  !include MUI2.nsh
  !include nsDialogs.nsh
  !include LogicLib.nsh
  !include CPUFeatures.nsh
  !include MultiDetailPrint.nsi
  
  # Installer names and locations
 
</s> remove     # Ask Docker/Cuda
        self.docker_ask_enable()
        self.cuda_ask_enable()
 </s> add     # Ask AMD/Docker/Cuda
        self.amd_ask_enable()
        if not self.env.enable_amd:
            self.docker_ask_enable()
            self.cuda_ask_enable() </s> remove         if IS_MACOS:
 </s> add         if self.plaid:
            # NB There is no useful way to get free VRAM on PlaidML.
            # OpenCL loads and unloads VRAM as required, so this returns the maximum allowed
            # allocation size. It's not particularly useful
            vram = self.plaid.max_alloc
        elif IS_MACOS:
!include winmessages.nsh
  !include MUI2.nsh
  !include nsDialogs.nsh
!include winmessages.nsh
  !include LogicLib.nsh
  !include CPUFeatures.nsh
  !include MultiDetailPrint.nsi
  
  # Installer names and locations
keep add keep keep keep keep keep
 Experimental AMD Support (#764)

* PlaidML support in setup.py

* Add AMD flag for plaidml support

* PlaidML - Use .plaidML file if present, otherwise default to largest available

* Update training info message for GUI

* Add AMD option to Windows Installer

* Add quiet keras.backend importer and minor sysinfo amend.

* plug PlaidMLStats into GPUStats

* Update Docs 
.install/windows/install.nsi