一、前向计算和反向传播数学过程讲解
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90XNR8MfvTeaJM1ndZ3FQx2uf6VFZ+KJLSVbTxFbvay9BNj5X9+P6V01QXllbX8Biu4UlQgj5hnGe49DRcduxKjrIgeNldT0KnINOrl30bUNA3TaDLJPCGybWQ5BGOfT0H+Rzf0vxLaaiRFKDa3JOPKkPU+xosFzZooopDCiiigAooooAKKKKACiiigAooooAxNU8W6VpTMksxllQ4aOMZI/pU+ieIbLXopGsvMUx43LIuCM1g6TY258c6rbzQRzx7fNBkQNtOR6/7xrrYLW3tVK20EcKk5IjQLk/hTdiVdktFFNlljgjaSZ1jRerMcAUih1FIjrIiujBlYZBHcUtABRRRQAUUUUAFFFFABVAaJpo1A3v2OP7QTnfjv646VfooAxdb0HSNSmSbUiIpAMbxIELD3z1rVtkhitkjtdvlIoVQpyAKo6roFlrLI14JNyDAKNisW48KXemg3GgX8qunPkyMcOB2yKZOx1tI6LJGyOMqwIIPcVkeGtZbWtMMkyhJ4n8uQDuR3x2zWxSK3OO1Dw7JYT6OtgGmSC4ZmLDpkqf6V2NFFO4krBRRRSGFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFcxeTXPiLUbrTbYmC3tjiSQN940CbOiN1AJhEZ4xI3RC4yfwqWuasPBNlaXaXU0sk0yNu56E5B/p2xXS0ArhRRRQMKgvLG21C3MF5CssZ7MOn09KnooA5seA9EEgYxzEA52mTit+1tYLK3WC1iWKJRgKoqWincVkgooopDCiiigApFdXGUYMPY5pSMgg1zV14RPnNPpupT20pO4Z5Gfr2FAmdLRXGXeo+IfDXlS6hNFeWhcITwCSefr2NdjG4liRwCAyggH3pgncdRRRSGFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAEf2eH/nlH/wB8is7xDBEPDGqERICLObBCj+4a1azvEX/Ir6r/ANec3/oBpTb5Wa4dL20PVfmXfs8P/PKP/vkUfZ4f+eUf/fIqSiquzHlRH9nh/wCeUf8A3yKiu4IRZTkRqv7tuQoyOKs1Hc/8esuOfkPf2ouw5Uc34Fhifw+5aND/AKQ3JX2FdJ9nh/55R/8AfIrn/ApB8OHBJ/fvnPbpWzqt7/Z2lXF3gExJkA+vQU23cSSsT/Z4f+eUf/fIo+zw/wDPKP8A75Fcfa6l4tmsRerDC0O0vtIALDrwOtdJomqrrGlR3YTYxyrrnow60agrPoXPs8P/ADyj/wC+RR9nh/55R/8AfIqSildj5UR/Z4f+eUf/AHyKPs8P/PKP/vkVJRRdhyoyE1nR3vzZ741lBxhkwD+Naf2eH/nlH/3yKzNa0Cz1GxlxBGlwFLJKq4O73wOaZ4TvpL/w/E83Lxkxls/ex3p3YrK+xrfZ4f8AnlH/AN8ij7PD/wA8o/8AvkVJRSux8qI/s8P/ADyj/wC+RR9nh/55R/8AfIqSs7WNPutQt0Syv3s2VslkH3qLsLLsXfs8P/PKP/vkVj67qDaMIpk05bi2P+sZV5X9KoHwZczhftmu3UuMkDnAJ69TXS29ssFmtuWMiqu0l+c07k2v0K+nXNjqlkl1aIjRt6oAQfQ1a+zw/wDPKP8A75Fcx4RX7Jq2sWMe4wRTZTJ6ckV1dDbGkmtiP7PD/wA8o/8AvkVy/jW3VF02ZEjQJcgE8A84/Dt3rrK5Xx6p/su1kDFQlwMke4NCbuDSsdN9nh/55R/98ij7PD/zyj/75FSA5AI6GildjsiP7PD/AM8o/wDvkUfZ4f8AnlH/AN8ipKKLsOVEf2eH/nlH/wB8ij7PD/zyj/75FSUUXYcqI/s8P/PKP/vkUfZ4f+eUf/fIqSii7DlRH9nh/wCeUf8A3yKPs8P/ADyj/wC+RUlFF2HKiP7PD/zyj/75Fcp41jSOfSCke3/SDnYvP8PpXX1yXjkFpNJVRybj72CcdKabuTJKx1P2eH/nlH/3yKPs8P8Azyj/AO+RUlU9V1BdL0ua8ddwjGcZxk9KV2VZFj7PD/zyj/75FH2eH/nlH/3yK5yLx5pJWISmXcygsyplVPp610dvcRXduk9tIskTjKsvenditFh9nh/55R/98ij7PD/zyj/75FSUUrsfKiP7PD/zyj/75FRz/ZLWEy3CxRoOrFRViorm2hu7d4LmNZInGGVu9F2HKhsK2lxEssCwyI3RkAINP+zw/wDPKP8A75FcgbZvCviazisZWNlfNtaJjnbz/wDXrs6d2JJdiP7PD/zyj/75FH2eH/nlH/3yKkpssiQxNJKwVFGWJ7Cldjshv2eH/nlH/wB8ij7PD/zyj/75FYc3jbRImwLh5B6pGf61Np/izS9TuFhtnkEjdA8ZFP3he6Wjf6UL77G0kC3H/PNlwaufZ4f+eUf/AHyK57xho9pNpM9+I1S6gAdZBwTzjBrW0K7kvtCtLmb/AFkkYLe56Zouwsr2sW/s8P8Azyj/AO+RR9nh/wCeUf8A3yKkopXY+VEf2eH/AJ5R/wDfIo+zw/8APKP/AL5FSUUXYcqI/s8P/PKP/vkUfZ4f+eUf/fIqSuRuPE2sT69dafo1hFP5BIJc46dTnIFO7E0kdV9nh/55R/8AfIo+zw/88o/++RWJo3iOW71F9M1W1+yXyjIUH5X+n8636V2CSZH9nh/55R/98iuT8IxRtrmuZRGVZ8AYyBy1dhXK+ECTq+vEjH+k8DGCOWp3YNK5032eH/nlH/3yKPs8P/PKP/vkVJRSux8qI/s8P/PKP/vkVm6n4b0/U13NEIZh92WMYI+vrWtRRdhyo5ET6j4bIXVLdb2y3BROgBZf6/nxXQWF1p+p2/nWflSL3G0ZU+4q8QGBBGQeoNc7qHhgrO15oU5s7rqVB+RvX6U7snlSN77PD/zyj/75FH2eH/nlH/3yK52z8US2lwLPxDCbeXO1Zgp2v7//AFx610qOsiB42DKwyCDkGldjSixn2eH/AJ5R/wDfIo+zw/8APKP/AL5FSUUXY+VEf2eH/nlH/wB8ij7PD/zyj/75FSUUXYcqI/s8P/PKP/vkUfZ4f+eUf/fIqSii7DlRH9nh/wCeUf8A3yKPs8P/ADyj/wC+RUlFF2HKjlNNtkX4hampVSvkKwGOBnbXT/Z4f+eUf/fIrmNP4+I+ohnbmAEA/wDAfeurptsSSI/s8P8Azyj/AO+RXIeIEGs+JrXQ4FVIE/eXBVcHpnr9Onua7OuQ0OVP+Ez1u4uJI18v5NzMBgbsd/oKE2JpHUQ2VtBCkUUCBEUKo254p/2eH/nlH/3yKWKaKeMSQSJIh6MjAj8xT6V2VZEf2eH/AJ5R/wDfIo+zw/8APKP/AL5FSUUXYcqI/s8P/PKP/vkUfZ4f+eUf/fIqSii7DlRBOLW3geadI0jQZZio4FJALW5gSaBI3jcZVgo5rJ8ZyPH4Yn2ZG5lViOwz/wDWrJtPBsw06G4sdXmSd4lZeoXkA49qd3bcmyvsdh9nh/55R/8AfIo+zw/88o/++RWH4a1e5uJJtN1QEXtr1JH3l+vc+/vXQUrsaSZH9nh/55R/98io7iOKK1lkEMeUQsPlHYVYqG8OLGfDbT5bfN6cdaLsdkc14Dhik0OaV41ZnuGzlR6D/Gun+zw/88o/++RXO+As/wDCNnP/AD3fHHsK6am27iSViP7PD/zyj/75FH2eH/nlH/3yKkopXY+VEf2eH/nlH/3yKPs8P/PKP/vkVJRRdhyoj+zw/wDPKP8A75FH2eH/AJ5R/wDfIqSii7DlRH9nh/55R/8AfIo+zw/88o/++RUlFF2HKiP7PD/zyj/75FH2eH/nlH/3yKkoouw5UR/Z4f8AnlH/AN8ij7PD/wA8o/8AvkVJRRdhyoj+zw/88o/++RR9nh/55R/98ipKMjOM80XYWRH9nh/55R/98ij7PD/zyj/75FSUUXYcqI/s8P8Azyj/AO+RXMeDo4J5NUmCBw1xwWUe/eupkbZEznooJrnPAwzos7n+K5c5554FO7sKyudD9nh/55R/98iq2oFbOwlnhshcOgyI0UZartFK7Hyo46HxzpYYrfadLbMD02Bvz6V0tjNYajaLc2YiliboQv6VneMZYoPDdxI8MckhHloXUHGev6Zqbwtp66d4dtowSWlUSvz3YCnfQlLWxp/Z4f8AnlH/AN8ij7PD/wA8o/8AvkVJRSuyuVEf2eH/AJ5R/wDfIo+zw/8APKP/AL5FSUUXYcqI/s8P/PKP/vkUfZ4f+eUf/fIqSii7DlRC8UEcbO0SBVBJ+UdKqaTd2urWAuobdVUsVwVHaptVfy9HvH5+WBzx/umsnwOm3wvCcY3uzfrTu7Csrm79nh/55R/98ij7PD/zyj/75FSUUrsfKjkfG6J/xLIFRFWW4+bCjtj/ABNdV9nh/wCeMf8A3yK5rxkVF7ovmcr9q55+naupp3diUlcj+zw/88o/++RR9nh/55R/98ipKKV2Vyoj+zw/88o/++RR9nh/55R/98ipKKLsOVEf2eH/AJ5R/wDfIo+zw/8APKP/AL5FSUUXYcqI/s8P/PKP/vkUfZ4f+eUf/fIqSii7DlRH9nh/55R/98ij7PD/AM8o/wDvkVJRRdhyoj+zw/8APKP/AL5FH2eH/nlH/wB8ipKKLsOVEf2eH/nlH/3yKPs8P/PKP/vkVJRRdhyoj+zw/wDPKP8A75FH2eH/AJ5R/wDfIqSii7DlRH9nh/55R/8AfIo+zw/88o/++RUlFF2HKiP7PD/zyj/75FH2eH/nlH/3yKkoouw5UR/Z4f8AnlH/AN8ij7PD/wA8o/8AvkVJRRdhyoj+zw/88o/++RR9nh/55R/98ipKKLsOVEf2eH/nlH/3yKPs8P8Azyj/AO+RUlFF2HKiP7PD/wA8o/8AvkUfZ4f+eUf/AHyKkoouw5UR/Z4f+eUf/fIo+zw/88o/++RUlFF2HKiP7PD/AM8o/wDvkUfZ4f8AnlH/AN8ipKKLsOVEf2eH/nlH/wB8iipKKLsOVBWd4i/5FfVf+vOb/wBANaNZ3iL/AJFfVf8Arzm/9ANRP4Wb4f8AjQ9V+Zo0UUVRiFRXX/HnNyB+7bknGOKlqO4i8+1liDbTIhXcO2RjNAHP+BWLeHTnB/ftzj6da2dUs/t+lXFqDgyIQPr2/WuasfDWv2EYhttVjih3ZIXOeevVa6bTree1sI4rqc3EoHzSHuabJW1jmbHxFBaeGJ7a9crd20bRhH6v2U/rj8K0/BsDQeGYC4wZWMmMY9v6VcudA0u8ujc3FnG8p6tzz9a0FUIoVAFVRgADAAouCTFooopFBRRRQBzfifxElip021Ia8nXaSWwIge5NWfDy2mlaLDaveW5lyTJiVT8x7fyqbUfDWlarMZry23TEAeYrEH/Cs5vAOikcC4H0k/8ArU9LE63OkjljmQPE6up6MpyKdXOWPgu003Uobuyu7lPLOSjMDu9uMcV0dIauFFFFAwrnfEfiuHRy9pCC14yZXK/KpPTPvXRVTvtIsNSIN9axzMvRiOR+NNCd+hz/AISuNMsbJmm1GB7y5bzJSz4x7ZOM/wCNdRHcQygGKWNwehVgf89axpPBehSDiy2H1WRv8apP8PtL24hnuo+ecODn9KNGJXR1Vcx4+/5F1Ocf6Qn8jWz/AGc8Oi/YbO5kjdU2pMxywPrXM3nhTXbmNbebV/tNuzhm8wkkfnQgd7HX2zFrSFickopJP0qWo4I/Jt44s52IFz64FSUigooooAKKKKACiiigAooooAK5Pxp81/osYxua4OM/Va6yuU8VAP4k0FW/579cf7S01uKWx1dZniOzN94dvIFGSY9wHqRz/StOikM5Twqml3fhT99bQnyQyzlkGeMnOevT+VL4CMjaXcsNwtTMfIDdQMc/0/HNM1HwZNJfSyaVe/ZILn/XRcgH6AV0Wl6fHpWmw2cPKxjBbABY9zVMhJ3LdFFFSWFQ3V1DZWslzcvsijGWb0qamTQx3MDwzoHjcbWU9CKAPPW8Q2et+KLe8vJvslhZnMYcElznjgA8n+QrqU8ZaFJKEW95PQmNgP5VMnhfRY2BXToTt6bgW/nU66FpSsGXT7YEdD5YqtCUmXlYMoZTkEZBpJI0ljaORQyMMFSODSgBVAUAAcADtS1JRUXSdOTG2wthj0hX/CpI7K1ifdFbQow7rGAanooA47x1f3Uaw2XlSJZy4aWZBnPP3cfrirGm+MNCgsoLcPNAkaBAZI/Qe2a6ggMMMAR6Gqk+kadc58+xt3JGCTGM/nTuibO9xllrem6g+yzvYpX/ALoOD+Rq/WPB4V0i1vku7a18uVDkYY4/I1sUhq/UKKKKBhXJaXIun+PNRtp8Ibv54/8Aa7/411tY3iDQP7XSOa2mNtewcxTA4/A45poTMrWAD8RtK2g7vKyccZGWrrq5rR/D1+msDU9cu1uJ402RBew6Z/z610tDBBXJeCv+QhrXy4/0gfzautrkvBjD+09aXuJxnI5zlvzo6Ce6OtooopFBRRRQAUUUUAQ3dnb30DQ3USyoR0YVzb6TqugOZtElN1bfxW0nJx7V1VFMTVzI0zxJY6iwhZjb3Y4eCUYKt3HvWvWXq2gWerjdKDHOPuzJ94Vkpe6t4ck8rUY3vrLPE6dVH+e1AXa3OqoqtY6ha6lbiazlEiH8x9RVabWYoNcj02aNlaVdySdifT9KQzSooooAKKKKAOUtnx8TrxScbrcDGP8AZU11dclGT/wtCXGf9QM/98CutpslBXneuaZZWnjZpNZeYWN2vmB1J+U9wePUduxFeiVXu7C1v4wl7bxzKOgdc4oTsNq5ynggg6pqQsDJ/ZqnEW4d88fpXZ1FbWsFnCIbSFIYx/Ci4FS0MErIKKKKQwooooAq6lYx6lp01pN92VcZ9D1B/OuX07xJJoETabrtvKDb/LHJGoO5QOBjj8/euyqOSCGZlaWJHKHKllB2n2piaOa8OJLqevXeuyRGKGVAkSsDk8AZ9+ldTR0opAlYKgvgTp1yBjJibGfoanpHQSRsjdGBBoGc34DyfDhJHWd/6V0tcr4DJj069tiT+5uTwRyMj/61dVTe4o7BRRRSGFUL3W9P06byry4ET4zgqT/Sr9V7iwtLvm5topT6ugJoAzx4s0Q4/wBOUf8AAW/wp3/CU6LnH2+P16H/AAqydG00jBsbcj/rmKYdB0o9bCA/VAaegtSJfE2jMpI1CLA9cj+lKviXR2UkahFgfWn/APCP6Vlj9hh+brx/nFIfD2ksxZrGIlupIzn3+tGgaiHxFpAJBv4sj3p413Syuft0OP8AeqI+GdGJz9gj65xk4/LND+GNGkbLWEY6fdyOn0NGgalj+2dN5zfQDHq4FC6xprdL+2/7+iqn/CKaLx/oK8f7bf40h8J6Kf8AlzA7ffb/ABo0DUvjVLBvu31ufpKv+NZWsw2uoNHPa6zDa3Ef3WEq4P15qX/hEtF/58x0x94msrVNM8OaMu2ZJjK5ykUbksT2+lGgnfqPg8UzaZKINZaK4jyAt1bkEHj0FdJZaha6hEZLKdJlHB2nlfqO1cJD4Yn1phJBZLp9q3eRyzNz6fT8OK67QfD9roFvJHas7tKQXZz1x047dabsCuXdQfy9NuX4G2Fzz06GsbwQhTwyjMc75Hbrnvj+laOvyeV4evmJx+5YfmMVV8ILt8K2WepVieP9o0ugdTaooopFHLfEHP8AwjsQHQ3K59+GrpLRdllAgBULGowRgjiud8eQy3GiwRQRtIxuFOFUnsf8a6WJPLhRP7qgU+hPUdRRRSKCiiigAooooAyvE7+X4Yv26/uiPzOKZ4TTZ4VsQf7hPT1JNS+I7V7zw5ewRqWZo8gDqcHP9KTwyjR+GrJHDBljwQw56mn0F1NSiiikM5Xx6CmmWc3aO6XOQPQ/4V1EciyxJJGdyOoZSO4NY/i+LzfC91jduQK67T0ORVnw9c/a/D1lMepiAP4cf0p9Cepo0UUUigooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKzvEX/Ir6r/15zf8AoBq79nh/55R/98is7xDBEPDGqERICLObBCj+4aU7crNcPf20PVfmatFR/Z4f+eUf/fIo+zw/88o/++RVaGOpJRUf2eH/AJ5R/wDfIo+zw/8APKP/AL5FGgaklFR/Z4f+eUf/AHyKPs8P/PKP/vkUaBqSUVH9nh/55R/98ij7PD/zyj/75FGgaklFR/Z4f+eUf/fIo+zw/wDPKP8A75FGgaklFR/Z4f8AnlH/AN8ij7PD/wA8o/8AvkUaBqSUVH9nh/55R/8AfIo+zw/88o/++RRoGpJRUf2eH/nlH/3yKPs8P/PKP/vkUaBqSUVH9nh/55R/98ij7PD/AM8o/wDvkUaBqSUVH9nh/wCeUf8A3yKPs8P/ADyj/wC+RRoGpJRUf2eH/nlH/wB8ij7PD/zyj/75FGgaklFR/Z4f+eUf/fIo+zw/88o/++RRoGpJRUf2eH/nlH/3yKPs8P8Azyj/AO+RRoGpJRUf2eH/AJ5R/wDfIo+zw/8APKP/AL5FGgaklFR/Z4f+eUf/AHyKPs8P/PKP/vkUaBqSUVH9nh/55R/98ij7PD/zyj/75FGgaklFR/Z4f+eUf/fIo+zw/wDPKP8A75FGgaklcp4oA/4SbQTwSZxwf94f4/pXT/Z4f+eUf/fIrlfE8MY8TaEFjUAzcjAAPzCmrEu9jrqKj+zw/wDPKP8A75FH2eH/AJ5R/wDfIpaFaklFR/Z4f+eUf/fIo+zw/wDPKP8A75FGgaklFR/Z4f8AnlH/AN8ij7PD/wA8o/8AvkUaBqSUVH9nh/55R/8AfIo+zw/88o/++RRoGpJRUfkQ/wDPKP8A75FH2eH/AJ5R/wDfIo0DUkoqP7PD/wA8o/8AvkUfZ4f+eUf/AHyKNA1JKKj+zw/88o/++RR9nh/55R/98ijQNSSiuW1PV71NVltdH0yG5W3GZcpk/pWhoerWOtQNsgSK4j/1sLKMr/8AWp2Qrs2aKj+zw/8APKP/AL5FH2eH/nlH/wB8iloPUkoqP7PD/wA8o/8AvkUfZ4f+eUf/AHyKNA1JKKjMEAGTFGB7qKjT7HI+2PyGb0XBNGgaliio/s8P/PKP/vkUfZ4f+eUf/fIo0DUkrkvCo2eKdfTj/XE/+PGup+zw/wDPKP8A75FcnoEMY8b60hjQryQMD+9T0Jd7o7Cio/s8P/PKP/vkUfZ4f+eUf/fIpaFaklFR/Z4f+eUf/fIo+zw/88o/++RRoGpJRUf2eH/nlH/3yKPs8P8Azyj/AO+RRoGpJRUf2eH/AJ5R/wDfIo+zw/8APKP/AL5FGgaklIyhlKsAQRggjrTPs8P/ADyj/wC+RR9nh/55R/8AfIo0DUwL/wALbJ2vdDnayucE7F+4x9PasjV7+a7gS11y3ayvIW3Q3IB2vg8jj19Rx9K6HVfD/wDaEySQXklptGCsY4P6isq58G3k6bDqpkTHIkjzzVaENPsbPh7Vl1bTFZmzPFhJRkHn149f8a1a5HQPB91o2sfaJLqKW3KFWj2klvTrXVfZ4f8AnlH/AN8ip0KVySio/s8P/PKP/vkUfZ4f+eUf/fIo0HqcvD/yVCfAJ/0cZ54HyrXWVx6RRn4nOpiTAt+AFGPujk11n2eH/nlH/wB8im7Eq5JRUf2eH/nlH/3yKqXV7pdlMsV3JBC7dA4ApaFal+iolht3UMkcbKRkEKCDS/Z4f+eUf/fIo0DUkoqP7PD/AM8o/wDvkUfZ4f8AnlH/AN8ijQNSSio/s8P/ADyj/wC+RR9nh/55R/8AfIo0DUkoqP7PD/zyj/75FRXWnwXVrJAyBA643IACPejQNSzRXD3B1HwjNG0+L/TWbBZlG5PbPauxhW1uIEmhSNkkUMpCjkGnZCTbJ6Kj+zw/88o/++RR9nh/55R/98iloPU5X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o8b9Rthnv5oNQP4o0WNQW1GHn0yf5VUTwdpKKFGnoRnPNw/JqVPCmkxsCulW/BzzIx/mKLILsZJ410KMcXZf/djNV28f6Mp4+0N/ux9f1rTj0LT4jlNKs8+4z/NagEtimsjS00+1EuzfwAB/wCg0WC7M1viFYkfurO6Y9twAyfwzTT4+UnEek3LNn1H+FdSqMn3IIV+jY/pVGLXbebV5NNj2m4j+8Nxx9M4osF/MxB43un4i0G4Y47OT/7LTm8W6qWxH4duOeRkk5H4Dn8K6nM3/POP/vs/4Ubpv+ecf/fZ/wAKA17nKt4o17jb4dmGR3DHn8qQeJ/EPGfDkvXn5Wrq903/ADzj/wC+z/hRum/55x/99n/CgDD0fV9bvb/y7/Sfs0GD85yCPzroKj3Tf884/wDvs/4Ubpv+ecf/AH2f8KVhpklFR7pv+ecf/fZ/wo3Tf884/wDvs/4UWHdHPS/8lEg4/wCXY9/Y8/0rpa5aUyD4iQfKoY254ycHg98V0u6b/nnH/wB9n/Cm0JMkoqPdN/zzj/77P+FG6b/nnH/32f8AClYd0SUVHum/55x/99n/AAo3Tf8APOP/AL7P+FFguiSmuxWNmVdxAyAO9N3Tf884/wDvs/4Ubpv+ecf/AH2f8KLBc5q48Tau0myw0KZmBwTIDjr9B/OomuvGd5kw2sFopHGdpP6k11W6b/nnH/32f8KN03/POP8A77P+FMk5U6F4puG3XGuCLI6REjH5AU0eBrkks+u3BJB6rn+tdZum/wCecf8A32f8KyNYk8QRyo+kQ28kYGWRmyT+eKNQ0Ms+BZCu3+27rH0P+NIfATk5OtXJb12//XqS28Zyw3It9csGsnJwJGyE/ka6dJJJEV41iZWGVYSZBHr0o1D3TlB4CbPOs3H/AHz/APXpD4AOQw1i43g53Fe/511u6b/nnH/32f8ACjdN/wA84/8Avs/4UahaJFp9obHT4bYytMYl2736mrNR7pv+ecf/AH2f8KN03/POP/vs/wCFKxV0SUVHum/55x/99n/CjdN/zzj/AO+z/hRYLokoqPdN/wA84/8Avs/4Ubpv+ecf/fZ/wosF0SUVHum/55x/99n/AAo3Tf8APOP/AL7P+FFguiSio903/POP/vs/4Ubpv+ecf/fZ/wAKLBdElFR7pv8AnnH/AN9n/CjdN/zzj/77P+FFguiSio903/POP/vs/wCFG6b/AJ5x/wDfZ/wosF0SUVHum/55x/8AfZ/wo3Tf884/++z/AIUWC6JKKj3Tf884/wDvs/4Ubpv+ecf/AH2f8KLBdElFR7pv+ecf/fZ/wo3Tf884/wDvs/4UWC6JKKj3Tf8APOP/AL7P+FG6b/nnH/32f8KLBdElFR7pv+ecf/fZ/wAKN03/ADzj/wC+z/hRYLokoqPdN2jj/wC+z/hXC21tqviTXNQgvb94YraUAxRsQByRgfhRYTkd4kscozG6uPVTmm3FxFaW7zTtsjQZYmuHvdMbwrq+nXFhK7CeTy3ieXO/17Djn867aRHmjaOWCJ0YYKs2Qf0p2BSILDWLDVNwsLpJin3gMgj8DV2uF8R6fHoF9ZX+mRrayNJtKxvkHp2wPxrtt03/ADzj/wC+z/hRYFLuZPiDxJDoPkKyeZJK+Nueg9aePFOiFgo1CMk8YAP+FYHj6FZP7OaaBSzSlcqxJI446VuReGNLhcPHpduGByCZGP8AMUW0FzO5sqwdQynIIyDS1EPNVQFjjAAwAHPH6Uu6b/nnH/32f8KVirklc14fB/4SjWzg48wD9TXQ7pv+ecf/AH2f8K5nw+XPijWiiID5nI3Hrk5/lTsJvU6qio903/POP/vs/wCFG6b/AJ5x/wDfZ/wpWHdElY+ueJLTRPKSU+ZNIwAjVhkD1PpWpum/55x/99n/AArkNYsYp/H+nmeKMl49xUsSGIzjt7fSmkJy7GpZ+M9Ju7hId8kLPwDKmFz9c1v1zvirTUuNAncwQxPEA4kU4Ix+HoTV7Qrqa70GzmKoxaIAkyZzjj09qLAn3NSio903/POP/vs/4Ubpv+ecf/fZ/wAKVh3RFDf2095NaxSbpoRl1x0qzXA+IYr7S/ExniuvsUOoAKZk52njOe/XH4VpW/h/xB50clzrjOqsCVR25H5U+UnmOsoqMGYDlEPvvP8AhRum/wCecf8A32f8KVirokoqPdN/zzj/AO+z/hRum/55x/8AfZ/wosF0SUVHum/55x/99n/CjdN/zzj/AO+z/hRYLokoqPdN/wA84/8Avs/4Ubpv+ecf/fZ/wosF0SUVHum/55x/99n/AAo3Tf8APOP/AL7P+FFguiSio903/POP/vs/4Ubpv+ecf/fZ/wAKLBdElFR7pv8AnnH/AN9n/CjdN/zzj/77P+FFguiSio903/POP/vs/wCFG6b/AJ5x/wDfZ/wosF0SUVHum/55x/8AfZ/woosF0SVneIv+RX1X/rzm/wDQDWjWd4i/5FfVf+vOb/0A1E/hZvh/40PVfmaNFFFUYhRRRQAUUUUAFFFFABUF3e29jCZbuVYo/wC81T1DdWdvfQ+VdxLKnoaAMtvF+hhWIv1YqCcBG5x+FVT470cdDOzegj/+vitSPQtLiIKWEGQc5KZJP49asJYWcf8Aq7SBfpGBT0J1OVnuIm8f6XeRghbqAgblwf4hzXZVy3iZPJ8QaJcZARZtpz2GRXU0MEFFFFIoKKKKACiikdlRGdzhVGST2FAGZr8OntpFxJqSR7BGcOwG4HHGD61R8D+b/wAIynnbtvmN5e4fw/8A681gXWqweKNVxeXcdppVs2djN80h9cf/AK8V00Xibw/bwiKG+hSONeFVTgD24quhF1e5t0VQstc03UZfKsrtJXxnaAR/Or9SWFc5c8/EK03EcWx2jPPRvb+ddHXN3Ib/AIWFZ4PH2Y5A+jU0JnSUUUUhhWP4sOPCt9/uDp/vCtisrxPE0/hq8jRSzMowB/vCmtxPYXwyFHhmw2cjygemK1KzfD0bReHbJJF2ssQyMYxWlSBbBRRRQMKKKKAOR8DP5C6paSHaYJ8nJ6dQeO33aPDkg1Lxhq2pJ80agRIwOARnjj6LS6p4X1JtWurrR7uOGO9XbMrdeev51vaLpUejaXHaRHcR8zsf4mPU1TISexfoooqSwooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACisy18QWF1eyWiyGOdG27ZBjJ9j0rToAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACsHXPDz390l/p0/2a+jXCt0DVvUUC3OSHiLWtLUjWdKeVEODPD39/SsTSPFNja+JdRv7mKYLcfcRUBI5zzzXpFcf4dgjbxlrpYIw3kbSM5+b/wCtVEtO5o6f4st9Vvkt7K0uGU/ekZcBa36akaRrtjVUX0UYp1SUFFFFAwooooAKKKKAOXmOPiRbjOM2569/lP8AhXUVzUxY/EW3BwALY4568GulpsSCiiikMKKKKACiiigAooooAKKKo6zBfXOlSxaXOILlsbXJxj157UAUfE15o8WnvBq+2Qsp2RLy+fUen1qt4EjuY/D+LkOqGQmIP/dwOlc7D4W8S2159paO3upc/fmdX/H5q1QfHIP3bcg/w/JharoRfW52VFcgh8cFwGFso7sdldFpQ1AWK/2sUNx32DilYpO5dooopDCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKz9S1q00l4lvCy+aeCFyBVu3uoLuISW0qSp6qc0AS0UUUAFFFFABXG6feW+keONUjv5BAs43xs7fKe9dlVDUdF0/VSpvrZZWUYDZIP5imhNHOi7XxR4utjZ7jZ6c28yY+Vz1z+ePX8K6XUtVtdKs5Li7kwsYBKryxz04qW0s7extxDaRLHGvQD/Gqc/h7T7m8nuLiJpDcLtkRmO09Py6UCszkbXVbbX/ESajq9zDb2lsT9ngc8tzwSOfbNd5b3MN1H5ltKkqZxuRsjNZS+D9CU5Gnp9C7Eflmr8NhFp9k0OmRJFxlVJJGaHYEmtzH8b2TXGhC4iBMlo4kGPToa1dG1FNV0mC6jbcWUB/Zh1GO1ZFxrmrwF4LjQnnJ+XMeSjfoazvCllqdvrk0q2stnYSAl45eQT2x0/On0C+p21FFFSUFc14eDL4m1sFgQZc49OT/jXS1zPh4bfFGuDGB5uefqaYnujpqKKKQwrlvGAaxudP1iNS32aTa4PTB5/wAa6mo7i3iu7d4LhBJFIMMp7imhNXRyvibXIr/TbfT9KcTzagV4U/dX0Pof/r10mmWY0/S7e0Bz5UYUn1Pf9apab4Y0zSro3FrC3m9AzsTtHtWvQCT3ZQttas7rVZ9OjdvtEH3gVwD64NX6jFvCsxmWJBK3Vwo3H8ac7rHGXchVUZJPakMo63pUesaXLavgORmNj/C3asnwjq8kkT6TqOUvLQ7QG/iUf4V0P2qD7OJ/OQREZDlgB+dcjbzw6r8RUutMy0UMRE0oBwxwR/UCmtiXudnRRRSKCiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKzvEX/Ir6r/15zf8AoBrRrO8Rf8ivqv8A15zf+gGpn8LNsP8Axoeq/M0aKKKoxCiiigAooooAKKKKACiiigAooooAhntYbnYZ0D+W25c9jWe/ijRkkKPfIGBwRtb/AArWqk+j6c+d9jASSTnyxQLXoVD4r0Udb5f++G/wpT4q0YYzerycfcb/AAqz/YumbcCxgA9kFA0XTRnFjBz/ALAp6BqVh4q0Uru+3Jj/AHT/AIUHxVooxm+UZ/2G/wAKsjRdMGMWMHByP3Ypf7G03GPsFv0xxGKNA1KzeKdFXrfp+Csf6Ux/FGhvG6NeI6kbWGxsEH8Kt/2Lpg/5cLf/AL9ig6JpbdbC3/79ijQNTmFs/BCSFyyOSeFZn49sVMv/AAhP3VSA54Hyuc10J0bTSebGDP8AuCg6JphH/HjB/wB8Ci4rGNY33hPTZTJZvDFIR97a5P6itD/hKtFyP9OTHrtb/CrR0fTj1sYPwjAo/sbTQQRYwZHQ7B65o0DUqHxXoo63y/8AfLHH6VhT69pp8c210l4hgWAqz4OAcHjpXTnRdMIANhb4H/TMf5Nc4+k6fB46tbeO0iMRgYlCuQDgn/OaasDubX/CU6Nn/j+T/vk/4UHxXogxm/Tn/Yb/AAqz/Ymlhs/YLfP/AFzFH9i6bz/oMBz1zGDmloPUrDxXopz/AKcvH+w3+FB8U6MODfL/AN8N/hVk6Lpp62UP/fAo/sTTM/8AHjB1z9wUaBqVh4p0YEL9tQEnAG1v8KX/AISnRdxH29OP9lv8Ksf2LpmQfsFvn/rmPTFB0XTDj/QLfjoPLHFGgalf/hKdFxn7emP91v8ACk/4SrRf+f5PxVv8Ktf2NpvGbC3OP+mQpBoumK2RYW4P/XMUaBqVf+Er0Xj/AE5ef9hv8KUeKtFPS9H/AH7b/CrI0XTAciwt/wDv2KDoumdTYwf98CjQNSsPFWik4+3L+KMP6Uv/AAlGjbyovkJ9lP8AhWHe6/4bgvHt7fTftc0Zx+6hG3P1/wDrVc0K90LWWaKPT4YLlMkwyRjP1HFOwrnSo6yRq6HKsAQfUUtAAUAAYA4AHaipKCiiigArD1HxPHp961u1lcSFejKvB+lblFAjmf8AhNIst/xLrrj0FCeNI2Zs6Ze4Az8qZ47k+ldNRT0CzObfxlFtUxaddvkZIK4x/nimHxpGMj+zLvI6gjoa6eijQLM5Y+Nl7aXcn/P0qRvGOCR/ZV5ntlevP0rpaKNAszmT4xy3yaTdkepGOPyoHjFiuf7Iu85xgD/61dNRRoFmc1/wmBwT/Y97wSCdvA9Pxp0vi1kZtmkXjBRlty4I4HX+VdHRRoFmcz/wmDlsLo92fTI/+t9KQeMJSwH9i3eM49/yxXT0UaBZ9zh9Vv4NU+abQryO56JMgIZT27etUtG8WalZXy2MsMl7GWChWzvTnGM/SuiurPWtZunink+wWSkjEbfM/wCVa2m6PZaVEVs4QpI+ZzyzfU07omzuXaKKKksKKKKACiiigAooooARjtUkDJAzgd659/E12khUaLcsASMjIH5lcV0NFAjm28U3asQ2hXY4z/nij/hKL0KC+g3ajGS3bp9K6SimFmc03im8QDdoVzyeMHOf0pP+EsvRndoF1kdQCeB+VdNRRoFn3Ob/AOEovsj/AIkN1zn1P9KZ/wAJZdlQRoV11+YnIA/SunpAQSQCCR1o0CzOdHie9P8AzArrpnuP5is+01N7G/vLyHQrwy3LZYE9/wAuOtdnRRcLM5v/AISi9H3tBul+p/rimHxXfKwU6DclsZIDH8/u109FGgWfc5lfFV6emgXR4zwf/rU4+KL0ZJ0C8Cj65/lXSUUaBZ9zmT4su/4dDusY6nPX8vrT/wDhJ73bn+wLz+v5Yro6KNAszm/+EpvCONCu8+4OP5UHxTeAf8gG6Bz0Y4/pXSUUaBZ9zz+bxBcnxnFcLpVwJFgK+QT8x4Jz0raXxZeN/wAwC79sEnn0+7RMR/wsa3wf+Xc5DD/ZPT/PrXTU2JXOabxVequToN2B+P8AhQPFN6XYf2HdADpkHn8lrpaKWg7Puc4fE96F3f2FdEY5w3/1qaPFN63+r0G6b5QcAn/CulooCzOc/wCEovOcaFdZHJVjg4/KmHxZec40C7IBwTk/4V01FGgWfc5tfFN633dAuzz6nn/x3603/hK7wbd2h3QDHj3/AErpqKNAszmV8VXp66FdA+nP/wATTz4puwAf7CusE9c8fyro6KNAs+5zf/CUXpY7dAvCoOCeRj9KQ+KbwZ/4kV1hc7ucEfhiuloo0CzOXHi29Khv7BucYyfmP+FP/wCEpvtvOgXY/M44+ldLRRoFn3OaPiq8QlX0K73KOg6H8cUsXii8kcL/AGHdD1PPH14rpKKNAs+42Ni8asylSQCVPb2p1FFIYUUUUAFR3E32e2kmKlhGpbCjk4qSigDmf+E1gDANp14PX5BxTR43iJx/Z1yTjjHf/IrqKKegrM5keNIuCdNuwvc7fal/4TIHG3S7vkZ5XH1/Kuloo0CzOZ/4TMfNjS7s4HpSjxku4htKveMHhM8d66WijQLM5tvF/wBzytKu3ZgCQVwR/kYNM/4TLOANJu8+4rp6KNAszlz4ykH/ADB7rjr/AJxT38Xuh50a8GemRjP6V0tFGgWfc5W58Sm6jaC40C5kjYfMrjt27Vzdxdvprm70q2u9POeUkbKH26D24Nd3rNxqccccekwB5JDgyMMhPes628KGe4F1r1017NuyEB+QD0x/+qnoS02J4T8S3Wu+bHdWZjaIZMyghD04+vX8q6WmxxpFGqRKqIowFUYAp1SUgooooGFY2p6++nXhhGnzzjAxImcZPQdK2aKAOZXxg7rldHuye2Bx79u1KPF0vBbRbwRkgb8cZ646eldLRT0FZnNHxe+fl0i7ZR3APX8vcfnTT4xkCj/iT3OT05/+tXT0UaBZ9zmf+EwbodIuw/cEf/WoHjFivGj3hbsAOvpjiumoo0Cz7nMjxixjLf2RdA9hjg/p+NH/AAmLbSV0m6wOcnOMflXTUUaBZ9zmz4snRiJdEvE9Nwxn9Kw9K8RPba3qlwum3Li4YMFAPHJ68fX8q9ArmfDox4l1v5m/133ew5NPQTvcD4wk3BV0a6JPQd/5U3/hMz/0CLr8u35V1FFLQdn3OaPi6UID/Yt7nODkYGccjpSDxgxAzpF1njI+vTtXTUUaBZnMHxi+QP7Hu8n1H/1qf/wlsiqfN0a8jcdVYdP0rpKKNAszmf8AhMJB10e6BzjB4/pTW8WtOjo2i3TIV+YDJ479q6iijQLM8zaCze4LNYalLATu8jdgfy6Yrt/D4tPsB+xae1imeVdcFvqep/GtWihsSVgooopFBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAR4m/56R/98H/Gs7xCJf8AhGNUy6EfY5s4Q/3D71q1neIv+RX1X/rzm/8AQDSm/dZrh1++h6r8y7ib/npH/wB8H/GjE3/PSP8A74P+NSUVVzGyI8Tf89I/++D/AI0Ym/56R/8AfB/xqSii4WRHib/npH/3wf8AGjE3/PSP/vg/41JRRcLIjxN/z0j/AO+D/jRib/npH/3wf8akoouFkR4m/wCekf8A3wf8aMTf89I/++D/AI1JRRcLIjxN/wA9I/8Avg/41z/izXrjRbFEtXja7nbag2HKj16n6V0lcr46jT7LYzyg7I7gB2A5AP8A+qmnqJrQpsvizSLH+0Z7tLkKA0tuwLEDv/8AXxXU6feNqOnw3cLpslXcAUPHqOtWJ1jns5FfDRSRkE+oIrnfAcrPocqM2RHOwX6cf560X0FbU6PE3/PSP/vg/wCNGJv+ekf/AHwf8akopXKsiPE3/PSP/vg/40Ym/wCekf8A3wf8akoouFkR4m/56R/98H/GjE3/AD0j/wC+D/jUlFFwsjG1zR7vUo45LW88i5gO6MqCAT78n3rMtdd1TTL+HT/EAiHmfLHcKM7jnvyOOev/ANeusrkPG9xDci00232yXzTAqB1Qf/X4ppktW1OrxN/z0j/74P8AjRib/npH/wB8H/GnRhhGoc5YAZPqadSuVZEeJv8AnpH/AN8H/GucuEk/4WBakFS32ZiT5ZwOvvXT1zdyQfiJZ84Itm6Hg8N196aYmjoMTf8APSP/AL4P+NGJv+ekf/fB/wAakpGBKkKcHHBx0pXHYZib/npH/wB8H/GjE3/PSP8A74P+NcxLofiaSRiNcVF3ZXaW/wAKItB8SxyCQ69uPGVOSMUyS34h1PVNH8m7gjSe0XiZQhyPfrWlp1+uqWMd3aTI0b+sfIPofm61PLIkGns9+6FFj/esw+U8c1zXgBHXTLt+fJef93wfx/pRfQLanUYm/wCekf8A3wf8aMTf89I/++D/AI1JRSuVZEeJv+ekf/fB/wAaR45XRkZ0wwwfkP8AjUtFFwsjjfB1v5Wsa0sO1RHMFGVzkZb39qTWUa1+IGlTReWZZwFfCH1IyefT+VTWDDSvH19DKSsd4vmKTwM9f/ihTLdj4g8dLdwgNaaeu0SKerc4/XnjtVXIsrHWYm/56R/98H/GjE3/AD0j/wC+D/jUlFTcuyI8Tf8APSP/AL4P+NGJv+ekf/fB/wAakoouFkR4m/56R/8AfB/xoxN/z0j/AO+D/jUlFFwsiPE3/PSP/vg/40Ym/wCekf8A3wf8akoouFkR4m/56R/98H/GjE3/AD0j/wC+D/jUlFFwsiPE3/PSP/vg/wCNGJv+ekf/AHwf8akoouFkR4m/56R/98H/ABoxN/z0j/74P+NSUUXCyI8Tf89I/wDvg/40Ym/56R/98H/GpKKLhZEeJv8AnpH/AN8H/GjE3/PSP/vg/wCNSUUXCyI8Tf8APSP/AL4P+NGJv+ekf/fB/wAakoouFkR4m/56R/8AfB/xoxN/z0j/AO+D/jUlFFwsiPE3/PSP/vg/40Ym/wCekf8A3wf8akoouFkR4m/56R/98H/GjE3/AD0j/wC+D/jUlFFwsiPE3/PSP/vg/wCNGJv+ekf/AHwf8akoouFkR4m/56R/98H/ABoxN/z0j/74P+NSUUXCyI8Tf89I/wDvg/41z+v+J59JvorC0t/td3Ku4KqHAHPoc9jXSVyd0qr8TbSR8rm3KqSODw3FNMTRY0fxLcXd81hqsKWN5/AjIcP9MnrXQYm/56R/98H/ABrl/HFv5SWOpwArcQzhA6nsef6frXVg5UH1FFwSGYm/56R/98H/ABrmvD01w/iXW4nmVtsoxlTgcnoM1Z1bWdYs7po7HR2uY+gkBJz+Vcno99ro8R6k1hYL9pmJMqPkCLJ+vvRqS7XPSMTf89I/++D/AI1S1SDVZrULpl1DDLuyWeM4I/WrGn/a/sMf9o7ftGPn2dKs0rl2OTsvEGrWesJpmvxRoZWxFOiZV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alt="" width="800" />
这里讲解的是平均池化层，最大池化层见本文第三小节
二、测试代码
数据和上面完全一致，自行打印验证即可。
1、前向传播
import tensorflow as tf
import numpy as np # 输入张量为3×3的二维矩阵
M = np.array([
[[1], [-1], [0]],
[[-1], [2], [1]],
[[0], [2], [-2]]
])
# 定义卷积核权重和偏置项。由权重可知我们只定义了一个2×2×1的卷积核
filter_weight = tf.get_variable('weights', [2, 2, 1, 1], initializer=tf.constant_initializer([
[1, -1],
[0, 2]]))
biases = tf.get_variable('biases', [1], initializer=tf.constant_initializer(1)) # 调整输入格式符合TensorFlow要求
M = np.asarray(M, dtype='float32')
M = M.reshape(1, 3, 3, 1) # 计算输入张量通过卷积核和池化滤波器计算后的结果
x = tf.placeholder('float32', [1, None, None, 1]) # 我们使用了带Padding，步幅为2的卷积操作，因为filter_weight的深度确定了卷积核的数量
conv = tf.nn.conv2d(x, filter_weight, strides=[1, 2, 2, 1], padding='SAME')
bias = tf.nn.bias_add(conv, biases) # 使用带Padding，步幅为2的平均池化操作
pool = tf.nn.avg_pool(x, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='VALID') # 执行计算图
with tf.Session() as sess:
tf.global_variables_initializer().run()
convoluted_M = sess.run(bias, feed_dict={x: M})
pooled_M = sess.run(pool, feed_dict={x: M}) print("convoluted_M: \n", convoluted_M)
print("pooled_M: \n", pooled_M)
2、反向传播
import tensorflow as tf
import numpy as np # 输入张量为3×3的二维矩阵
M = np.array([
[[1], [-1], [0]],
[[-1], [2], [1]],
[[0], [2], [-2]]
])
# 定义卷积核权重和偏置项。由权重可知我们只定义了一个2×2×1的卷积核
filter_weight = tf.get_variable('weights', [2, 2, 1, 1], initializer=tf.constant_initializer([
[1, -1],
[0, 2]]))
biases = tf.get_variable('biases', [1], initializer=tf.constant_initializer(1)) # 调整输入格式符合TensorFlow要求
M = np.asarray(M, dtype='float32')
M = M.reshape(1, 3, 3, 1) # 计算输入张量通过卷积核和池化滤波器计算后的结果
x = tf.placeholder('float32', [1, None, None, 1]) # 我们使用了带Padding，步幅为2的卷积操作，因为filter_weight的深度确定了卷积核的数量
conv = tf.nn.conv2d(x, filter_weight, strides=[1, 2, 2, 1], padding='SAME')
bias = tf.nn.bias_add(conv, biases) d_filter = tf.gradients(bias,filter_weight)
d_biases = tf.gradients(bias,biases)
d_conv = tf.gradients(bias,conv)
d_conv_x = tf.gradients(conv,x)
d_conv_w = tf.gradients(conv,filter_weight)
# d_bias_x = tf.gradients(bias,x) # 使用带Padding，步幅为2的平均池化操作
pool = tf.nn.avg_pool(x, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME') d_pool = tf.gradients(pool,x) # 执行计算图
with tf.Session() as sess:
tf.global_variables_initializer().run()
# convoluted_M = sess.run(bias, feed_dict={x: M})
# pooled_M = sess.run(pool, feed_dict={x: M})
#
# print("convoluted_M: \n", convoluted_M)
# print("pooled_M: \n", pooled_M) print("d_filter:\n", sess.run(d_filter, feed_dict={x: M}))
print("d_biases:\n", sess.run(d_biases, feed_dict={x: M}))
print("d_conv:\n", sess.run(d_conv, feed_dict={x: M}))
print("d_conv_x:\n", sess.run(d_conv_x, feed_dict={x: M}))
print("d_conv_w:\n", sess.run(d_conv_w, feed_dict={x: M}))
四、CS31n上实现的卷积层池化层API
1、卷积层
卷积层向前传播示意图：
def conv_forward_naive(x, w, b, conv_param):
"""
A naive implementation of the forward pass for a convolutional layer. The input consists of N data points, each with C channels, height H and width
W. We convolve each input with F different filters, where each filter spans
all C channels and has height HH and width HH. Input:
- x: Input data of shape (N, C, H, W)
- w: Filter weights of shape (F, C, HH, WW)
- b: Biases, of shape (F,)
- conv_param: A dictionary with the following keys:
- 'stride': The number of pixels between adjacent receptive fields in the
horizontal and vertical directions.
- 'pad': The number of pixels that will be used to zero-pad the input. Returns a tuple of:
- out: Output data, of shape (N, F, H', W') where H' and W' are given by
H' = 1 + (H + 2 * pad - HH) / stride
W' = 1 + (W + 2 * pad - WW) / stride
- cache: (x, w, b, conv_param)
"""
out = None
#############################################################################
# TODO: Implement the convolutional forward pass. #
# Hint: you can use the function np.pad for padding. #
############################################################################
pad = conv_param['pad']
stride = conv_param['stride']
N, C, H, W = x.shape
F, _, HH, WW = w.shape
H0 = 1 + (H + 2 * pad - HH) / stride
W0 = 1 + (W + 2 * pad - WW) / stride
x_pad = np.pad(x, ((0,0),(0,0),(pad,pad),(pad,pad)),'constant') # 填充后的输入
out = np.zeros((N,F,H0,W0)) # 初始化的输出 # 以输出的每一个像素点为单位写出其前传表达式
for n in range(N):
for f in range(F):
for h0 in range(H0):
for w0 in range(W0):
out[n,f,h0,w0] = np.sum(x_pad[n,:,h0*stride:HH+h0*stride,w0*stride:WW+w0*stride] * w[f]) + b[f]
#############################################################################
# END OF YOUR CODE #
#############################################################################
cache = (x, w, b, conv_param)
return out, cache
卷积层反向传播示意图：
def conv_backward_naive(dout, cache):
"""
A naive implementation of the backward pass for a convolutional layer. Inputs:
- dout: Upstream derivatives.
- cache: A tuple of (x, w, b, conv_param) as in conv_forward_naive Returns a tuple of:
- dx: Gradient with respect to x
- dw: Gradient with respect to w
- db: Gradient with respect to b
"""
dx, dw, db = None, None, None
#############################################################################
# TODO: Implement the convolutional backward pass. #
#############################################################################
x, w, b, conv_param = cache
pad = conv_param['pad']
stride = conv_param['stride']
N, C, H, W = x.shape
F, _, HH, WW = w.shape
_, _, H0, W0 = out.shape x_pad = np.pad(x, [(0,0), (0,0), (pad,pad), (pad,pad)], 'constant')
dx, dw = np.zeros_like(x), np.zeros_like(w)
dx_pad = np.pad(dx, [(0,0), (0,0), (pad,pad), (pad,pad)], 'constant')
# 计算b的梯度(F,)
db = np.sum(dout, axis=(0,2,3)) # dout:(N,F,H0,W0)
# 以每一个dout点为基准计算其两个输入矩阵x(:,:,窗,窗)和w(f)的梯度，注意由于这两个矩阵都是多次参与运算，所以都是累加的关系
for n in range(N):
for f in range(F):
for h0 in range(H0):
for w0 in range(W0):
x_win = x_pad[n,:,h0*stride:h0*stride+HH,w0*stride:w0*stride+WW]
dw[f] += x_win * dout[n,f,h0,w0]
dx_pad[n,:,h0*stride:h0*stride+HH,w0*stride:w0*stride+WW] += w[f] * dout[n,f,h0,w0]
dx = dx_pad[:,:,pad:pad+H,pad:pad+W]
#############################################################################
# END OF YOUR CODE #
#############################################################################
return dx, dw, db
2、最大池化层
池化层向前传播：
和卷积层类似，但是更简单一点，只要在对应feature map的原输入上取个窗口然后池化之即可，
def max_pool_forward_naive(x, pool_param):
HH, WW = pool_param['pool_height'], pool_param['pool_width']
s = pool_param['stride']
N, C, H, W = x.shape
H_new = 1 + (H - HH) / s
W_new = 1 + (W - WW) / s
out = np.zeros((N, C, H_new, W_new))
for i in xrange(N):
for j in xrange(C):
for k in xrange(H_new):
for l in xrange(W_new):
window = x[i, j, k*s:HH+k*s, l*s:WW+l*s]
out[i, j, k, l] = np.max(window) cache = (x, pool_param) return out, cache
池化层反向传播：
反向传播的时候也是还原窗口，除最大值处继承上层梯度外（也就是说本层梯度为零），其他位置置零。
池化层没有过滤器，只有dx梯度，且x的窗口不像卷积层会重叠，所以不用累加，
def max_pool_backward_naive(dout, cache):
x, pool_param = cache
HH, WW = pool_param['pool_height'], pool_param['pool_width']
s = pool_param['stride']
N, C, H, W = x.shape
H_new = 1 + (H - HH) / s
W_new = 1 + (W - WW) / s
dx = np.zeros_like(x)
for i in xrange(N):
for j in xrange(C):
for k in xrange(H_new):
for l in xrange(W_new):
window = x[i, j, k*s:HH+k*s, l*s:WW+l*s]
m = np.max(window)
dx[i, j, k*s:HH+k*s, l*s:WW+l*s] = (window == m) * dout[i, j, k, l] return dx
五、实际框架实现方法
实际框架当然不会才用这种大循环的手段实现卷积操作，矩阵化运算才是正路。
1、Theano
常见的一种拆法是将二维 input 展开成一维向量（[in_h * in_w] -> [out_h * out_w]），将卷积核展开为（[in_h * in_w, out_h * out_w]），
上面仅讨论了2维输入，其实由于 input 的 channels 和 kernal 的 channels 数一致，所以情况延申起来原理并无改变。最后的运算如下：
y = C·xT
2、Caffe
caffe的卷积矩阵化如下，其直接把 input 的各个通道的值放在了一个矩阵种，将各个 kernals 的各个通道值放入同一个矩阵，一次解决所有运算，感觉比上面的做法高明了一点（不过都是很厉害的算法）。
