Allow for uniform initialization in a single step. (#136)

candle-core/src/cpu_backend.rs

@@ -895,7 +895,7 @@ impl CpuStorage {
         MatMul(bmnk).map(self, lhs_l, rhs, rhs_l)
     }
 
-    pub(crate) fn rand_uniform(shape: &Shape, dtype: DType) -> Result<Self> {
+    pub(crate) fn rand_uniform(shape: &Shape, dtype: DType, min: f64, max: f64) -> Result<Self> {
         use rand::prelude::*;
 
         let elem_count = shape.elem_count();
@@ -907,7 +907,7 @@ impl CpuStorage {
             DType::F32 => {
                 let mut data = Vec::new();
                 data.reserve(elem_count);
-                let uniform = rand::distributions::Uniform::new(0f32, 1f32);
+                let uniform = rand::distributions::Uniform::new(min as f32, max as f32);
                 for _i in 0..elem_count {
                     data.push(rng.sample::<f32, _>(uniform))
                 }
@@ -916,7 +916,7 @@ impl CpuStorage {
             DType::F64 => {
                 let mut data = Vec::new();
                 data.reserve(elem_count);
-                let uniform = rand::distributions::Uniform::new(0f64, 1f64);
+                let uniform = rand::distributions::Uniform::new(min, max);
                 for _i in 0..elem_count {
                     data.push(rng.sample::<f64, _>(uniform))
                 }

candle-core/src/cuda_backend.rs

@@ -153,7 +153,13 @@ impl CudaDevice {
         })
     }
 
-    pub(crate) fn rand_uniform(&self, shape: &Shape, dtype: DType) -> Result<CudaStorage> {
+    pub(crate) fn rand_uniform(
+        &self,
+        shape: &Shape,
+        dtype: DType,
+        lo: f64,
+        up: f64,
+    ) -> Result<CudaStorage> {
         let elem_count = shape.elem_count();
         let curand = self.curand.lock().unwrap();
         let slice = match dtype {
@@ -174,6 +180,10 @@ impl CudaDevice {
                 CudaStorageSlice::F64(data)
             }
         };
+        if lo != 0.0 || up != 1.0 {
+            let layout = Layout::contiguous(shape);
+            Affine(up - lo, lo).map(&slice, self, &layout)?;
+        }
         Ok(CudaStorage {
             slice,
             device: self.clone(),

candle-core/src/device.rs

@@ -109,14 +109,20 @@ impl Device {
         }
     }
 
-    pub(crate) fn rand_uniform(&self, shape: &Shape, dtype: DType) -> Result<Storage> {
+    pub(crate) fn rand_uniform(
+        &self,
+        shape: &Shape,
+        dtype: DType,
+        lo: f64,
+        up: f64,
+    ) -> Result<Storage> {
         match self {
             Device::Cpu => {
-                let storage = CpuStorage::rand_uniform(shape, dtype)?;
+                let storage = CpuStorage::rand_uniform(shape, dtype, lo, up)?;
                 Ok(Storage::Cpu(storage))
             }
             Device::Cuda(device) => {
-                let storage = device.rand_uniform(shape, dtype)?;
+                let storage = device.rand_uniform(shape, dtype, lo, up)?;
                 Ok(Storage::Cuda(storage))
             }
         }

candle-core/src/dummy_cuda_backend.rs

@@ -39,7 +39,7 @@ impl CudaDevice {
         Err(Error::NotCompiledWithCudaSupport)
     }
 
-    pub(crate) fn rand_uniform(&self, _: &Shape, _: DType) -> Result<CudaStorage> {
+    pub(crate) fn rand_uniform(&self, _: &Shape, _: DType, _: f64, _: f64) -> Result<CudaStorage> {
         Err(Error::NotCompiledWithCudaSupport)
     }
 

candle-core/src/tensor.rs

@@ -226,19 +226,33 @@ impl Tensor {
         s: S,
         dtype: DType,
         device: &Device,
+        lo: f64,
+        up: f64,
         is_variable: bool,
     ) -> Result<Self> {
         let s = s.into();
-        let storage = device.rand_uniform(&s, dtype)?;
+        let storage = device.rand_uniform(&s, dtype, lo, up)?;
         Ok(from_storage(storage, s, None, is_variable))
     }
 
-    pub fn rand_uniform<S: Into<Shape>>(s: S, dtype: DType, device: &Device) -> Result<Self> {
-        Self::rand_uniform_impl(s, dtype, device, false)
+    pub fn rand_uniform<S: Into<Shape>>(
+        s: S,
+        dtype: DType,
+        device: &Device,
+        lo: f64,
+        up: f64,
+    ) -> Result<Self> {
+        Self::rand_uniform_impl(s, dtype, device, lo, up, false)
     }
 
-    pub fn rand_uniform_var<S: Into<Shape>>(s: S, dtype: DType, device: &Device) -> Result<Self> {
-        Self::rand_uniform_impl(s, dtype, device, true)
+    pub fn rand_uniform_var<S: Into<Shape>>(
+        s: S,
+        dtype: DType,
+        device: &Device,
+        lo: f64,
+        up: f64,
+    ) -> Result<Self> {
+        Self::rand_uniform_impl(s, dtype, device, lo, up, true)
     }
 
     fn rand_normal_impl<S: Into<Shape>>(