# Tensorflow Graph Compatibility

Layer to Graph Node Compatibility

The sections below describe what topologies of Tensorflow graph
operations are compatible with each of the Qualcomm® Neural Processing SDK supported
layers.

![../images/node_labels.png](data:image/png;base64,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)

Batch Normalization

[Tensorflow
Reference](https://www.tensorflow.org/api_docs/python/tf/nn/batch_normalization)

![../images/node_batchnorm.png](data:image/png;base64,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)

Convolution

[Tensorflow
Reference](https://www.tensorflow.org/api_docs/python/tf/nn/conv2d)

![../images/node_conv1.png](data:image/png;base64,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)

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)

Concatenation

[Tensorflow
Reference](https://www.tensorflow.org/api_docs/python/tf/concat)

![../images/node_concat.png](data:image/png;base64,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)

Deconvolution/Transposed Convolution

[Tensorflow
Reference](https://www.tensorflow.org/api_docs/python/tf/nn/conv2d_transpose)

![../images/node_deconv.png](data:image/png;base64,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)

ElementWise Sum/Mul/Max

[Tensorflow Reference
Sum](https://www.tensorflow.org/api_docs/python/tf/add)

[Tensorflow Reference
Mul](https://www.tensorflow.org/api_docs/python/tf/multiply)

[Tensorflow Reference
Max](https://www.tensorflow.org/api_docs/python/tf/maximum)

![../images/node_eltwise.png](data:image/png;base64,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)

Fully Connected

[Tensorflow
Reference](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Dense)

![../images/node_fullyconnected.png](data:image/png;base64,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)

Local Response Normalization

[Tensorflow
Reference](https://www.tensorflow.org/api_docs/python/tf/nn/local_response_normalization)

![../images/node_lrn.png](data:image/png;base64,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)

Pooling Avg/Max

[Tensorflow Avg Pooling
Reference](https://www.tensorflow.org/api_docs/python/tf/nn/avg_pool2d)

[Tensorflow Max Pooling
Reference](https://www.tensorflow.org/api_docs/python/tf/nn/max_pool2d)

![../images/node_pooling.png](data:image/png;base64,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)

Sigmoid/Relu/TanH/Elu

[Tensorflow Relu
Reference](https://www.tensorflow.org/api_docs/python/tf/nn/relu)

[Tensorflow Sigmoid
Reference](https://www.tensorflow.org/api_docs/python/tf/sigmoid)

[Tensorflow TanH
Reference](https://www.tensorflow.org/api_docs/python/tf/tanh)

[Tensorflow Elu
Reference](https://www.tensorflow.org/api_docs/python/tf/nn/elu)

![../images/node_activations.png](data:image/png;base64,UklGRs4dAABXRUJQVlA4TMIdAAAvqMFQABVpYf9fjiRbevDBgQMfHDiw4YUNGxZsWPDChDWsYMELL2zYcODAgQMbDhw4cNiTIpwR9vH/xN3vRSlLJaU8q5UqqQzdUmfKzFKRM5tnzUH9A62SQUsmJVmzpaHfkjK0VCrV4ZUBA4Rk6DOrUcvSXQydepvJlYzemtF6i0lKx2kjSZIU/lt1/zUs2LBhw4EDXdq2tVUT9/0/7/8CNww/PBiG4YdhGPYfFmxbVZuNJo3tpXp46A1y/f91ftxf+gd8RKHU3+FvAhyhuPgH7/E+D3iMZf4eTxiVygD8bRQX/+AbfMCHlFb5hG9RKpUDKBQX/0An6ceY/OkRGg1XAPAs8ndpgG/DFQBCi9U1BTquAGCSv0+ts0HxlP4R/5BoWtD35imQ5BVfQkyVUEp8k8o0Jepu5FAHlZmoteGkeExSw8IyCC6FCFCbXwbJpQ4hdKg2QxqgJ7VZUoZ0w+jQwVnZUKqRYwG8OjDXv0l+EYkzmdJh4lgHJ6lWV9+BX6Q0p0qtOV5MVoVERxzrINQqamyafq/cOP1eBWdTeG5I1IahR75hGJBtCKI25xk5munNgrbkuhRGaaJnaQOum+84bbZWwjMZyo1jXGyK8+AmYtgw5N+TMQ0jz4wP8c3sy8D16aB3RxNmQ8QzhVt+D9Xr/SCLMevtRvwKfx07/bewMnM6yEa2x8xuz4rYZUIVShP+ZFYa4bN4IhvHU2S8TJfOuBoOu5HJ/TV+lb9GPSiVdQw6hm4FfHQjf4PYmHwq5CjsxHGcOb6UfIO4bp34wGpMkzPaprmM66YZNgEHYwkNKnIut400EMUwFAE3RPG8FK8pDaqHONR97CoZo7/c5iO2qVIyvTzs+mPlMuJQdwyxP9XxoJQK6+2lK5WMEczbVCwZljtgr/9mC7u4VLtDnh+cNXDjv4lD7MsVzWOO0+xygYi3iRcf6nyOA5XETjfH/fE9c7tt7Nrov9mC3B76NM6WYiyF8JfA3cY+P/6bjOOmaXaxVkPsSNnE02r4MfMPcYy2MlDGUKo1EE9Kx7nK4yyMoVQZ62N7pg17ZqOZPZSjoTREHEeqj1Ml4nhUfmzH0JGNGJIrVR4bUsknavLTOT6UCwzqq8L4opQTl6qIW8POyHirVu0Zb6hutz3EO6MYZeys2AF7seGDH9dqgVMuklxBzxVKKeXFzgp6A5fHcTcARVyPoYHL41zazZj1dmzexYUa4lqpMBRL5PLo3djlxn8rLlOlVBDXKz64a1l+MCizas9s9d9soY1zNVAgCiebzYZlRru47Q4woOY49WaezC5jpM4h9peIy+WfrEUlcZPP8aBW7RlvZnmse1weAhNwl1EdZypytgcnOnbku4MTcISq0vmw1ceuJcP5kORxuw7pbg8Y1Ko963lDOIfdkB+0Cb6jf8EZjUp1cf690DjYHGf55SH6XmgcbEy227r8YY1xMALQGwcji43jYDwThdP3TP39j+LcT/gT//23n/jvv4nQzxqnrhPH7YpqI3Qj05C3TrIUos2HaRN0I3LI2+aYDsHEbTcihlZjdUq6kXOmvsGa1PQT38giXVcwjj/xiOxr4L3r/ePB5mHnm6mjqmX6ZvLh5IPNNy4ATckxUaaB6w/W2XxUWerwaj57eg3oLOKXydPA9fsnH47KoMPLYzq0n8Cd/1bUwDduPpx69MijqkV69KlFOlmmo8r+AmhGTv036enFlvnRo1YL8dP56TW0J/n032S31OFh52RNwcz310A7ceW/fUIDvJsXh/7o812dFhKcXQCe4NEsqHH9YLxcK8SiVF7+xjXqgEezMsH1/VHl5OSztQXzcn8N3XOU0aBx8bBjOPq/9fmsTksJfmd/jSbiDuEBb16ZEMJQJK/eAJ7gjhx494cnJ2vL5d8s6+zLp0AreMEHnv7O8ujNpIUCf3iBeuQMmeL67MSkEMsfzq6RSr4QLfDpTy3oUF2jkbb6b2zXs5NXhp9MKvA7bxYLV/6bTPGezCefWRFi/nqxUPDfmK7Xs7WCOapcwJl48N96XD/srCgOsxvvUX8CR2YixcVR5cSKDv/GUCKp4Misxdd/aLFgTl4+hyPpZxQAi/XfGJKFunqPJOKHFhcvLQtx8vICLT94uDbWV0tN6HeeIxXUGbVxtSrAT9+gEbzgQx8rD4s/avi8UED/IYuCeXkBj7j/JhrcGw/fclW9QM6J/zZqzEyEOJmhRz78t6jGww4bHf7wGiVt/83HxaPK4vTMqEA+gQ+zBvtFeTAR4sEEDR9mLp6y0uEMiaCc0WRsN6wKxOWCAhe/84oNr356gYIHSujfecWqYJ7Dp4x3fBuTTRolBwhjB8eoQCrUggMcnLHTYYaWdP23SR+7kGLVp6Qc+G8F3i10YCbEOxT0/bcBFz999Cl2BfMUOV3/LTd2/MzerjHSN3OM7+zeEvpmqfGd3VstyGaUYF7AToA9OvKEKxoOs1+H1Ilwvfw9y65loEqIi8XKkD9ELajjYc9WiD086vi4Z6vDGVqq/luH/QKWAlxgpO6/JTiqsK6xCXX/rcHMlEefegktiPpvDmbG/Ff4xM0iQ8/CuMZGtM0krlnr8BwhzYwkrn/6ii0PO3CJE+Apa54ioE2Jd6z5r/BpMuI56+M/qiAhTocz1pyho02PPWsqtDT9twD3C9gKcA1J239zDbmy7lpo+28ezljzh2ho+m859sy5QEXbzMEr9l2LQ9ssxWyEoYsLTTOjDmfMeYeQNjVesi6Ql6hp0+APbejqBEk8fDjFnDcoaaPxO6/Ytxx22NazMEdDkvTfMsOpiPXVXUnbf9NY6MBYCGja/ltiD3b4byQ/vEFI26zGS/Yvta1mVD+QzCi3ZfNIm8SOP0lok2JmDrQiSY/fsMEsok2KmTUzUtq07N2UV0ho+m8l3thx1Wur/8bmqoo1T5HR9t9yfMq+wro0/bcIF3b4kbTNfPxX1uzh0zYLcG/DNzREh1fq5bmI8fF7xAnxnDXvENImwoUN33naA6u+n7HlQByhjeODLMe6tWA/DmZPC2I4gqoRER0HK/D0hHV5TNTHwVJUJyw5qZBSHwfLcMZWhxmOIjoOJg0th+klg0v+7qcCb9jyBgX1u59KPGfLPXxFMyOlXJydsOQdAvJIfc3wW8bPTl5ea0kdUeMPGd91FJGlxAXrm3vIozz8Bkt+A56yF3K3h518CpfwvCxn6TEx7OByDu4nrLB8Y/eOyub7CRnecMns/WuUhOdlBYY7l9m9Sx5mkbS4Z8c9Wh5mkXh4w06HPRq23QjzlLLybT979c8v0CseiDRmRkKczNARD0jDvd2Mvra6xkiaTzAUCKN20wguUP6yb2E1/8hXPKAK6JcnTHT46XN4xONb+Ph60fszcZX0J3AyL0s0+GAt7sli8uVDIziJb9HiHRsd7uFI6vEtUhZN57OT+RoFN7Pxo3p5FmBxIqojXmbjT8nydG29YM6gR8U22YF08M7i8plhGp+nuEGFevlluVUhPoUOFS+oUeM3TiwXzIdTQKDIo6JksZx8Zmky/qzRKo5Qgcb+5JU1IfbQgeIHVWrc/9RiwZwBPRfxLSYHF/Oi7ZiupT/dAx5ncQJLjTe/Y0WI33kDXfIVJ3Cs8e6lJR0+WNABJ3ECpxTXn54YFDAVuuYNkNvRjdicwhoXs1khTk7mC9QhkW6E5ZLg64cdSzroweZuhHHMo2MlslIDQ3Sqf352jXpQ3KGiBjgWm2p9CKanQBMp3lBTCrwxqcPLe8D5BMUNSoUO8O5h52R1GLGTxdGffQ20k+IQJXyN6/s/XBz7miBrf3h/De0LRQM7wvM9ndfrcFT5r9fQueArTqDoa+Dr36h+5+R4emWIWNiU3MZbjzINPP90PlmR5k+fAzqLeI23PnUauNiv1OEPz94BaCv+4q3L3gGAizf3+//6G/fvrgHoduA6OnTV1QCuL57e/9f/ev/04hpA3VU8R4eO8mSlDs8NOnijWpd46fUqP8WKpNtAch/GW5Rdsjq0bim4D+Mdds5KHbxB8BxvXVSD76Dtw2hjxFuXY5ADeTAaaist7NRBwwvCif9465H3a8S6l5sk3vroxLEzbpJ461V6iJNS0Hlulb1rvG6hYmbvunYhYmbvGtu95CiorMbFXqitxsVmqK3GxV6IrMcXWyG2Hl/shdh6fOH5uVXS1/M8H+LLeZ6dUmyC51ZN7bxIcby0a6dN8Nyqydut0MGteH5ulRz6RdKxu8xpFJvAbOqXKY4NOU2bwGwq+kXaxvkyp9UX5Jz2ek1cbJrHIcXxpnkc0hwbnabvrRmz3mZoPrfKXmg+t8p2CPlvNkOzG7EXmt0Iz+QofpDFNIwkoOa/UYCa/8YzhVt+t53RT+D239JDLzYM21huGHZxtSH8t2zbyQ3jvyEeN4z/lhwGsRn8N+/SmzaMWR2XG8bMORSC+4zG3kud3XaXpF4/ik2ALP2sceatdtwuiDYB4pgOcNyuqPglzGoY0g6GVGch54gg1UYdjgmR5BHfiMFdq0NX8ei/icABdJMPlVymashTDTiF4Nd/k3kNaLcvI4MQY+ElANyRX/9N+gYd/OM6BJ0DIC25899KB3B6uU6SogGSgVMz4WvothRmZmq5EZ9moq8BdxBmZmqlI1fXEVNrek5j2QDuxCOhA51FZstJ+zxSNWbnNIoige4EP4wJavN6BTWSkT96jcb0wcoOcCV3BBpOaLqJ5xrNxIv/VmqkVg5RutADb/6bB1iaOR0mcCLO/Lcc8KzoUDmoKz78t0HDaqeRQwd8mWWoS8tBDJKInJm9uksX9chDRqVmEMitBwae8BjILVwkE0fkDALUiAx1RZ9Ro2cTLS/kB5+J2MKFI6lARXMPyUTdf5M1clalNvHivw2MArmJFC0v/tuodclEBxepIO6/ZcyCy7toOTGTCasAYVONgA8z4SBnppdPO6OSXQudagx84MFl1+JryQU5uwifodYRZYTDsD0MSAQPjCy79hYeD0SaYWjYDi1l/61Ao9ilFL3d/hvTg2NWdhEH/luGTrFTu8ZI138TCUKWdQ61oG82su0ucnj0zSKtWfbrPVq6GQ3Ld6ZvBX3alVcCY3K51YMKZyuPF9ATebrlO9O3iiwuAsbVKSWPXN1wdr5SxVaKyVJ16qkjakSMq1NO1X+btJbM5aLuvxUrOy0RT0qpyvDSXcKf1YhM70pn166qiA11/61EqphSIaHqvwXMr488FNTN2tU756CflFoybieRLIhL1eyE2E6rauxE3MxjHvTZQUU0o4y5rzqgJY7QkKvHLeoDiiW+o1SwzE4pz1VqHldWKOIkiJifSnuiOIgYM6Emzghn/fDkIVzQpcZs5wWtUrtw1fVdZysUdR7Q0vTfJLRinRJMtP23YPV1fjQYjtRfkDeLF3OMSGn7byVc1kRwaPpv1bprABEfDofLVK5QfzaVaUjbLF/dY1XbQKlyOy4Il5vNIVHTNitWdxRJbEhratp4qdYlrQXJjAZk64iUmpLWEh4C27ClHAe93erAYNbO2jeHqiFJ060tx8tQKWURBxFJAngmUH6tVIC5npaEO7XYvqap0cZFaOlYTJ8DSOMhMIG/m+tIjfDq3aDG2ZvnYU1XN5L03wrkZl5qT0XbUeWOOXz4BP03JvJO20qlrTkcRKT9twzleqZDpFJXjfGgCq3GQ698va6Kk/Tf+vVst9tDJgxX4fIgTNHDt9XMRpQ/z85kjgYVabPWDEoqVSQGD2Wcj+W0Zk9DkhkV6Na+GNqM6g7zPG8nsx9o49ogr4OINB4GE3ha72o1Xi64PJbTug8kGUxt9hKleuO17TGGlXQoaNOiZE4NSZrOzOYAUvVWaFCR9N9CuCaQ21JNl5UK2yXRQSp3JS1KW/03O78aC2ez179Ca9r+mw9/PbmjZKItUEOS9N8mJGbMchjMUBqKo90l+UocRLTNeuRmEZNZKjiKtNmAzMSf6F0dXmamkaiJDq9o5h2W0FrQpkRrogPY7epj39zP8NYzoKVNhYZ5/4mUKC5KxoRIFW0karGOaFupXC+ptpNq1tOhp41gf+r1kRMdB/ORsz9+6uNgDsZ19I5SIpYLfEepYT0NRuLjYC5K9i2O6DjYCIcxDUJlq5ktQ7NdqpTaVse/uV9LhFoQH17p4dkwMG5LRoxaDlMiJIo6IxJrL8FafHiKOBPrGhigVVTJ0THWtCOPchCa2VwfH1121uIgpI5KETAlxUD2fsJJ64lph4KI/v2EPdz1jWNXR4a8vctdvo4BDf37CQe2J6UQiaA7L6tFzhAfro3dCMmbJ5VqECjyt6mJhOkfu/BZdiPMqbSOmDFpjBygfKTsKOAIGyF5cCVqSRjVwWXY6DPFAyJBwLDRl4oDVMOueQoHBel5WTJBz4gA9cTHvKwSOmI3/4iPeVmj1iMjPKTE52WVYCRApTHwMhvfYzW/pkc9cTIbP2c1pzJYW7Ep9nod6ogBUwJP8YJ02DTRAbpUnCBSNnMYQ41AUUe4cCbrhdYgFdygoppFZSw1esULanLQWhd9rJFzEN9CpnAi6xI1kqf4FmONTFhfO57iW0QJXMFAKS7iWwgX9WCtOGqk0v5uhHF51mgiSzp1QE+kG2H5ozNawtfIbehGbFoyoJPKSuiaVii+UJGDOrCwUyl0ofhCTY2lQ51awFecoFSvzUcvGxxoXyneULIF3MpsEDiNZFS8oYRnPnqZ6GvUJU9xAqsUcAJhIoJhAzQVn3ECgxpoTWg3+TXgSS7jBJYJ4JqoCLJPgGxSRmz031iXiAPU3rBKfDl4NZAE3EaHlrkGHD8Uq/IuWg24I6/RoYVfA0m+Wocg00AaKntTicyWgKQAkLhenuedmwBAWgjFLUpNeQJAO1mX552X1gB0FvIcxlv6jkGHtsvz/JgObclpvPWodzUAzDsA2u0j/uOtj3kDALsZAOpskNzHW6/81Tq0geQ53rqIyt6Znb6MxKaIty6rIcfcFuG0KeKti2rw69ntw4n/eOtTvot3+USvG7G1eN1tXA/0wtXYWrzZZawLaXc3QmWNl4vNkFvj5WIz1NZ4udgMldW42Au51bjYC7XVuJB5bpWd6/GF3HOr7FyPL9SeW2Xnav9SuKXtjUkGyTzP23g7z3NSSMW/mZId5nk+xJfzPKejUNybKZnrFTo0pa062E/YL1ITJ8ucys1A0C/SHHvLnKqNwNAvEuJ2mdNIBhtTF2dqwzy3CvG4YZ5b5cQBqedW2c13xOdW2Q8d/81maHYjNkPyuVU8k6P4QRbTMFKAnP9GAWr+G88Ubvk9lNl33fzEf//tJ7T4b1HY50lc530ZbQj/TVSDn1/GbR6MckP4b1HZ57s4zYtQcuy/idJLAGB3uQOApAu5N5NFWwPAfAkAOvUj3s1kcEwHY8E0ecVnRjJPAOgPzvnhzm/OftTb69ent3sNIMknnqkyDeAb936w8+EepwsdTm/fv9d79waQfozgmMgz6LB/OMeyYI7p0PSCO4RfA1enTzI+eiyrUn56DugnSF6JMgD7o9m/VesqHb5d6+P0rQacgVcmTwP71yt1ePY4/fYKSALO/LfSAfaPuxcH/dFrWZWWGx7sCSQll/6b8DXec39+t0aIZZk86u0KcCMu/beixle3dyYK5sU5kFYc+W+iA85zw8F/9PqvSgYJ8j3gCf7Moga4vVkrhLFM/t8V9MCfmUyBB+f8Vg2TBfPiCrrgJiOZIj5dHv1/WZ+WCryOkU68Eda4+nPzQtzcAjlvVAmuHqet6eAJPogcnN8dO3pzCtydI4n4ItCLreaFWDYejVZwRajxYKc1HR6nr+BKHvy3abHePDMcvWkFbvaLhSf/rdR4+8yKEFn27EnGYuHJfxs1bq3qcHeFVND330SDvWG1ujiSH7NxuX70WqwKkWt0/JhFNW6t6mBYjqCfUYYrw2p1OYfLDVOC24UOloX48xgBL0gHD3ay0OFJRgyfOh8DfWc8futVteCFFvuFDgyEeIE64gQP5zdMCuZxGnqk7b9NNV4syoNNgeiID/8twNUNIyFukfLhv5XQd4x0eAtHkPbfMmP/xqhAXC7MpLHCMuHmCgEPZsLBa2YFcw6fckYh4m8/VmbcaJQ80B3fxmiT5AAf5+x0eJIBPRHGxeni+FkJ8BopB0wadwyF2KOnj6jx5wx1+AI5Xf9txNUNQ26uENL333LDGYAZf45EkPffCuxZ6nAHLcn6bx3eLo6fnQCnOIK+WY0nGUyFOEdJ3qzB4zRTHfYoqGYkatwx5UtoQZ3ScCZiyGscQZ0KV2x1eIGUIfaUB9OaWlLHwylbfgktiJPjli03Wk9E/bccp4w5RUfdf0uMn5l+DIn7bykepxnr8GAnBqL+W4o/Z0wOh7jZZOjhmPIWPm0zoeMb5i3II5qRxg3rAokhaFMiYM3jNFrajIZTEuMW1NAkMjQctpyjok2Pt6y5g0Obj8Eta26gafpvJfbMOcNA23/z8Jq5EF9pQdp/y3HKXIcrTCT9twC3zLlFQdusxeO0DQUi7TQjWWHPUZHMqLCBt+hp4+LPbSAiTYYXzNljJEmPt8w5hU+bFE8y7Gg5zLCtZ7GBkKT/VuBzG+ht9d9I8v65ENnpv1F9scN/I7n5cxS2mhHdPJE28/D/CF+Os6XEg502/MnH0CbDo272ZhB2QtQsIuq/ndtQUUfa+Dhl778l3xn9N4GYORqStv824Av234i4vw5p/y3EfgHr7/aIjoM5yJ9lzBsObbMKV6w5RadIm0lo1rzGEUSHVzqcMuY1jqA+vFLjjv14D/HhlYZ5C7pFQZQBe8Z8gYA6LV6zJHt2E2vJHuIt6AoR0XEwqfHls4xxeVAfBxuwZ8t/gKuIj4OFrEeWH6fRkL2fsMUpU17DJX/3k9T4JVMh9giUvWbMRlBZfmY6LMeaEldMOcdAHuXhLTuyZzlqSZ4cX7DU4ctYR2RRDsMvZ7JnL+AI+lSIWd43d4tckWfSX/2SoQ5vcQTheVkBrhhyjoKHeVktPmd7RywH87I8dm/Zs7tYV5TnZTXLXzP7vSNs7UbYSae/umMmxH75Tv5+QjXV+HNmOnwBj2k3YkOLR7w4TbOppxqh4gHV4ZwN2bPXSAQPqJ7drJYXqCfSqM4w7YjNNk/xgXCWm5hs0ygVF4gUt2x0+KVGQDy+hXBw9ixj0p84kpf4FqPG0WzPMgZXdlfoeIlvEWnDWYnFVNDWvvgWlKbGLi+k6oqf2fgFvloMhzEoj1RwMxt/0IZLclaTq+3JiPlkc0uH/+wWulT8oHLEixLJrK6OVNygeuC1ZR32SCZFHxVq7K2Eb1gc/hfLlSdUDpxaqLLZwuIKzqQ4QvUwxnGwGACEjziBY40rQ2Afk1vzc9Qhb3ECfeCLG7M6LIT4WYxUchYnsNDYf2lBhxcazsRLnMCoAT6/MfFDttz69is4kR3diN2prHH1whDyaL0Oz+5WBYWy34xxrCH92qCDiZ++PANaaUc3YlcSucbVqSE61bqoXa+voDup+ENFKXC+CHv0bK0Od7dfoV58BcwdamqB8xfPTBTMzecx6l4pflCqSgF9uzpM4CKfzzWQjkrxiFJBAvzp6S9X63Dz4gzQnlQ8otTgAFend2sK5nH6ixg6m7iLtx66APSDnacvnmTc3d3lL06/uALghhzHWxeFA+Dq9vXjdL7QIf/Z230MaC/iON76xzQGHU6NOvwHow5ZxGW89chvsDo5T4h4jw4deglWJu0WkvPo0ONaHdJe8hvGWw595jZO42b+MG2GMN5VkLep4zRu14diI4TxjoI8M+jg9aVUStGAQKIHgUSOzZDGrLcZms+tshmSz62ymU3w3KrvmruRH2QxDXafimg+t8pmSD63imcKt/weqtf7bpuf+O+//eiK/9ZvGv/NT8NN47+lKyrsiFR9Z+5lmM4MydVmSBGcTUOPfMMQbI7TQo1pwxAi3TBESDYFXscxU2/qkEXDs0NZDsJU4Fyf52uHQG6KuglPbZYkEpQbRogGwWaggJ42DC1ctVno0Kzt/jNOCyqzUE8LX/D5RVpSR6a74o5PHYRTj+vDl+ss4uzQp3FpZ36NNBLeMpfRUvdqNL1XNWrefhAGHaJwvQCZRqWUcgBE3PwDafHk3RiclQpAw80/cC3Pe62VUhOAhJt/0Jiuq4HiC52klbKYqpIzaiez/P8GztBOK9SP/0sK)

SoftMax

[Tensorflow SoftMax
Reference](https://www.tensorflow.org/api_docs/python/tf/nn/softmax)

![../images/node_softmax.png](data:image/png;base64,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)

PReLu

[TFLearn PReLU
Reference](http://tflearn.org/activations/#prelu)

![../images/node_prelu.png](data:image/png;base64,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)

Slice

[Tensorflow Slice
Reference](https://www.tensorflow.org/api_docs/python/tf/split)

![../images/node_slice.png](data:image/png;base64,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)

Reshape

[Tensorflow Reshape
Reference](https://www.tensorflow.org/api_docs/python/tf/reshape)

![../images/node_reshape.png](data:image/png;base64,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)

Last Published: Jun 04, 2026

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