diff options
Diffstat (limited to 'candle-nn/src/vision')
-rw-r--r-- | candle-nn/src/vision/cifar.rs | 62 | ||||
-rw-r--r-- | candle-nn/src/vision/mnist.rs | 65 | ||||
-rw-r--r-- | candle-nn/src/vision/mod.rs | 12 |
3 files changed, 0 insertions, 139 deletions
diff --git a/candle-nn/src/vision/cifar.rs b/candle-nn/src/vision/cifar.rs deleted file mode 100644 index 0683c4d2..00000000 --- a/candle-nn/src/vision/cifar.rs +++ /dev/null @@ -1,62 +0,0 @@ -//! The CIFAR-10 dataset. -//! -//! The files can be downloaded from the following page: -//! <https://www.cs.toronto.edu/~kriz/cifar.html> -//! The binary version of the dataset is used. -use crate::vision::Dataset; -use candle::{DType, Device, Result, Tensor}; -use std::fs::File; -use std::io::{BufReader, Read}; - -const W: usize = 32; -const H: usize = 32; -const C: usize = 3; -const BYTES_PER_IMAGE: usize = W * H * C + 1; -const SAMPLES_PER_FILE: usize = 10000; - -fn read_file(filename: &std::path::Path) -> Result<(Tensor, Tensor)> { - let mut buf_reader = BufReader::new(File::open(filename)?); - let mut data = vec![0u8; SAMPLES_PER_FILE * BYTES_PER_IMAGE]; - buf_reader.read_exact(&mut data)?; - let mut images = vec![]; - let mut labels = vec![]; - for index in 0..SAMPLES_PER_FILE { - let content_offset = BYTES_PER_IMAGE * index; - labels.push(data[content_offset]); - images.push(&data[1 + content_offset..content_offset + BYTES_PER_IMAGE]); - } - let images: Vec<u8> = images - .iter() - .copied() - .flatten() - .copied() - .collect::<Vec<_>>(); - let labels = Tensor::from_vec(labels, SAMPLES_PER_FILE, &Device::Cpu)?; - let images = Tensor::from_vec(images, (SAMPLES_PER_FILE, C, H, W), &Device::Cpu)?; - let images = (images.to_dtype(DType::F32)? / 255.)?; - Ok((images, labels)) -} - -pub fn load_dir<T: AsRef<std::path::Path>>(dir: T) -> Result<Dataset> { - let dir = dir.as_ref(); - let (test_images, test_labels) = read_file(&dir.join("test_batch.bin"))?; - let train_images_and_labels = [ - "data_batch_1.bin", - "data_batch_2.bin", - "data_batch_3.bin", - "data_batch_4.bin", - "data_batch_5.bin", - ] - .iter() - .map(|x| read_file(&dir.join(x))) - .collect::<Result<Vec<_>>>()?; - let (train_images, train_labels): (Vec<_>, Vec<_>) = - train_images_and_labels.into_iter().unzip(); - Ok(Dataset { - train_images: Tensor::cat(&train_images, 0)?, - train_labels: Tensor::cat(&train_labels, 0)?, - test_images, - test_labels, - labels: 10, - }) -} diff --git a/candle-nn/src/vision/mnist.rs b/candle-nn/src/vision/mnist.rs deleted file mode 100644 index 2267f9a0..00000000 --- a/candle-nn/src/vision/mnist.rs +++ /dev/null @@ -1,65 +0,0 @@ -//! The MNIST hand-written digit dataset. -//! -//! The files can be obtained from the following link: -//! <http://yann.lecun.com/exdb/mnist/> -use candle::{DType, Device, Result, Tensor}; -use std::fs::File; -use std::io::{self, BufReader, Read}; - -fn read_u32<T: Read>(reader: &mut T) -> Result<u32> { - let mut b = vec![0u8; 4]; - reader.read_exact(&mut b)?; - let (result, _) = b.iter().rev().fold((0u64, 1u64), |(s, basis), &x| { - (s + basis * u64::from(x), basis * 256) - }); - Ok(result as u32) -} - -fn check_magic_number<T: Read>(reader: &mut T, expected: u32) -> Result<()> { - let magic_number = read_u32(reader)?; - if magic_number != expected { - Err(io::Error::new( - io::ErrorKind::Other, - format!("incorrect magic number {magic_number} != {expected}"), - ))?; - } - Ok(()) -} - -fn read_labels(filename: &std::path::Path) -> Result<Tensor> { - let mut buf_reader = BufReader::new(File::open(filename)?); - check_magic_number(&mut buf_reader, 2049)?; - let samples = read_u32(&mut buf_reader)?; - let mut data = vec![0u8; samples as usize]; - buf_reader.read_exact(&mut data)?; - let samples = data.len(); - Tensor::from_vec(data, samples, &Device::Cpu) -} - -fn read_images(filename: &std::path::Path) -> Result<Tensor> { - let mut buf_reader = BufReader::new(File::open(filename)?); - check_magic_number(&mut buf_reader, 2051)?; - let samples = read_u32(&mut buf_reader)? as usize; - let rows = read_u32(&mut buf_reader)? as usize; - let cols = read_u32(&mut buf_reader)? as usize; - let data_len = samples * rows * cols; - let mut data = vec![0u8; data_len]; - buf_reader.read_exact(&mut data)?; - let tensor = Tensor::from_vec(data, (samples, rows * cols), &Device::Cpu)?; - tensor.to_dtype(DType::F32)? / 255. -} - -pub fn load_dir<T: AsRef<std::path::Path>>(dir: T) -> Result<crate::vision::Dataset> { - let dir = dir.as_ref(); - let train_images = read_images(&dir.join("train-images-idx3-ubyte"))?; - let train_labels = read_labels(&dir.join("train-labels-idx1-ubyte"))?; - let test_images = read_images(&dir.join("t10k-images-idx3-ubyte"))?; - let test_labels = read_labels(&dir.join("t10k-labels-idx1-ubyte"))?; - Ok(crate::vision::Dataset { - train_images, - train_labels, - test_images, - test_labels, - labels: 10, - }) -} diff --git a/candle-nn/src/vision/mod.rs b/candle-nn/src/vision/mod.rs deleted file mode 100644 index 6ce743eb..00000000 --- a/candle-nn/src/vision/mod.rs +++ /dev/null @@ -1,12 +0,0 @@ -use candle::Tensor; - -pub struct Dataset { - pub train_images: Tensor, - pub train_labels: Tensor, - pub test_images: Tensor, - pub test_labels: Tensor, - pub labels: usize, -} - -pub mod cifar; -pub mod mnist; |