abhinavs95 commented on a change in pull request #14405: [MXNet-1343][WIP][Fit API]Add CNN integration test for fit() API URL: https://github.com/apache/incubator-mxnet/pull/14405#discussion_r265270422
########## File path: tests/nightly/estimator/test_estimator_cnn_gpu.py ########## @@ -0,0 +1,96 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +# Test gluon estimator on GPU using ResNet18 + +import os +import sys +import mxnet as mx +from mxnet import gluon +from mxnet.gluon import data +from mxnet.gluon.estimator import estimator, event_handler +from mxnet.gluon.model_zoo import vision + +def load_data_mnist(batch_size, resize=None, num_workers=None, + root=os.path.join('~', '.mxnet', 'datasets', 'mnist')): + ''' + Load MNIST dataset + ''' + root = os.path.expanduser(root) # Expand the user path '~'. + transformer = [] + if resize: + transformer += [data.vision.transforms.Resize(resize)] + transformer += [data.vision.transforms.ToTensor()] + transformer = data.vision.transforms.Compose(transformer) + mnist_train = data.vision.MNIST(root=root, train=True) + mnist_test = data.vision.MNIST(root=root, train=False) + + if num_workers is None: + num_workers = 0 if sys.platform.startswith('win32') else 4 + + train_iter = data.DataLoader( + mnist_train.transform_first(transformer), batch_size, shuffle=True, + num_workers=num_workers) + test_iter = data.DataLoader( + mnist_test.transform_first(transformer), batch_size, shuffle=False, + num_workers=num_workers) + return train_iter, test_iter + +def test_estimator(): + ''' + Test estimator by training resnet18_v1 for 5 epochs on MNIST and verify accuracy + ''' + model_name = 'resnet18_v1' + batch_size = 128 + num_epochs = 5 + input_size = 224 + lr = 0.001 + # Set context + if mx.context.num_gpus() > 0: + context = mx.gpu(0) + else: + context = mx.cpu() + # Get model + net = vision.get_model(model_name, classes=10) + # Load train and validation data + train_data, test_data = load_data_mnist(batch_size, resize=input_size) + # Define loss and evaluation metrics + loss = gluon.loss.SoftmaxCrossEntropyLoss() + acc = mx.metric.Accuracy() + # Hybridize and initialize net + net.hybridize() + net.initialize(mx.init.MSRAPrelu(), ctx=context) + # Define trainer + trainer = gluon.Trainer(net.collect_params(), 'sgd', {'learning_rate': lr}) + # Define estimator + est = estimator.Estimator(net=net, + loss=loss, + metrics=acc, + trainers=trainer, + context=context) + # Call fit() to begin training + logging_handler = event_handler.LoggingHandler(est, model_name+'_log', model_name+'_log') Review comment: same as above ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
