refactor: move example data to respective folders

examples/gpt2/examples/gpt2.rs

@@ -1,4 +1,7 @@
-use std::io::{self, Write};
+use std::{
+	io::{self, Write},
+	path::Path
+};
 
 use ndarray::{array, concatenate, s, Array1, Axis};
 use ort::{download::language::machine_comprehension::GPT2, inputs, CUDAExecutionProvider, Environment, GraphOptimizationLevel, SessionBuilder, Tensor};
@@ -26,7 +29,7 @@ fn main() -> ort::Result<()> {
 		.with_intra_threads(1)?
 		.with_model_downloaded(GPT2::GPT2LmHead)?;
 
-	let tokenizer = Tokenizer::from_file("tests/data/gpt2-tokenizer.json").unwrap();
+	let tokenizer = Tokenizer::from_file(Path::new(env!("CARGO_MANIFEST_DIR")).join("data").join("tokenizer.json")).unwrap();
 	let tokens = tokenizer.encode(PROMPT, false).unwrap();
 	let tokens = tokens.get_ids().iter().map(|i| *i as i64).collect::<Vec<_>>();
 

examples/yolov8/examples/yolov8.rs

@@ -1,5 +1,7 @@
 #![allow(clippy::manual_retain)]
 
+use std::path::Path;
+
 use image::{imageops::FilterType, GenericImageView};
 use ndarray::{s, Array, Axis};
 use ort::{inputs, CUDAExecutionProvider, Environment, SessionBuilder, SessionOutputs};
@@ -40,7 +42,7 @@ const YOLOV8_CLASS_LABELS: [&str; 80] = [
 fn main() -> ort::Result<()> {
 	tracing_subscriber::fmt::init();
 
-	let original_img = image::open("tests/data/baseball.jpg").unwrap();
+	let original_img = image::open(Path::new(env!("CARGO_MANIFEST_DIR")).join("data").join("baseball.jpg")).unwrap();
 	let (img_width, img_height) = (original_img.width(), original_img.height());
 	let img = original_img.resize_exact(640, 640, FilterType::CatmullRom);
 	let mut input = Array::zeros((1, 3, 640, 640));