update bindgen and examples

Cargo.toml

@@ -10,7 +10,7 @@ documentation = "https://docs.rs/xgboost"
 readme = "README.md"
 
 [dependencies]
-xgboost-sys = "0.1.2"
+xgboost-sys = { path="./xgboost-sys" }
 libc = "0.2"
 derive_builder = "0.5"
 log = "0.4"

examples/basic/src/main.rs

@@ -97,7 +97,7 @@ fn main() {
     let mut data = Vec::new();
 
     let reader = BufReader::new(File::open("../../xgboost-sys/xgboost/demo/data/agaricus.txt.train").unwrap());
-    let mut current_row = 0;
+    let mut current_row: u64 = 0;
     for line in reader.lines() {
         let line = line.unwrap();
         let sample: Vec<&str> = line.split_whitespace().collect();
@@ -106,16 +106,16 @@ fn main() {
         for entry in &sample[1..] {
             let pair: Vec<&str> = entry.split(':').collect();
             rows.push(current_row);
-            cols.push(pair[0].parse::<usize>().unwrap());
+            cols.push(pair[0].parse::<u64>().unwrap());
             data.push(pair[1].parse::<f32>().unwrap());
         }
 
         current_row += 1;
     }
 
     // work out size of sparse matrix from max row/col values
-    let shape = (*rows.iter().max().unwrap() + 1 as usize,
-                 *cols.iter().max().unwrap() + 1 as usize);
+    let shape = ((*rows.iter().max().unwrap() + 1) as usize,
+                 (*cols.iter().max().unwrap() + 1) as usize);
     let triplet_mat = sprs::TriMatBase::from_triplets(shape, rows, cols, data);
     let csr_mat = triplet_mat.to_csr();
 

examples/multiclass_classification/Cargo.toml

@@ -8,4 +8,4 @@ publish = false
 xgboost = { path = "../../" }
 log = "0.4"
 env_logger = "0.5"
-reqwest = "0.8"
+reqwest = { version = "0.11", features = ["blocking"] }

examples/multiclass_classification/src/main.rs

@@ -73,7 +73,7 @@ fn download_dataset<P: AsRef<Path>>(dst: P) {
     }
 
     debug!("Fetching training dataset from {}", url);
-    let mut response = reqwest::get(url).expect("failed to download training set data");
+    let mut response = reqwest::blocking::get(url).expect("failed to download training set data");
 
     let file = File::create(dst).expect(&format!("failed to create file {}", dst.display()));
     let mut writer = BufWriter::new(file);

src/booster.rs

@@ -178,7 +178,7 @@ impl Booster {
                     for (dmat, dmat_name) in eval_sets {
                         let margin = bst.predict_margin(dmat)?;
                         let eval_result = eval_fn(&margin, dmat);
-                        let mut eval_results = dmat_eval_results.entry(eval_name.to_string())
+                        let eval_results = dmat_eval_results.entry(eval_name.to_string())
                             .or_insert_with(IndexMap::new);
                         eval_results.insert(dmat_name.to_string(), eval_result);
                     }
@@ -188,7 +188,7 @@ impl Booster {
                 let mut eval_dmat_results = BTreeMap::new();
                 for (dmat_name, eval_results) in &dmat_eval_results {
                     for (eval_name, result) in eval_results {
-                        let mut dmat_results = eval_dmat_results.entry(eval_name).or_insert_with(BTreeMap::new);
+                        let dmat_results = eval_dmat_results.entry(eval_name).or_insert_with(BTreeMap::new);
                         dmat_results.insert(dmat_name, result);
                     }
                 }
@@ -548,7 +548,7 @@ impl Booster {
                     let score = metric_parts[1].parse::<f32>()
                         .unwrap_or_else(|_| panic!("Unable to parse XGBoost metrics output: {}", eval));
 
-                    let mut metric_map = result.entry(evname.to_string()).or_insert_with(IndexMap::new);
+                    let metric_map = result.entry(evname.to_string()).or_insert_with(IndexMap::new);
                     metric_map.insert(metric.to_owned(), score);
                 }
             }

src/dmatrix.rs

@@ -1,6 +1,7 @@
 use std::{slice, ffi, ptr, path::Path};
 use libc::{c_uint, c_float};
 use std::os::unix::ffi::OsStrExt;
+use std::convert::TryInto;
 
 use xgboost_sys;
 
@@ -123,17 +124,17 @@ impl DMatrix {
     /// `data[indptr[i]:indptr[i+1]`.
     ///
     /// If `num_cols` is set to None, number of columns will be inferred from given data.
-    pub fn from_csr(indptr: &[usize], indices: &[usize], data: &[f32], num_cols: Option<usize>) -> XGBResult<Self> {
+    pub fn from_csr(indptr: &[u64], indices: &[usize], data: &[f32], num_cols: Option<usize>) -> XGBResult<Self> {
         assert_eq!(indices.len(), data.len());
         let mut handle = ptr::null_mut();
         let indices: Vec<u32> = indices.iter().map(|x| *x as u32).collect();
         let num_cols = num_cols.unwrap_or(0); // infer from data if 0
         xgb_call!(xgboost_sys::XGDMatrixCreateFromCSREx(indptr.as_ptr(),
                                                         indices.as_ptr(),
                                                         data.as_ptr(),
-                                                        indptr.len(),
-                                                        data.len(),
-                                                        num_cols,
+                                                        indptr.len().try_into().unwrap(),
+                                                        data.len().try_into().unwrap(),
+                                                        num_cols.try_into().unwrap(),
                                                         &mut handle))?;
         Ok(DMatrix::new(handle)?)
     }
@@ -146,17 +147,17 @@ impl DMatrix {
     /// `data[indptr[i]:indptr[i+1]`.
     ///
     /// If `num_rows` is set to None, number of rows will be inferred from given data.
-    pub fn from_csc(indptr: &[usize], indices: &[usize], data: &[f32], num_rows: Option<usize>) -> XGBResult<Self> {
+    pub fn from_csc(indptr: &[u64], indices: &[usize], data: &[f32], num_rows: Option<usize>) -> XGBResult<Self> {
         assert_eq!(indices.len(), data.len());
         let mut handle = ptr::null_mut();
         let indices: Vec<u32> = indices.iter().map(|x| *x as u32).collect();
         let num_rows = num_rows.unwrap_or(0); // infer from data if 0
         xgb_call!(xgboost_sys::XGDMatrixCreateFromCSCEx(indptr.as_ptr(),
                                                         indices.as_ptr(),
                                                         data.as_ptr(),
-                                                        indptr.len(),
-                                                        data.len(),
-                                                        num_rows,
+                                                        indptr.len().try_into().unwrap(),
+                                                        data.len().try_into().unwrap(),
+                                                        num_rows.try_into().unwrap(),
                                                         &mut handle))?;
         Ok(DMatrix::new(handle)?)
     }

src/error.rs

@@ -31,7 +31,7 @@ impl XGBError {
         match ret_val {
             0  => Ok(()),
             -1 => Err(XGBError::from_xgboost()),
-            _  => panic!(format!("unexpected return value '{}', expected 0 or -1", ret_val)),
+            _  => panic!("unexpected return value '{}', expected 0 or -1", ret_val),
         }
     }
 

src/lib.rs

@@ -65,7 +65,6 @@ extern crate libc;
 extern crate tempfile;
 extern crate indexmap;
 
-#[macro_use]
 macro_rules! xgb_call {
     ($x:expr) => {
         XGBError::check_return_value(unsafe { $x })

xgboost-sys/Cargo.toml

@@ -13,4 +13,4 @@ readme = "README.md"
 libc = "0.2"
 
 [build-dependencies]
-bindgen = "0.36"
+bindgen = "0.59"