[PATCH] accel: work around DRM_ACCEL dependencies

[Arnd Bergmann]

From: Arnd Bergmann <arnd at arndb.de>

At the moment, accel drivers can be built-in even with CONFIG_DRM=m,
but this causes a link failure:

x86_64-linux-ld: drivers/accel/ivpu/ivpu_drv.o: in function `ivpu_dev_init':
ivpu_drv.c:(.text+0x1535): undefined reference to `drmm_kmalloc'
x86_64-linux-ld: ivpu_drv.c:(.text+0x1562): undefined reference to `drmm_kmalloc'
x86_64-linux-ld: drivers/accel/ivpu/ivpu_drv.o: in function `ivpu_remove':
ivpu_drv.c:(.text+0x1faa): undefined reference to `drm_dev_unregister'
x86_64-linux-ld: drivers/accel/ivpu/ivpu_drv.o: in function `ivpu_probe':
ivpu_drv.c:(.text+0x1fef): undefined reference to `__devm_drm_dev_alloc'

This could be avoided by making DRM_ACCEL a tristate symbol, which
would mean that every ACCEL driver is guarantee to be able to link
against DRM as well. However, having both as =m causes another link
failure because the DRM core code also links against the accel driver:

x86_64-linux-ld: drivers/gpu/drm/drm_drv.o: in function `drm_minor_register':
drm_drv.c:(.text+0x259): undefined reference to `accel_debugfs_init'
x86_64-linux-ld: drm_drv.c:(.text+0x298): undefined reference to `accel_minor_replace'

I think it will be necessary to establish a link hierarchy between drm.ko
and drm_accel.ko to avoid circular dependencies like this, but until then
the only way that both can be used is to have both subsystems built into
the kernel. Enforce this using a Kconfig dependency.

Fixes: 8bf4889762a8 ("drivers/accel: define kconfig and register a new major")
Signed-off-by: Arnd Bergmann <arnd at arndb.de>
---
 drivers/accel/Kconfig | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/drivers/accel/Kconfig b/drivers/accel/Kconfig
index 834863902e16..dd18d3b2028c 100644
--- a/drivers/accel/Kconfig
+++ b/drivers/accel/Kconfig
@@ -8,7 +8,7 @@
 #
 menuconfig DRM_ACCEL
 	bool "Compute Acceleration Framework"
-	depends on DRM
+	depends on DRM=y
 	help
 	  Framework for device drivers of compute acceleration devices, such
 	  as, but not limited to, Machine-Learning and Deep-Learning
-- 
2.39.0