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@joshfp
Created November 5, 2018 08:02
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Walker SGD
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{
"cells": [
{
"metadata": {},
"cell_type": "markdown",
"source": "# \"Walker SGD\""
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "import torch\nimport numpy as np\nimport matplotlib.pyplot as plt",
"execution_count": 1,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "torch.manual_seed(17);\nuse_gpu = True",
"execution_count": 2,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Linear Regression Problem"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "n = 100",
"execution_count": 3,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "x = torch.ones(n, 2)\nx[:,0].uniform_(-1., 1);",
"execution_count": 4,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "w_y = torch.tensor([3., 2]); w_y",
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 5,
"data": {
"text/plain": "tensor([3., 2.])"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "y = x@w_y + torch.rand(n)\ny = y[:,None]",
"execution_count": 6,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "plt.scatter(x[:,0], y);",
"execution_count": 7,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "def mse(y_hat, y): return ((y_hat-y)**2).mean(0)",
"execution_count": 8,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "device = torch.device('cuda') if use_gpu and torch.cuda.is_available() else torch.device('cpu')\nx = x.to(device)\ny = y.to(device)",
"execution_count": 9,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "# initial weights\nw0 = torch.rand(2) * 1000 - 500; w0",
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 10,
"data": {
"text/plain": "tensor([ 214.6787, -491.5229])"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## \"Stepper SGD\" (vanilla SGD)"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "def train_stepper_sgd(w0, lr, n_epochs=100, min_loss=0.1, verbose=True):\n w = w0[:,None].clone().to(device).requires_grad_()\n if verbose: print('Epoch\\tLoss')\n \n for i in range(n_epochs):\n y_hat = x@w\n loss = mse(y, y_hat)\n loss.backward()\n\n with torch.no_grad():\n w -= lr * w.grad\n w.grad.zero_()\n if verbose: print(f'{i+1}\\t{loss.item():.3f}')\n if loss.item() < min_loss: break\n print(f'Final loss: {loss.item():.3f} in {i+1} epochs.')",
"execution_count": 11,
"outputs": []
},
{
"metadata": {
"trusted": true,
"scrolled": true
},
"cell_type": "code",
"source": "lr = 0.3\ntrain_stepper_sgd(w0, lr)",
"execution_count": 12,
"outputs": [
{
"output_type": "stream",
"text": "Epoch\tLoss\n1\t287112.469\n2\t44595.219\n3\t7959.141\n4\t2058.046\n5\t874.773\n6\t498.912\n7\t313.233\n8\t201.491\n9\t130.359\n10\t84.459\n11\t54.747\n12\t35.500\n13\t23.030\n14\t14.951\n15\t9.716\n16\t6.324\n17\t4.127\n18\t2.703\n19\t1.780\n20\t1.183\n21\t0.795\n22\t0.544\n23\t0.382\n24\t0.277\n25\t0.208\n26\t0.164\n27\t0.135\n28\t0.117\n29\t0.105\n30\t0.097\nFinal loss: 0.097 in 30 epochs.\n",
"name": "stdout"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## \"Walker SGD\""
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "def train_walker_sgd(w0, lrs, n_epochs=100, min_loss=0.1, verbose=True, record=False):\n lrs = torch.tensor(lrs, dtype=torch.float32).to(device)\n n_lrs = lrs.size(0)\n w = w0.repeat(n_lrs, 1).transpose(0,1).clone().to(device).requires_grad_()\n if record: rec = []\n \n if verbose: print('Epoch\\tLR\\tLoss')\n \n for i in range(n_epochs):\n w_rec = w.data\n y_hat = x@w\n losses = mse(y, y_hat)\n\n # identify the best learning rate\n bst_lr_idx = losses.argmin()\n bst_loss = losses[bst_lr_idx] \n bst_loss.backward()\n\n with torch.no_grad():\n # take the weights of the best lr and copy them over the others lrs,\n # dismissing weights from non-optimal lrs.\n w_grad = w.grad[:,bst_lr_idx].repeat(n_lrs, 1).transpose(0,1)\n w.data = w.data[:,bst_lr_idx].repeat(n_lrs, 1).transpose(0,1)\n w.data -= lrs * w_grad\n w.grad.zero_()\n \n if record: rec.append((w_rec.to('cpu'), losses.data.to('cpu'), bst_lr_idx.to('cpu')))\n if verbose: print(f'{i+1}\\t{lrs[bst_lr_idx].item():.2f}\\t{bst_loss.item():.3f}')\n if bst_loss.item() < min_loss: break\n\n print(f'Final loss: {bst_loss.item():.3f} in {i+1} epochs.')\n if record: \n rec = list(zip(*rec))\n wgts = np.stack(rec[0])\n loss = np.stack(rec[1])\n best = np.stack(rec[2])\n return wgts, loss, best",
"execution_count": 14,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "lrs = np.arange(0.1, 1, 0.1)\ntrain_walker_sgd(w0, lrs);",
"execution_count": 15,
"outputs": [
{
"output_type": "stream",
"text": "Epoch\tLR\tLoss\n1\t0.10\t287112.469\n2\t0.50\t2092.768\n3\t0.90\t459.608\n4\t0.70\t122.471\n5\t0.80\t32.740\n6\t0.70\t8.685\n7\t0.80\t2.412\n8\t0.70\t0.689\n9\t0.70\t0.247\n10\t0.80\t0.126\n11\t0.70\t0.094\nFinal loss: 0.094 in 11 epochs.\n",
"name": "stdout"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Visualizing \"Walker SGD\""
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "from mpl_toolkits import mplot3d\nfrom matplotlib import animation\nplt.rc('animation', html='html5')",
"execution_count": 16,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "def loss_wrt_wgts(w1, w2):\n w = torch.Tensor([w1, w2]).to(device)\n y_hat = x@w\n loss = mse(y_hat[:,None], y)\n return loss.item()\nloss_wgts = np.vectorize(loss_wrt_wgts)\n\nw0_range = np.linspace(-20, 20, 50)\nw1_range = np.linspace(-20, 20, 50)\nmesh = np.meshgrid(w0_range, w1_range)\nloss_mesh = loss_wgts(*mesh)",
"execution_count": 17,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "w0 = torch.tensor([-19., -19])\nlrs = np.linspace(0.1, 1, 7)\nwgts, loss, best = train_walker_sgd(w0, lrs, record=True)",
"execution_count": 18,
"outputs": [
{
"output_type": "stream",
"text": "Epoch\tLR\tLoss\n1\t0.10\t507.883\n2\t0.55\t94.030\n3\t1.00\t16.269\n4\t0.70\t4.323\n5\t0.70\t1.234\n6\t0.85\t0.380\n7\t0.70\t0.160\n8\t0.70\t0.103\n9\t0.85\t0.088\nFinal loss: 0.088 in 9 epochs.\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "fig = plt.figure(figsize=(12,10))\nax = plt.axes(projection='3d')\n\nax.plot_surface(*mesh, loss_mesh, cmap='viridis', alpha=0.8)\nline0, = ax.plot3D([], [], [], c='r', marker='o', label='Current walk') \nline1, = ax.plot3D([], [], [], c='b', marker='o', label='Learning curve')\nline2, = ax.plot3D([], [], [], c='r', marker='*', markersize=20, label='Best step in walk', linewidth=0)\n\nax.set_xlabel('w0'); ax.set_ylabel('w1'); ax.set_zlabel('Loss')\nfig.suptitle(f'\"Walker SGD\"', fontsize=22)\nax.view_init(30, 20)\nax.legend()\nfig.tight_layout()\nplt.close()\n\ndef animate(i):\n if i > 0:\n line0.set_data(wgts[i,0], wgts[i,1])\n line0.set_3d_properties(loss[i])\n line2.set_data(wgts[i,0,best[i]], wgts[i,1,best[i]])\n line2.set_3d_properties(loss[i,best[i]])\n \n rng = range(i)\n line1.set_data(wgts[rng,0,best[:i]], wgts[rng,1,best[:i]])\n line1.set_3d_properties(loss[rng,best[:i]])\n \n return line0, line1, line2\n\nanimation.FuncAnimation(fig, animate, 6, interval=1000)",
"execution_count": 28,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 28,
"data": {
"text/plain": "<matplotlib.animation.FuncAnimation at 0x7fa6d003aac8>",
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SEGv4Adcxa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\nLaBgUuxQGOuD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GtR5z9Nu9edMsWvWTHJqwdZSTxZuEEwhSvclqk92VV05syH3vUGIC2mo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+grIyK8CWDNdC2rlMNK6Q+g2+HTdaErWdiYw52bqxS3nT6ekXroUY8LAiZWnZhBO3iJGjI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\nAZ6br4jV4HB2ip79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Your browser does not support the video tag.\n</video>"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## Benchmarking"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "n = 1000000\ntorch.manual_seed(17);",
"execution_count": 21,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "w0 = torch.rand(2) * 1000 - 500; w0",
"execution_count": 22,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 22,
"data": {
"text/plain": "tensor([-65.7588, 35.1096])"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### \"Walker SGD\""
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "lrs = np.linspace(0.1, 1, 10)\n%time train_walker_sgd(w0, lrs, verbose=False)",
"execution_count": 23,
"outputs": [
{
"output_type": "stream",
"text": "Final loss: 0.096 in 9 epochs.\nCPU times: user 21.2 ms, sys: 0 ns, total: 21.2 ms\nWall time: 5.2 ms\n",
"name": "stdout"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### \"Stepper SGD\" (vanilla SGD)"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "lr = 0.1\n%time train_stepper_sgd(w0, lr, verbose=False)",
"execution_count": 24,
"outputs": [
{
"output_type": "stream",
"text": "Final loss: 0.098 in 85 epochs.\nCPU times: user 99.7 ms, sys: 3.51 ms, total: 103 ms\nWall time: 25.6 ms\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "lr = 0.9\n%time train_stepper_sgd(w0, lr, verbose=False)",
"execution_count": 25,
"outputs": [
{
"output_type": "stream",
"text": "Final loss: 0.100 in 36 epochs.\nCPU times: user 13 ms, sys: 51 µs, total: 13.1 ms\nWall time: 12.2 ms\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "lr = 0.5\n%time train_stepper_sgd(w0, lr, verbose=False)",
"execution_count": 26,
"outputs": [
{
"output_type": "stream",
"text": "Final loss: 0.092 in 16 epochs.\nCPU times: user 2.09 ms, sys: 3.85 ms, total: 5.94 ms\nWall time: 5.35 ms\n",
"name": "stdout"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "lr = 0.7 # optimal learning rate\n%time train_stepper_sgd(w0, lr, verbose=False)",
"execution_count": 27,
"outputs": [
{
"output_type": "stream",
"text": "Final loss: 0.089 in 11 epochs.\nCPU times: user 4.01 ms, sys: 0 ns, total: 4.01 ms\nWall time: 3.6 ms\n",
"name": "stdout"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## End!"
}
],
"metadata": {
"_draft": {
"nbviewer_url": "https://gist.github.com/4eaff328eb27042169da4a54e4f8b017"
},
"gist": {
"id": "4eaff328eb27042169da4a54e4f8b017",
"data": {
"description": "Walker SGD",
"public": true
}
},
"kernelspec": {
"name": "conda-env-fastai-py",
"display_name": "Python [conda env:fastai]",
"language": "python"
},
"varInspector": {
"window_display": false,
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
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"kernels_config": {
"python": {
"library": "var_list.py",
"delete_cmd_prefix": "del ",
"delete_cmd_postfix": "",
"varRefreshCmd": "print(var_dic_list())"
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"r": {
"library": "var_list.r",
"delete_cmd_prefix": "rm(",
"delete_cmd_postfix": ") ",
"varRefreshCmd": "cat(var_dic_list()) "
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},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
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},
"language_info": {
"name": "python",
"version": "3.6.6",
"mimetype": "text/x-python",
"codemirror_mode": {
"name": "ipython",
"version": 3
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"pygments_lexer": "ipython3",
"nbconvert_exporter": "python",
"file_extension": ".py"
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"nbformat": 4,
"nbformat_minor": 2
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