Fixed requirements, refactored and formatted code in some examples (#567)

examples/frameworks/megengine/megengine_mnist.py

@@ -1,23 +1,28 @@
-#!/usr/bin/env python3
-# -*- coding:utf-8 -*-
-
 import argparse
 import os
+import sys
 from tempfile import gettempdir
+
 import numpy as np
 
-import megengine as mge
-import megengine.module as M
-import megengine.functional as F
-from megengine.optimizer import SGD
-from megengine.autodiff import GradManager
+try:
+    import megengine as mge
+    import megengine.functional as F
+    import megengine.module as M
+    from megengine.autodiff import GradManager
+    from megengine.data import DataLoader, RandomSampler
+    from megengine.data.dataset import MNIST
+    from megengine.data.transform import Compose, Normalize, Pad, ToMode
+    from megengine.optimizer import SGD
+except ImportError:
+    raise ImportError(
+        "megengine package is missing, you can install it using pip: pip install megengine"
+        if sys.version_info.minor <= 8
+        else "MegEngine does not support python version >= 3.9"
+    )
 
-from megengine.data import DataLoader, RandomSampler
-from megengine.data.transform import ToMode, Pad, Normalize, Compose
-from megengine.data.dataset import MNIST
-
-from tensorboardX import SummaryWriter
 from clearml import Task
+from tensorboardX import SummaryWriter
 
 
 class Net(M.Module):
@@ -55,11 +60,7 @@ def build_dataloader():
     train_dataset = MNIST(root=gettempdir(), train=True, download=True)
     dataloader = DataLoader(
         train_dataset,
-        transform=Compose([
-            Normalize(mean=0.1307*255, std=0.3081*255),
-            Pad(2),
-            ToMode('CHW'),
-        ]),
+        transform=Compose([Normalize(mean=0.1307 * 255, std=0.3081 * 255), Pad(2), ToMode("CHW"),]),
         sampler=RandomSampler(dataset=train_dataset, batch_size=64),
     )
     return dataloader
@@ -69,10 +70,7 @@ def train(dataloader, args):
     writer = SummaryWriter("runs")
     net = Net()
     net.train()
-    optimizer = SGD(
-        net.parameters(), lr=args.lr,
-        momentum=args.momentum, weight_decay=args.wd
-    )
+    optimizer = SGD(net.parameters(), lr=args.lr, momentum=args.momentum, weight_decay=args.wd)
     gm = GradManager().attach(net.parameters())
 
     epoch_length = len(dataloader)
@@ -90,28 +88,24 @@ def train(dataloader, args):
                 print("epoch:{}, iter:{}, loss:{}".format(epoch + 1, step, float(loss)))  # noqa
             writer.add_scalar("loss", float(loss), epoch * epoch_length + step)
         if (epoch + 1) % 5 == 0:
-            mge.save(net.state_dict(), os.path.join(gettempdir(), f"mnist_net_e{epoch + 1}.pkl")) # noqa
+            mge.save(
+                net.state_dict(), os.path.join(gettempdir(), f"mnist_net_e{epoch + 1}.pkl"),
+            )  # noqa
 
 
 def main():
-    task = Task.init(project_name='examples', task_name='megengine mnist train')  # noqa
+    task = Task.init(project_name="examples", task_name="megengine mnist train")  # noqa
 
-    parser = argparse.ArgumentParser(description='MegEngine MNIST Example')
+    parser = argparse.ArgumentParser(description="MegEngine MNIST Example")
     parser.add_argument(
-        '--epoch', type=int, default=10,
-        help='number of training epoch(default: 10)',
+        "--epoch", type=int, default=10, help="number of training epoch(default: 10)",
+    )
+    parser.add_argument("--lr", type=float, default=0.01, help="learning rate(default: 0.01)")
+    parser.add_argument(
+        "--momentum", type=float, default=0.9, help="SGD momentum (default: 0.9)",
     )
     parser.add_argument(
-        '--lr', type=float, default=0.01,
-        help='learning rate(default: 0.01)'
-    )
-    parser.add_argument(
-        '--momentum', type=float, default=0.9,
-        help='SGD momentum (default: 0.9)',
-    )
-    parser.add_argument(
-        '--wd', type=float, default=5e-4,
-        help='SGD weight decay(default: 5e-4)',
+        "--wd", type=float, default=5e-4, help="SGD weight decay(default: 5e-4)",
     )
 
     args = parser.parse_args()

examples/frameworks/megengine/requirements.txt

@@ -1,3 +1,3 @@
-MegEngine
+MegEngine ; python_version < '3.9'
 tensorboardX
-clearml
+clearml

examples/frameworks/pytorch/requirements.txt

@@ -3,4 +3,5 @@ tensorboardX
 tensorboard>=1.14.0
 torch>=1.1.0
 torchvision>=0.3.0
+tqdm
 clearml