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doc reference for gpu_backend! #2292

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f03fc02
docs for gpu_backend!
CarloLucibello Jul 16, 2023
7462d4a
update
CarloLucibello Jul 16, 2023
7f6e9d3
gpu docstring
CarloLucibello Jul 16, 2023
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2 changes: 1 addition & 1 deletion docs/src/gpu.md
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Expand Up @@ -46,7 +46,7 @@ Flux relies on [Preferences.jl](https://github.com/JuliaPackaging/Preferences.jl

There are two ways you can specify it:

- From the REPL/code in your project, call `Flux.gpu_backend!("AMD")` and restart (if needed) Julia session for the changes to take effect.
- From the REPL/code in your project, call [`Flux.gpu_backend!`](ref)`("AMD")` and restart (if needed) Julia session for the changes to take effect.
- In `LocalPreferences.toml` file in you project directory specify:
```toml
[Flux]
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1 change: 1 addition & 0 deletions docs/src/models/functors.md
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Expand Up @@ -21,6 +21,7 @@ Functors.fmapstructure
Flux provides some convenience functions based on `fmap`. Some ([`f16`](@ref Flux.f16), [`f32`](@ref Flux.f32), [`f64`](@ref Flux.f64)) change the precision of all arrays in a model. Others are used for moving a model to of from GPU memory:

```@docs
Flux.gpu_backend!
cpu
gpu(::Any)
gpu(::Flux.DataLoader)
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16 changes: 14 additions & 2 deletions src/functor.jl
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Expand Up @@ -190,6 +190,14 @@ _isleaf(x) = _isbitsarray(x) || Functors.isleaf(x)
const GPU_BACKENDS = ("CUDA", "AMD", "Metal")
const GPU_BACKEND = @load_preference("gpu_backend", "CUDA")

"""
gpu_backend!(backend::String)

Sets the gpu backend in `LocalPreferences.toml`.
Possible `backend` values are "CUDA", "AMD", and "Metal".
The selected backend affects the data movement in [`Flux.gpu`](@ref).
Current backend is stored in `Flux.GPU_BACKEND`.
"""
function gpu_backend!(backend::String)
if backend == GPU_BACKEND
@info """
Expand Down Expand Up @@ -217,8 +225,10 @@ end
Copies `m` to the current GPU device (using current GPU backend), if one is available.
If no GPU is available, it does nothing (but prints a warning the first time).

On arrays, this calls CUDA's `cu`, which also changes arrays
with Float64 elements to Float32 while copying them to the device (same for AMDGPU).
When the backed is set to "CUDA", when called on arrays it calls `CUDA.cu`,
which also changes arrays with Float64 elements to Float32 while copying them to the device.
Similar conversions happen for "AMDGPU" and "Metal" backends.

To act on arrays within a struct, the struct type must be marked with [`@functor`](@ref).

Use [`cpu`](@ref) to copy back to ordinary `Array`s.
Expand All @@ -227,6 +237,8 @@ See also [`f32`](@ref) and [`f16`](@ref) to change element type only.
See the [CUDA.jl docs](https://juliagpu.github.io/CUDA.jl/stable/usage/multigpu/)
to help identify the current device.

See [`Flux.gpu_backend!`](@ref) for setting the backend.

# Example
```julia-repl
julia> m = Dense(rand(2, 3)) # constructed with Float64 weight matrix
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