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Improve grammar (#1619)
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@ -125,7 +125,7 @@ pub fn train<B: AutodiffBackend>(artifact_dir: &str, config: TrainingConfig, dev
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B::seed(config.seed);
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let batcher_train = MnistBatcher::<B>::new(device.clone());
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let batcher_valid = MnistBatcher::<B::InnerBackend>::new(device.clone());
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let batcher_valid = MnistBatcher::<B>::InnerBackend>::new(device.clone());
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let dataloader_train = DataLoaderBuilder::new(batcher_train)
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.batch_size(config.batch_size)
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@ -1,6 +1,6 @@
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# Dataset
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Most deep learning training being done on datasets –with perhaps the exception of reinforcement learning–, it is
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In most deep learning training performed on datasets (with perhaps the exception of reinforcement learning), it is
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essential to provide a convenient and performant API.
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The dataset trait is quite similar to the dataset abstract class in PyTorch:
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@ -69,7 +69,7 @@ let dataset = ShuffledDataset<DbPedia, DbPediaItem>::with_seed(dataset, 42);
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```rust, ignore
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// define chained dataset type here for brevity
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type PartialData = PartialDataset<ShuffledDataset<DbPedia, DbPediaItem>>;
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let dataset_len = dataset.len();
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let len = dataset.len();
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let split == "train"; // or "val"/"test"
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let data_split = match split {
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