fix: cast some ops to float

Author: avik-pal

.github/workflows/Documenter.yaml

@@ -3,19 +3,19 @@ name: Documentation
 on:
   pull_request:
     paths:
-      - '.github/workflows/Documenter.yaml'
-      - 'docs/**'
-      - 'lib/**'
-      - 'src/**'
+      - ".github/workflows/Documenter.yaml"
+      - "docs/**"
+      - "lib/**"
+      - "src/**"
   push:
     branches:
       - main
-    tags: '*'
+    tags: "*"
     paths:
-      - '.github/workflows/Documenter.yaml'
-      - 'docs/**'
-      - 'lib/**'
-      - 'src/**'
+      - ".github/workflows/Documenter.yaml"
+      - "docs/**"
+      - "lib/**"
+      - "src/**"
 
 concurrency:
   # Same group concurrency as the `PreviewCleanup.yml` workflow, because they both
@@ -37,22 +37,14 @@ jobs:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v2
         with:
-          version: '1'
+          version: "1"
       - uses: julia-actions/cache@v2
       - name: Instantiate docs environment
+        shell: julia --color=yes --project=docs {0}
         run: |
-          julia --color=yes --project=docs -e '
-            using Pkg
-            Pkg.instantiate()'
-        env:
-          JULIA_PKG_SERVER_REGISTRY_PREFERENCE: eager
-      - name: Run doctests
-        run: |
-          julia --color=yes --project=docs -e '
-            using Documenter: DocMeta, doctest
-            using Reactant
-            DocMeta.setdocmeta!(Reactant, :DocTestSetup, :(using Reactant); recursive=true)
-            doctest(Reactant)'
+          using Pkg
+          Pkg.develop(PackageSpec(path=pwd()))
+          Pkg.instantiate()
       - name: Build documentation
         run: julia --color=yes --project=docs docs/make.jl
         env:

docs/src/tutorials/sharding.md

@@ -271,15 +271,15 @@ Reactant.addressable_devices()
 
 You can inspect the type of the device, as well as its properties.
 
-## Generating Distributed Data by Concatenating Local-Worker Data
+<!-- ## Generating Distributed Data by Concatenating Local-Worker Data
 
 ## Handling Replicated Tensors
 
 ## Sharding in Neural Networks
 
 ### 8-way Batch Parallelism
 
-### 4-way Batch & 2-way Model Parallelism
+### 4-way Batch & 2-way Model Parallelism -->
 
 ## Related links
 

src/TracedRNumber.jl

@@ -416,6 +416,28 @@ for (jlop, hloop) in (
     @eval $(jlop)(@nospecialize(lhs::TracedRNumber)) = Ops.$(hloop)(lhs)
 end
 
+for (jlop, hloop) in (
+    (:(Base.sin), :sine),
+    (:(Base.cos), :cosine),
+    (:(Base.tan), :tan),
+    (:(Base.tanh), :tanh),
+    (:(Base.FastMath.tanh_fast), :tanh),
+    (:(Base.exp), :exponential),
+    (:(Base.FastMath.exp_fast), :exponential),
+    (:(Base.expm1), :exponential_minus_one),
+    (:(Base.log), :log),
+    (:(Base.log1p), :log_plus_one),
+    (:(Base.sqrt), :sqrt),
+    (:(Base.acos), :acos),
+    (:(Base.acosh), :acosh),
+    (:(Base.asin), :asin),
+    (:(Base.asinh), :asinh),
+    (:(Base.atan), :atan),
+    (:(Base.atanh), :atanh),
+)
+    @eval $(jlop)(@nospecialize(lhs::TracedRNumber{<:Integer})) = Ops.$(hloop)(float(lhs))
+end
+
 for (jlop, hloop) in
     ((:(Base.sinpi), :sine), (:(Base.cospi), :cosine), (:(Base.tanpi), :tan))
     @eval $(jlop)(@nospecialize(lhs::TracedRNumber{T})) where {T} = Ops.$(hloop)(T(π) * lhs)