From 587561f7b694318f85232f1b7aa1b9ea9b2dc61e Mon Sep 17 00:00:00 2001 From: lichenever Date: Thu, 4 Jun 2020 21:11:31 +0800 Subject: [PATCH] fix_distributed_training_doc bug --- .../advanced_use/distributed_training.md | 31 +++++++++---------- .../advanced_use/distributed_training.md | 31 +++++++++---------- 2 files changed, 30 insertions(+), 32 deletions(-) diff --git a/tutorials/source_en/advanced_use/distributed_training.md b/tutorials/source_en/advanced_use/distributed_training.md index 8d45551e76..4c61f175a3 100644 --- a/tutorials/source_en/advanced_use/distributed_training.md +++ b/tutorials/source_en/advanced_use/distributed_training.md @@ -256,11 +256,13 @@ device_id = int(os.getenv('DEVICE_ID')) context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") context.set_context(device_id=device_id) # set device_id -def test_train_cifar(num_classes=10, epoch_size=10): +def test_train_cifar(epoch_size=10): context.set_auto_parallel_context(parallel_mode=ParallelMode.AUTO_PARALLEL, mirror_mean=True) loss_cb = LossMonitor() - dataset = create_dataset(epoch_size) - net = resnet50(32, num_classes) + dataset = create_dataset(data_path, epoch_size) + batch_size = 32 + num_classes = 10 + net = resnet50(batch_size, num_classes) loss = SoftmaxCrossEntropyExpand(sparse=True) opt = Momentum(filter(lambda x: x.requires_grad, net.get_parameters()), 0.01, 0.9) model = Model(net, loss_fn=loss, optimizer=opt) @@ -342,17 +344,14 @@ The running time is about 5 minutes, which is mainly occupied by operator compil Log files are saved in the device directory. The env.log file records environment variable information. The train.log file records the loss function information. The following is an example: ``` -resnet50_distributed_training.py::test_train_feed ===============ds_num 195 -global_step: 194, loss: 1.997 -global_step: 389, loss: 1.655 -global_step: 584, loss: 1.723 -global_step: 779, loss: 1.807 -global_step: 974, loss: 1.417 -global_step: 1169, loss: 1.195 -global_step: 1364, loss: 1.238 -global_step: 1559, loss: 1.456 -global_step: 1754, loss: 0.987 -global_step: 1949, loss: 1.035 -end training -PASSED +epoch: 1 step: 156, loss is 2.0084016 +epoch: 2 step: 156, loss is 1.6407638 +epoch: 3 step: 156, loss is 1.6164391 +epoch: 4 step: 156, loss is 1.6838071 +epoch: 5 step: 156, loss is 1.6320667 +epoch: 6 step: 156, loss is 1.3098773 +epoch: 7 step: 156, loss is 1.3515002 +epoch: 8 step: 156, loss is 1.2943741 +epoch: 9 step: 156, loss is 1.2316195 +epoch: 10 step: 156, loss is 1.1533381 ``` diff --git a/tutorials/source_zh_cn/advanced_use/distributed_training.md b/tutorials/source_zh_cn/advanced_use/distributed_training.md index dab0586678..4ca5fb796c 100644 --- a/tutorials/source_zh_cn/advanced_use/distributed_training.md +++ b/tutorials/source_zh_cn/advanced_use/distributed_training.md @@ -254,11 +254,13 @@ device_id = int(os.getenv('DEVICE_ID')) context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") context.set_context(device_id=device_id) # set device_id -def test_train_cifar(num_classes=10, epoch_size=10): +def test_train_cifar(epoch_size=10): context.set_auto_parallel_context(parallel_mode=ParallelMode.AUTO_PARALLEL, mirror_mean=True) loss_cb = LossMonitor() - dataset = create_dataset(epoch_size) - net = resnet50(32, num_classes) + dataset = create_dataset(data_path, epoch_size) + batch_size = 32 + num_classes = 10 + net = resnet50(batch_size, num_classes) loss = SoftmaxCrossEntropyExpand(sparse=True) opt = Momentum(filter(lambda x: x.requires_grad, net.get_parameters()), 0.01, 0.9) model = Model(net, loss_fn=loss, optimizer=opt) @@ -340,17 +342,14 @@ cd ../ 日志文件保存device目录下，env.log中记录了环境变量的相关信息，关于Loss部分结果保存在train.log中，示例如下： ``` -resnet50_distributed_training.py::test_train_feed ===============ds_num 195 -global_step: 194, loss: 1.997 -global_step: 389, loss: 1.655 -global_step: 584, loss: 1.723 -global_step: 779, loss: 1.807 -global_step: 974, loss: 1.417 -global_step: 1169, loss: 1.195 -global_step: 1364, loss: 1.238 -global_step: 1559, loss: 1.456 -global_step: 1754, loss: 0.987 -global_step: 1949, loss: 1.035 -end training -PASSED +epoch: 1 step: 156, loss is 2.0084016 +epoch: 2 step: 156, loss is 1.6407638 +epoch: 3 step: 156, loss is 1.6164391 +epoch: 4 step: 156, loss is 1.6838071 +epoch: 5 step: 156, loss is 1.6320667 +epoch: 6 step: 156, loss is 1.3098773 +epoch: 7 step: 156, loss is 1.3515002 +epoch: 8 step: 156, loss is 1.2943741 +epoch: 9 step: 156, loss is 1.2316195 +epoch: 10 step: 156, loss is 1.1533381 ``` -- Gitee