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Generating Handwritten Digits on MNIST using GANs #161
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2f3532f
removed unnecessary files
swaingotnochill e4f0597
added initial notebook on gans
swaingotnochill e7fea91
added layers
swaingotnochill 8ff8b75
added pycache to gitignore
swaingotnochill f0ea62c
Merge branch 'master' of https://github.com/mlpack/examples
swaingotnochill 8f99b26
master sync
swaingotnochill 4685f83
update on gan mnist work
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353 changes: 353 additions & 0 deletions
353
...ing_hand_written_digits_mnist_with_gan/generating_handwritten_digits_mnist_with_gan.ipynb
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,353 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "id": "c23013fc", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "#include<mlpack/xeus-cling.hpp>\n", | ||
| "#include<mlpack/core.hpp>\n", | ||
| "#include<mlpack/core/data/split_data.hpp>\n", | ||
| "#include<mlpack/methods/ann/layer/layer.hpp>\n", | ||
| "#include<mlpack/methods/ann/ffn.hpp>\n", | ||
| "#include<bits/stdc++.h>\n", | ||
| "#include<ensmallen.hpp>" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "id": "ad7ab4c6", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "using namespace mlpack;\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "id": "0c8af9e2", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "using namespace mlpack::ann;" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "id": "ff1b2e2f", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "using namespace arma;" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 5, | ||
| "id": "4834841f", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "using namespace std;" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 6, | ||
| "id": "d1dc9cb6", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "using namespace ens;" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 7, | ||
| "id": "7ed7a903", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "arma::Row<size_t> getLabels(arma::mat predOut){\n", | ||
| " arma::Row<size_t> predLabels(predOut.n_cols);\n", | ||
| " for( arma::uword i = 0; i < predOut.n_cols; ++i){\n", | ||
| " predLabels(i) = predOut.col(i).index_max();\n", | ||
| " }\n", | ||
| " return predLabels;\n", | ||
| "}" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 8, | ||
| "id": "131fe748", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "constexpr double RATIO = 0.1;\n", | ||
| "constexpr int MAX_ITERATIONS = 0;\n", | ||
| "constexpr double STEP_SIZE = 1.2e-3;\n", | ||
| "constexpr int BATCH_SIZE = 50;" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 9, | ||
| "id": "697a8d63", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "arma::mat dataset;" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 10, | ||
| "id": "64ee4e72", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "data::Load(\"/home/viole/swaingotnochill/examples/generating_hand_written_digits_mnist_with_gan/digit-recognizer/train.csv\", dataset, true);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 11, | ||
| "id": "d8a3d8da", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "arma::mat train, valid;" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 12, | ||
| "id": "da10fdac", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "data::Split(dataset, train, valid, RATIO);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 13, | ||
| "id": "a6a484e7", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "const arma::mat trainX = train.submat(1, 0, train.n_rows - 1, train.n_cols - 1);\n", | ||
| "const arma::mat validX = valid.submat(1, 0, valid.n_rows - 1, valid.n_cols - 1);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 14, | ||
| "id": "db267de6", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "const arma::mat trainY = train.row(0);\n", | ||
| "const arma::mat validY = valid.row(0);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 15, | ||
| "id": "7eb2907b", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "FFN<NegativeLogLikelihood<>, RandomInitialization> model;" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 16, | ||
| "id": "ffc66454", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "model.Add<mlpack::ann::Convolution<>> (1,6,5,5,1,1,0,0,28,28);\n", | ||
| " " | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 17, | ||
| "id": "03d0646a", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "model.Add<LeakyReLU<>>();" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 18, | ||
| "id": "2fff115e", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "model.Add<MaxPooling<>>(2,\n", | ||
| " 2,\n", | ||
| " 2,\n", | ||
| " 2,\n", | ||
| " true);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 19, | ||
| "id": "462e4ce2", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "model.Add<Convolution<>>(6,\n", | ||
| " 16,\n", | ||
| " 5,\n", | ||
| " 5,\n", | ||
| " 1,\n", | ||
| " 1,\n", | ||
| " 0,\n", | ||
| " 0,\n", | ||
| " 12,\n", | ||
| " 12);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 20, | ||
| "id": "73033233", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "model.Add<LeakyReLU<>>();" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 21, | ||
| "id": "ee5d88cc", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "model.Add<LeakyReLU<>>();" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 22, | ||
| "id": "7859b83e", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "model.Add<MaxPooling<>>(2,2,2,2,true);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 23, | ||
| "id": "f423475d", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "model.Add<Linear<>>(16*4*4, 10);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 24, | ||
| "id": "369063ba", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "model.Add<LogSoftMax<>>();" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 25, | ||
| "id": "17dfcdef", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "ens::Adam optimizer(STEP_SIZE,\n", | ||
| " BATCH_SIZE,\n", | ||
| " 0.9,\n", | ||
| " 0.999,\n", | ||
| " 1e-8,\n", | ||
| " MAX_ITERATIONS,\n", | ||
| " 1e-8,\n", | ||
| " true);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 26, | ||
| "id": "c52947c7", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stderr", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "\n", | ||
| "error: Mat::operator(): index out of bounds\n" | ||
| ] | ||
| }, | ||
| { | ||
| "ename": "Standard Exception", | ||
| "evalue": "Mat::operator(): index out of bounds", | ||
| "output_type": "error", | ||
| "traceback": [ | ||
| "Standard Exception: Mat::operator(): index out of bounds" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "model.Train(trainX,\n", | ||
| " trainY,\n", | ||
| " optimizer,\n", | ||
| " ens::PrintLoss(),\n", | ||
| " ens::ProgressBar(),\n", | ||
| " ens::EarlyStopAtMinLoss(\n", | ||
| " [&](const arma::mat&){\n", | ||
| " double validationLoss = model.Evaluate(validX, validY);\n", | ||
| " std::cout << \"Validation Loss\" << validationLoss << \".\" << \"\\n\";\n", | ||
| " return validationLoss;\n", | ||
| " }))" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "d6060587", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "C++14", | ||
| "language": "C++14", | ||
| "name": "xcpp14" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": "text/x-c++src", | ||
| "file_extension": ".cpp", | ||
| "mimetype": "text/x-c++src", | ||
| "name": "c++", | ||
| "version": "14" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } | ||
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generating_hand_written_digits_mnist_with_gan/mnist_first250_training_4s_and_9s.arm
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Could you try this?
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I tried but it doesn't seems to work too.
input_line_65:2:16: error: no matching constructor for initialization of 'mlpack::ann::Convolution<>' model.Add(new mlpack::ann::Convolution<>(1,6,5,5,1,1,0,0,28,28)); ^ ~~~~~~~~~~~~~~~~~~~~~ /home/viole/anaconda3/envs/notebook/include/mlpack/methods/ann/layer/layer_types.hpp:172:7: note: candidate constructor (the implicit copy constructor) not viable: requires 1 argument, but 10 were provided class Convolution; ^ /home/viole/anaconda3/envs/notebook/include/mlpack/methods/ann/layer/layer_types.hpp:172:7: note: candidate constructor (the implicit move constructor) not viable: requires 1 argument, but 10 were providedNo matching constructor..
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I just tested it on lab.mlpack.org and there it works fine, I had some problems with namespaces in the past, can you put each namespace into a separate cell?