{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# A CNN Mnist Model" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Installing packages:\n", "\t.package(path: \"/home/ubuntu/fastai_docs/dev_swift/FastaiNotebook_05b_early_stopping\")\n", "\t\tFastaiNotebook_05b_early_stopping\n", "With SwiftPM flags: []\n", "Working in: /tmp/tmpyihp3nn8/swift-install\n", "Fetching https://github.com/mxcl/Path.swift\n", "Fetching https://github.com/JustHTTP/Just\n", "Completed resolution in 3.15s\n", "Cloning https://github.com/mxcl/Path.swift\n", "Resolving https://github.com/mxcl/Path.swift at 0.16.2\n", "Cloning https://github.com/JustHTTP/Just\n", "Resolving https://github.com/JustHTTP/Just at 0.7.1\n", "Compile Swift Module 'Just' (1 sources)\n", "Compile Swift Module 'Path' (9 sources)\n", "Compile Swift Module 'FastaiNotebook_05b_early_stopping' (10 sources)\n", "Compile Swift Module 'jupyterInstalledPackages' (1 sources)\n", "Linking ./.build/x86_64-unknown-linux/debug/libjupyterInstalledPackages.so\n", "Initializing Swift...\n", "Installation complete!\n" ] } ], "source": [ "%install '.package(path: \"$cwd/FastaiNotebook_05b_early_stopping\")' FastaiNotebook_05b_early_stopping" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load data" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "('inline', 'module://ipykernel.pylab.backend_inline')\n" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import FastaiNotebook_05b_early_stopping\n", "%include \"EnableIPythonDisplay.swift\"\n", "IPythonDisplay.shell.enable_matplotlib(\"inline\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "// export\n", "import Path\n", "import TensorFlow\n", "import Python" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "let plt = Python.import(\"matplotlib.pyplot\")" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "let data = mnistDataBunch(flat: false, bs: 512)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Batch size: 512\r\n", "Example side size: 28\r\n", "Class count: 512\r\n" ] } ], "source": [ "let firstBatch = data.train.first(where: { _ in true })!\n", "let batchShape = firstBatch.xb.shape\n", "let batchSize = batchShape.dimensions[0]\n", "let exampleSideSize = batchShape.dimensions[1]\n", "assert(exampleSideSize == batchShape.dimensions[2])\n", "print(\"Batch size: \\(batchSize)\")\n", "print(\"Example side size: \\(exampleSideSize)\")\n", "\n", "let classCount = firstBatch.yb.shape.dimensions[0]\n", "print(\"Class count: \\(classCount)\")" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "▿ TensorShape\n", " ▿ dimensions : 3 elements\n", " - 0 : 512\n", " - 1 : 28\n", " - 2 : 28\n" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "firstBatch.xb.shape" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "// export\n", "extension Learner {\n", " public class AddChannel: Delegate {\n", " public override func batchWillStart(learner: Learner) {\n", " learner.currentInput = learner.currentInput!.expandingShape(at: -1)\n", " }\n", " }\n", " \n", " public func makeAddChannel() -> AddChannel { return AddChannel() }\n", "}" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "//export \n", "public func conv(_ cIn: Int, _ cOut: Int, ks: Int = 3, stride: Int = 2) -> FAConv2D {\n", " return FAConv2D(filterShape: (ks, ks, cIn, cOut), \n", " strides: (stride,stride), \n", " padding: .same, \n", " activation: relu)\n", "}\n", "\n", "public struct CnnModel: Layer {\n", " public var convs: [FAConv2D]\n", " public var pool = FAAdaptiveAvgPool2D()\n", " public var flatten = Flatten()\n", " public var linear: FADense\n", " \n", " public init(channelIn: Int, nOut: Int, filters: [Int]){\n", " convs = []\n", " let allFilters = [channelIn] + filters\n", " for i in 0..(inputSize: filters.last!, outputSize: nOut)\n", " }\n", " \n", " @differentiable\n", " public func applied(to input: TF) -> TF {\n", " return input.sequenced(through: convs, pool, flatten, linear)\n", " }\n", "}" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "let model = CnnModel(channelIn: 1, nOut: 10, filters: [8, 16, 32, 32])" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "TensorShape(dimensions: [512, 10])\r\n", "[-0.0056363903, -0.0055124904, 0.003962202, 0.00024041766, 0.0010704098, 0.012630586,\r\n", " -0.01890578, -0.012497755, -0.0075372434, -0.001092382]\r\n" ] } ], "source": [ "// Test that data goes through the model as expected.\n", "let predictions = model.applied(to: firstBatch.xb.expandingShape(at: -1))\n", "print(predictions.shape)\n", "print(predictions[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Compare training on CPU and GPU" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "let opt = SimpleSGD(learningRate: 0.4)\n", "func modelInit() -> CnnModel { return CnnModel(channelIn: 1, nOut: 10, filters: [8, 16, 32, 32]) }\n", "let learner = Learner(data: data, lossFunction: softmaxCrossEntropy, optimizer: opt, initializingWith: modelInit)\n", "let recorder = learner.makeDefaultDelegates(metrics: [accuracy])\n", "learner.addDelegates([learner.makeNormalize(mean: mnistStats.mean, std: mnistStats.std),\n", " learner.makeAddChannel()])" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0: [0.3500186, 0.8953] \n", "4725.451923 ms \n" ] } ], "source": [ "// This happens on the GPU (if you have one and it's configured correctly).\n", "// I tried this on a GCE 8vCPU 30GB + Tesla P100:\n", "// - time: ~4.3s\n", "// - nvidia-smi shows ~10% GPU-Util while this is running\n", "time {\n", " try! learner.fit(1)\n", "}" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0: [0.1639871, 0.9526] \n", "6769.385988 ms \n" ] } ], "source": [ "// This happens on the CPU.\n", "// I tried this on a GCE 8vCPU 30GB + Tesla P100:\n", "// - time: ~6.3s\n", "// - nvidia-smi shows 0% GPU-Util while this is running\n", "time {\n", " withDevice(.cpu) {\n", " try! learner.fit(1)\n", " }\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Collect Layer Activation Statistics" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "class ActivationStatistics: LayerDelegate> {\n", " var activationMeans: [Float] = []\n", " var activationStds: [Float] = [] \n", " override func didProduceActivation(_ activation: Tensor) {\n", " activationMeans.append(activation.mean().scalar!)\n", " activationStds.append(activation.standardDeviation().reshaped(to: []).scalar!)\n", " }\n", "}" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "extension KeyPathIterable { \n", " mutating func initializeLayerDelegates(with initializer: () -> LayerDelegate) {\n", " for kp in recursivelyAllWritableKeyPaths(to: LayerDelegate.self) {\n", " self[keyPath: kp] = initializer()\n", " }\n", " }\n", " \n", " func layerDelegates>(havingType: D.Type) -> [D] {\n", " var result: [D] = []\n", " for kp in recursivelyAllWritableKeyPaths(to: LayerDelegate.self) {\n", " guard let d = self[keyPath: kp] as? D else { continue }\n", " result.append(d)\n", " }\n", " return result\n", " }\n", "}" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "let learner = Learner(data: data, lossFunction: softmaxCrossEntropy, optimizer: opt, initializingWith: modelInit)\n", "let recorder = learner.makeDefaultDelegates(metrics: [accuracy])\n", "learner.addDelegates([learner.makeNormalize(mean: mnistStats.mean, std: mnistStats.std),\n", " learner.makeAddChannel()])\n", "\n", "learner.model.initializeLayerDelegates(with: { ActivationStatistics() })" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0: [0.3566188, 0.8989] \n", "Epoch 1: [0.16688569, 0.9504] \n", "9983.915673 ms \n" ] } ], "source": [ "// This LayerDelegate stuff slows it down to ~6s/epoch.\n", "time {\n", " try! learner.fit(2)\n", "}" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "None\n" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "let activationStatistics = learner.model.layerDelegates(havingType: ActivationStatistics.self)\n", "for stats in activationStatistics {\n", " plt.plot(stats.activationMeans)\n", "}\n", "plt.legend(Array(1...activationStatistics.count))\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "None\n" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "for stats in activationStatistics {\n", " plt.plot(stats.activationStds)\n", "}\n", "plt.legend(Array(1...activationStatistics.count))\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Export" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "notebookToScript(fname: (Path.cwd / \"06_cuda.ipynb\").string)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Swift", "language": "swift", "name": "swift" }, "language_info": { "file_extension": ".swift", "mimetype": "text/x-swift", "name": "swift", "version": "" } }, "nbformat": 4, "nbformat_minor": 2 }