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@lajosdeme
Forked from stsievert/Centralized-PS.ipynb
Created December 6, 2023 23:44
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PyTorch MNIST parameter server
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This notebook implements a decentralized parameter server. Every worker holds onto a model, and they communicate gradients.\n",
"\n",
"Most of this is copied from PyTorch's MNIST example: https://github.com/pytorch/examples/blob/master/mnist/main.py. The top couple cells are copy/pasted from there."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"execution_count": 1,
"metadata": {
"image/png": {
"width": 400
}
},
"output_type": "execute_result"
}
],
"source": [
"from IPython.display import Image\n",
"Image('./decentralized.png', width=400)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from __future__ import print_function\n",
"import argparse\n",
"import torch\n",
"import torch.nn as nn\n",
"import torch.nn.functional as F\n",
"import torch.optim as optim\n",
"from torchvision import datasets, transforms"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"class Net(nn.Module):\n",
" def __init__(self):\n",
" super(Net, self).__init__()\n",
" self.conv1 = nn.Conv2d(1, 10, kernel_size=5)\n",
" self.conv2 = nn.Conv2d(10, 20, kernel_size=5)\n",
" self.conv2_drop = nn.Dropout2d()\n",
" self.fc1 = nn.Linear(320, 50)\n",
" self.fc2 = nn.Linear(50, 10)\n",
"\n",
" def forward(self, x):\n",
" x = F.relu(F.max_pool2d(self.conv1(x), 2))\n",
" x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))\n",
" x = x.view(-1, 320)\n",
" x = F.relu(self.fc1(x))\n",
" x = F.dropout(x, training=self.training)\n",
" x = self.fc2(x)\n",
" return F.log_softmax(x, dim=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This noteboko depends on PyTorch 0.4.1 for serialization of torch.Device objects: https://github.com/pytorch/pytorch/pull/7713 "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from types import SimpleNamespace\n",
"args = SimpleNamespace(batch_size=64, test_batch_size=1000,\n",
" epochs=2, lr=0.01, momentum=0.5,\n",
" no_cuda=True, seed=42, log_interval=80)\n",
" \n",
"use_cuda = not args.no_cuda and torch.cuda.is_available()\n",
"torch.manual_seed(args.seed)\n",
"\n",
"kwargs = {'num_workers': 1, 'pin_memory': True} if use_cuda else {}\n",
"train_loader = torch.utils.data.DataLoader(\n",
" datasets.MNIST('../data', train=True, download=True,\n",
" transform=transforms.Compose([\n",
" transforms.ToTensor(),\n",
" transforms.Normalize((0.1307,), (0.3081,))\n",
" ])),\n",
" batch_size=args.batch_size, shuffle=True, **kwargs)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table style=\"border: 2px solid white;\">\n",
"<tr>\n",
"<td style=\"vertical-align: top; border: 0px solid white\">\n",
"<h3>Client</h3>\n",
"<ul>\n",
" <li><b>Scheduler: </b>tcp://127.0.0.1:49822\n",
" <li><b>Dashboard: </b><a href='http://127.0.0.1:49823/status' target='_blank'>http://127.0.0.1:49823/status</a>\n",
"</ul>\n",
"</td>\n",
"<td style=\"vertical-align: top; border: 0px solid white\">\n",
"<h3>Cluster</h3>\n",
"<ul>\n",
" <li><b>Workers: </b>8</li>\n",
" <li><b>Cores: </b>8</li>\n",
" <li><b>Memory: </b>17.18 GB</li>\n",
"</ul>\n",
"</td>\n",
"</tr>\n",
"</table>"
],
"text/plain": [
"<Client: scheduler='tcp://127.0.0.1:49822' processes=8 cores=8>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from distributed import Client\n",
"import distributed as d\n",
"client = Client()\n",
"client"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The function `compute_grad` is (almost) copy pasted from the example. The differences are that...\n",
"\n",
"* it does not loop over all `(data, target)` item. This fucntion only consumes `(data, target)` item\n",
"* it does not call `optimizer.step`. It only computes the gradient, and returns the model (which holds the modified gradients)."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def compute_grad(model, data, target, optimizer, args, device):\n",
" data, target = data.to(device), target.to(device)\n",
" optimizer.zero_grad()\n",
" output = model(data)\n",
" loss = F.nll_loss(output, target)\n",
" loss.backward()\n",
" # optimizer.step() # do not include this\n",
" return {k: p.grad for k, p in model.named_parameters()}"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"import toolz\n",
"from pprint import pprint\n",
"from time import time\n",
"import numpy as np\n",
"\n",
"class Worker:\n",
" def __init__(self, model, train_loader,\n",
" args, worker_id=0, num_workers=1):\n",
" self.args = args\n",
" torch.manual_seed(args.seed + worker_id)\n",
" \n",
" self.device = torch.device(\"cuda\" if use_cuda else \"cpu\")\n",
" self.model = model.to(self.device)\n",
" self.optimizer = optim.SGD(model.parameters(), lr=args.lr, momentum=args.momentum)\n",
" \n",
" self.grads = []\n",
" self.worker_id = worker_id\n",
" self.num_workers = num_workers\n",
" \n",
" self.train_loader = train_loader\n",
" \n",
" @property\n",
" def _model(self):\n",
" return self.model\n",
" \n",
" def compute_gradients(self):\n",
" data, target = next(iter(self.train_loader))\n",
" self.grad = compute_grad(self.model, data, target, self.optimizer,\n",
" self.args, self.device)\n",
" return True\n",
" \n",
" def send(self, worker):\n",
" worker.recv(self.grad)\n",
" \n",
" def recv(self, grad):\n",
" self.grads += [grad]\n",
" return True\n",
" \n",
" def apply_gradients(self):\n",
" # This is a little verbose; no all-reduce, list of grads, etc\n",
" if len(self.grads) != self.num_workers:\n",
" return None\n",
" \n",
" grads = {k: sum([named_grads[k] for named_grads in self.grads])\n",
" for k in self.grads[0]}\n",
" self.grads = []\n",
" \n",
" for name, param in self.model.named_parameters():\n",
" param.grad = grads[name]\n",
" \n",
" self.optimizer.step()\n",
" return True"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<Actor: Worker, key=Worker-cf4e23a5-e8cd-44f6-9659-17e9cf38516a>,\n",
" <Actor: Worker, key=Worker-879bf354-9983-4118-a7ff-a5f1398134cd>,\n",
" <Actor: Worker, key=Worker-e7862e16-8c60-45b4-983a-a7e24502afd1>,\n",
" <Actor: Worker, key=Worker-db13d370-f944-45c0-97d4-5ea276aa169a>]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"num_workers = 4\n",
"model = Net()\n",
"\n",
"model, train_loader = client.scatter([model, train_loader])\n",
"futures = [client.submit(Worker, model, train_loader, args,\n",
" worker_id=i, num_workers=num_workers,\n",
" actor=True)\n",
" for i in range(num_workers)]\n",
"\n",
"workers = client.gather(futures)\n",
"workers"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"10\n"
]
}
],
"source": [
"meta = {'apply_grads': 0, 'compute_grad': 0, 'comm_grad': 0}\n",
"\n",
"train_start = time()\n",
"iters = 20\n",
"for k in range(iters):\n",
" if k % 10 == 0:\n",
" print(k)\n",
" # compute gradient\n",
" start = time()\n",
" futures = [worker.compute_gradients() for worker in workers]\n",
" [f.result() for f in futures]\n",
" meta['compute_grad'] += time() - start\n",
"\n",
" # communication scheme\n",
" # here, all-gather, but could (and should) be all-reduce\n",
" start = time()\n",
" futures = []\n",
" for i, w1 in enumerate(workers):\n",
" for j, w2 in enumerate(workers):\n",
" futures += [w1.send(w2)]\n",
" [f.result() for f in futures]\n",
" meta['comm_grad'] += time() - start\n",
"\n",
" # apply the gradients\n",
" start = time()\n",
" futures = [worker.apply_gradients() for worker in workers]\n",
" [f.result() for f in futures]\n",
" meta['apply_grads'] += time() - start\n",
" \n",
"\n",
"meta = {k: v / iters for k, v in meta.items()}\n",
"params = [np.prod(tuple(p.size())) for p in Net().parameters()]\n",
"meta['params'] = sum(params)\n",
"meta['avg_step_time'] = (time() - train_start) / iters\n",
"meta = [meta]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x117e424a8>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import pandas as pd\n",
"df = pd.DataFrame(meta)\n",
"show = df.groupby('params').mean()\n",
"show.plot.bar()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"models = [worker._model for worker in workers]\n",
"params = [dict(model.named_parameters()) for model in models]\n",
"named_params = {k: [param[k] for param in params]\n",
" for k in params[0]}\n",
"for k, params in named_params.items():\n",
" p0 = params[0]\n",
" rel_errors = [torch.norm(p0 - p) / torch.norm(p)\n",
" for p in params]\n",
" rel_errors = [e.item() for e in rel_errors]\n",
" if max(rel_errors) > 2e-7:\n",
" print(max(rel_errors))\n",
" assert False"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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