Merge pull request #384 from fndejan/feature/migarte-from-random-to-rand

Migrate from `random` to `rand`

Author: adamcrume

Cargo.toml

@@ -35,7 +35,7 @@ ndarray = { version = "0.15.6", optional = true }
 rustversion = "1.0.9"
 
 [dev-dependencies]
-random = "0.12.2"
+rand = "0.8.5"
 serial_test = "0.9.0"
 
 [features]

examples/expressions.rs

@@ -1,4 +1,4 @@
-extern crate random;
+extern crate rand;
 extern crate tensorflow;
 
 use std::error::Error;

examples/regression.rs

@@ -1,5 +1,4 @@
-use random;
-use random::Source;
+use rand;
 use std::error::Error;
 use std::fs::File;
 use std::io::Read;
@@ -39,11 +38,10 @@ fn main() -> Result<(), Box<dyn Error>> {
     let b = 0.3;
     let num_points = 100;
     let steps = 201;
-    let mut rand = random::default();
     let mut x = Tensor::new(&[num_points as u64]);
     let mut y = Tensor::new(&[num_points as u64]);
     for i in 0..num_points {
-        x[i] = (2.0 * rand.read::<f64>() - 1.0) as f32;
+        x[i] = (2.0 * rand::random::<f64>() - 1.0) as f32;
         y[i] = w * x[i] + b;
     }
 

examples/regression_checkpoint.rs

@@ -1,5 +1,4 @@
-use random;
-use random::Source;
+use rand;
 use std::error::Error;
 use std::fs::File;
 use std::io::Read;
@@ -39,11 +38,10 @@ fn main() -> Result<(), Box<dyn Error>> {
     let b = 0.3;
     let num_points = 100;
     let steps = 201;
-    let mut rand = random::default();
     let mut x = Tensor::new(&[num_points as u64]);
     let mut y = Tensor::new(&[num_points as u64]);
     for i in 0..num_points {
-        x[i] = (2.0 * rand.read::<f64>() - 1.0) as f32;
+        x[i] = (2.0 * rand::random::<f64>() - 1.0) as f32;
         y[i] = w * x[i] + b;
     }
 

examples/regression_savedmodel.rs

@@ -1,5 +1,4 @@
-use random;
-use random::Source;
+use rand;
 use std::error::Error;
 use std::path::Path;
 use std::result::Result;
@@ -36,11 +35,10 @@ fn main() -> Result<(), Box<dyn Error>> {
     let b = 0.3;
     let num_points = 100;
     let steps = 201;
-    let mut rand = random::default();
     let mut x = Tensor::new(&[num_points as u64]);
     let mut y = Tensor::new(&[num_points as u64]);
     for i in 0..num_points {
-        x[i] = (2.0 * rand.read::<f64>() - 1.0) as f32;
+        x[i] = (2.0 * rand::random::<f64>() - 1.0) as f32;
         y[i] = w * x[i] + b;
     }