Indicate default Float32 eltype in docstrings

Author: adrhill

src/gradient.jl

@@ -75,8 +75,8 @@ function call_analyzer(
 end
 
 """
-    SmoothGrad(analyzer, [n=50, std=1.0, rng=GLOBAL_RNG])
-    SmoothGrad(analyzer, [n=50, distribution=Normal(0, 1), rng=GLOBAL_RNG])
+    SmoothGrad(analyzer, [n=50, std=1.0f0, rng=GLOBAL_RNG])
+    SmoothGrad(analyzer, [n=50, distribution=Normal(0.0f0, 1.0f0), rng=GLOBAL_RNG])
 
 Analyze model by calculating a smoothed sensitivity map.
 This is done by averaging sensitivity maps of a `Gradient` analyzer over random samples

src/input_augmentation.jl

@@ -90,7 +90,7 @@ end
 A wrapper around analyzers that augments the input with `n` samples of additive noise sampled from a scalar `distribution`.
 This input augmentation is then averaged to return an `Explanation`.
 
-Defaults to the normal distribution `Normal(0, std^2)` with `std=1`.
+Defaults to the normal distribution `Normal(0, std^2)` with `std=1.0f0`.
 For optimal results, $REF_SMILKOV_SMOOTHGRAD recommends setting `std` between 10% and 20% of the input range of each sample,
 e.g. `std = 0.1 * (maximum(input) - minimum(input))`.