 2), mai = rep(0.5, 4))
boxplot(testerrSuper[,2], main = "Accuracy (%)")
stripchart(testerrSuper[,2], add = TRUE, vertical = TRUE, jitter = 0.1,
pch = 1, method = "jitter")
boxplot(testerrSuper[,1], main = "Loss")
stripchart(testerrSuper[,1], add = TRUE, vertical = TRUE, jitter = 0.1,
pch = 1, method = "jitter")</code></pre>
<p><img 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" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="self-supervised-learning-pretext-task" class="section level2">
<h2>Self-Supervised Learning: Pretext Task</h2>
<pre class="r"><code>## Pretext task
## ----------------------------------------------------------------------------
## Pseudolabel p: random rotation of image
## 0: 0°, 1: 90°, 2: 180°, 3: 270°
mnist$train$p <- sample(x = c(0, 1, 2, 3), size = ntrain, replace = TRUE)
mnist$test$p <- sample(x = c(0, 1, 2, 3), size = ntest, replace = TRUE)
mnist$train$pBin <- to_categorical(mnist$train$p)
mnist$test$pBin <- to_categorical(mnist$test$p)
## rotating image with OpenImageR::rotateImage()
mnist$train$xRot <- array(dim = c(ntrain, 28, 28, 1))
for (i in seq(1, ntrain)) {
angle <- mnist$train$p[i]*90
mnist$train$xRot[i,,,] <- rotateImage(image = mnist$train$x[i,,,],
angle = angle)
}
mnist$test$xRot <- array(dim = c(ntest, 28, 28, 1))
for (i in seq(1, ntest)) {
angle <- mnist$test$p[i]*90
mnist$test$xRot[i,,,] <- rotateImage(image = mnist$test$x[i,,,],
angle = angle)
}
## some plots of the rotated data with pseudolabels
par(mfrow = c(4, 4), mai = rep(0.15, 4))
for (i in seq(1, 16)) {
image(t(apply(mnist$train$xRot[i,,,1], 2, rev)),
col = hcl.colors(256, palette = "inferno"),
axes = FALSE,
main = paste(mnist$train$y[i], ": ", mnist$train$p[i]*90, "degrees"))
}</code></pre>
<p><img 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" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>## CNN model for rotation classification
modelRot <- keras_model_sequential(name = "MNIST-CNN-Rotation") %>%
layer_conv_2d(filters = 64, kernel_size = 2, padding = "same",
activation = "relu", input_shape = c(28, 28, 1)) %>%
layer_max_pooling_2d(pool_size = 2) %>%
layer_dropout(rate = 0.3) %>%
layer_conv_2d(filters = 32, kernel_size = 2, padding = "same",
activation = "relu") %>%
layer_max_pooling_2d(pool_size = 2) %>%
layer_dropout(rate = 0.3) %>%
layer_flatten() %>%
layer_dense(units = 256, activation = "relu") %>%
layer_dropout(rate = 0.5) %>%
layer_dense(units = 4, activation = "softmax")
## compile model
modelRot %>%
compile(loss = "categorical_crossentropy",
optimizer = "adam",
metrics = c("accuracy"))
## fit model
historyRot <- modelRot %>%
fit(x = mnist$train$xRot,
y = mnist$train$pBin,
batch_size = 64,
epochs = 10,
validation_split = 0.2)
## plot change of loss/accuracy over course of optimization
plot(historyRot)</code></pre>
<p><img src="data:image/png;base64,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" width="672" style="display: block; margin: auto;" /></p>
<pre class="r"><code>## evaluate on test data
modelRot %>%
evaluate(x = mnist$test$xRot,
y = mnist$test$pBin,
verbose = 0)</code></pre>
<pre><code>## $loss
## [1] 0.03620315
##
## $accuracy
## [1] 0.9883</code></pre>
<pre class="r"><code>## extract weights from fitted model
weights_rotation <- get_weights(modelRot)
str(weights_rotation)</code></pre>
<pre><code>## List of 8
## $ : num [1:2, 1:2, 1, 1:64] -0.2822 0.1696 0.0293 -0.2884 -0.0229 ...
## $ : num [1:64(1d)] 0.05202 -0.00654 0.01544 -0.02508 -0.02087 ...
## $ : num [1:2, 1:2, 1:64, 1:32] -0.0696 0.0999 0.1046 0.0124 -0.0138 ...
## $ : num [1:32(1d)] -0.09269 -0.08393 -0.00205 0.01039 0.00921 ...
## $ : num [1:1568, 1:256] 0.0422 0.0728 0.0294 -0.1015 -0.0918 ...
## $ : num [1:256(1d)] 0.0079 -0.0308 0.0194 -0.0485 0.0157 ...
## $ : num [1:256, 1:4] 0.20957 0.00317 0.13391 -0.0475 0.12097 ...
## $ : num [1:4(1d)] 0.0159 -0.0558 -0.0161 0.0479</code></pre>
</div>
<div id="self-supervised-learning-downstream-task" class="section level2">
<h2>Self-Supervised Learning: Downstream Task</h2>
<pre class="r"><code>## Downstream task
## ----------------------------------------------------------------------------
## CNN model for image classification
modelDown <- keras_model_sequential(name = "MNIST-CNN-Downstream") %>%
layer_conv_2d(filters = 64, kernel_size = 2, padding = "same",
activation = "relu", input_shape = c(28, 28, 1)) %>%
layer_max_pooling_2d(pool_size = 2) %>%
layer_dropout(rate = 0.3) %>%
layer_conv_2d(filters = 32, kernel_size = 2, padding = "same",
activation = "relu") %>%
layer_max_pooling_2d(pool_size = 2) %>%
layer_dropout(rate = 0.3) %>%
layer_flatten() %>%
layer_dense(units = 256, activation = "relu") %>%
layer_dropout(rate = 0.5) %>%
layer_dense(units = 10, activation = "softmax")
## take over weights from pretext task for first few layers
weights_down <- get_weights(modelDown)
weights_down[[1]] <- weights_rotation[[1]]
weights_down[[2]] <- weights_rotation[[2]]
weights_down[[3]] <- weights_rotation[[3]]
weights_down[[4]] <- weights_rotation[[4]]
weights_down[[5]] <- weights_rotation[[5]]
weights_down[[6]] <- weights_rotation[[6]]
## fit model M times with different small data sets and get test error
M <- 20
testerrSelf <- t(replicate(n = M, expr = {
## overwrite weights with initialization weights from pretext task
modelDown %>%
set_weights(weights = weights_down)
## freeze weights from convolution layers
modelDown %>%
freeze_weights(from = 1, to = 4)
# summary(modelDown)
## compile model
modelDown %>%
compile(loss = "categorical_crossentropy",
optimizer = "adam",
metrics = c("accuracy"))
## draw a small data set
sdat <- smallData(perc = 0.0025)
## calibrate parameters in last layers first ("model head")
modelDown %>%
fit(x = sdat$x,
y = sdat$yBin,
batch_size = 1,
epochs = 10,
validation_split = 0.2)
## unfreeze weights
modelDown %>%
unfreeze_weights()
## compile model again
modelDown %>%
compile(loss = "categorical_crossentropy",
optimizer = "adam",
metrics = c("accuracy"))
## fit the whole model including parameters from conv layers
modelDown %>%
fit(x = sdat$x,
y = sdat$yBin,
batch_size = 1,
epochs = 10,
validation_split = 0.2)
## evaluate on test data
testErr <- modelDown %>%
evaluate(x = mnist$test$x,
y = mnist$test$yBin,
verbose = 0)
return(c(loss = testErr$loss, accuracy = testErr$accuracy))
}, simplify = TRUE))
## Plot testerror
library(ggplot2)
library(dplyr)
library(tidyr)
rbind(data.frame(testerrSuper, method = "Supervised"),
data.frame(testerrSelf, method = "Self-supervised")) %>%
gather(key = "variable", value = "value", accuracy, loss) %>%
ggplot(aes(x = method , y = value)) +
geom_boxplot() +
geom_jitter(alpha = 0.7, width = 0.3) +
facet_wrap(~ variable, scales = "free")</code></pre>
<p><img 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" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="important-things-we-learned" class="section level2">
<h2>Important things we learned</h2>
<ul>
<li>Definition of pretext task is crucial</li>
<li>We should probably not use classification or a different loss function for a rotation task</li>
<li>First freeze transfered weights and calibrate the remaining part of the model</li>
<li>Train model again a bit afterwards (but easy to overfit!)</li>
</ul>
</div>
<div id="discussion-points" class="section level2">
<h2>Discussion points</h2>
<ul>
<li>Could self-supervised learning be used in your field?</li>
<li>How could a pretext task could look like?</li>
<li>In which other fields do you see applications?</li>
</ul>
</div>
<div id="useful-links" class="section level2">
<h2>Useful links</h2>
<ul>
<li><a href="https://github.com/jason718/awesome-self-supervised-learning">List</a> with many relevant papers from arXiv</li>
<li><a href="https://arxiv.org/pdf/1902.06162.pdf">Review</a> paper of self-supervised learning in computer vision</li>
<li><a href="https://www.youtube.com/watch?v=SaJL4SLfrcY">Talk</a> by Yann LeCun on self-supervised learning</li>
</ul>
</div>
<div id="sessioninfo" class="section level2">
<h2>SessionInfo</h2>
<pre class="r"><code>sessionInfo()</code></pre>
<pre><code>## R version 3.6.3 (2020-02-29)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 18.04.4 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=de_CH.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=de_CH.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=de_CH.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=de_CH.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] tidyr_1.0.2 dplyr_0.8.5 ggplot2_3.3.0 OpenImageR_1.1.6
## [5] keras_2.2.5.0
##
## loaded via a namespace (and not attached):
## [1] reticulate_1.14 tidyselect_1.0.0 xfun_0.12 purrr_0.3.3
## [5] splines_3.6.3 lattice_0.20-41 vctrs_0.2.4 colorspace_1.4-1
## [9] generics_0.0.2 htmltools_0.4.0 yaml_2.2.1 mgcv_1.8-31
## [13] base64enc_0.1-3 rlang_0.4.5 later_1.0.0 pillar_1.4.3
## [17] withr_2.1.2 glue_1.3.2 rappdirs_0.3.1 jpeg_0.1-8.1
## [21] lifecycle_0.2.0 tensorflow_2.0.0 stringr_1.4.0 munsell_0.5.0
## [25] gtable_0.3.0 codetools_0.2-16 evaluate_0.14 labeling_0.3
## [29] knitr_1.28 fastmap_1.0.1 httpuv_1.5.2 tfruns_1.4
## [33] Rcpp_1.0.4 xtable_1.8-4 promises_1.1.0 scales_1.1.0
## [37] jsonlite_1.6.1 mime_0.9 farver_2.0.3 png_0.1-7
## [41] digest_0.6.25 stringi_1.4.6 tiff_0.1-5 shiny_1.4.0.2
## [45] grid_3.6.3 tools_3.6.3 magrittr_1.5 tibble_2.1.3
## [49] crayon_1.3.4 whisker_0.4 pkgconfig_2.0.3 zeallot_0.1.0
## [53] ellipsis_0.3.0 Matrix_1.2-18 assertthat_0.2.1 rmarkdown_2.1
## [57] R6_2.4.1 nlme_3.1-144 compiler_3.6.3</code></pre>
</div>
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