def test_context_limits():
#figure out how many contexts we can have on each card:
cuda_devices = encoder_module.get_cuda_devices()
ec = getattr(encoder_module, "Encoder")
MAX_ENCODER_CONTEXTS_PER_DEVICE = 64
log("")
for encoding in encoder_module.get_encodings():
for w,h in TEST_DIMENSIONS:
log("test_context_limits() %s @ %sx%s" % (encoding, w, h))
src_format = encoder_module.get_colorspaces()[0]
for device_id, device_info in cuda_devices.items():
options = {"cuda_device" : device_id}
encoders = []
for i in range(MAX_ENCODER_CONTEXTS_PER_DEVICE):
e = ec()
encoders.append(e)
try:
e.init_context(w, h, src_format, encoding, 20, 0, options)
except Exception, e:
log("failed to created context %s on %s: %s" % (i, device_info, e))
break
log("device %s managed %s contexts at %sx%s" % (device_info, len(encoders)-1, w, h))
for encoder in encoders:
try:
encoder.clean()
except Exception, e:
log("encoder cleanup error: %s" % e)
def test_context_limits():
#figure out how many contexts we can have on each card:
cuda_devices = encoder_module.get_cuda_devices()
ec = getattr(encoder_module, "Encoder")
MAX_ENCODER_CONTEXTS_PER_DEVICE = 64
log("")
for encoding in encoder_module.get_encodings():
for w, h in TEST_DIMENSIONS:
log("test_context_limits() %s @ %sx%s" % (encoding, w, h))
src_format = encoder_module.get_colorspaces()[0]
for device_id, device_info in cuda_devices.items():
options = {"cuda_device": device_id}
encoders = []
for i in range(MAX_ENCODER_CONTEXTS_PER_DEVICE):
e = ec()
encoders.append(e)
try:
e.init_context(w, h, src_format, encoding, 20, 0,
options)
except Exception, e:
log("failed to created context %s on %s: %s" %
(i, device_info, e))
break
log("device %s managed %s contexts at %sx%s" %
(device_info, len(encoders) - 1, w, h))
for encoder in encoders:
try:
encoder.clean()
except Exception, e:
log("encoder cleanup error: %s" % e)
def test_parallel_encode():
cuda_devices = encoder_module.get_cuda_devices()
ec = getattr(encoder_module, "Encoder")
encoding = encoder_module.get_encodings()[0]
log("")
log("test_parallel_encode() will test one %s encoder using %s encoding on each of %s in parallel"
% (ec, encoding, cuda_devices))
w, h = 1920, 1080
IMAGE_COUNT = 20
ENCODER_CONTEXTS_PER_DEVICE = 4
src_format = encoder_module.get_colorspaces()[0]
log("generating %s images..." % IMAGE_COUNT)
images = []
for _ in range(IMAGE_COUNT):
images += gen_src_images(src_format, w, h, 1)
sys.stdout.write(".")
sys.stdout.flush()
log("%s images generated" % IMAGE_COUNT)
encoders = []
for device_id, device_info in cuda_devices.items():
options = {"cuda_device": device_id}
for i in range(ENCODER_CONTEXTS_PER_DEVICE):
e = ec()
e.init_context(w, h, src_format, encoding, 20, 0, options)
log("encoder %s for device %s initialized" % (i, device_id))
info = "%s / encoder %s" % (device_info, i)
encoders.append((info, e, images))
log("%s encoders initialized: %s" %
(len(encoders), [e[1] for e in encoders]))
threads = []
i = 0
for info, encoder, images in encoders:
name = "Card %s : %s" % (i, info)
thread = threading.Thread(target=encoding_thread,
name=name,
args=(encoder, src_format, w, h, images,
name))
threads.append(thread)
i += 1
log("%s threads created: %s" % (len(threads), threads))
log("starting all threads")
log("")
for thread in threads:
thread.start()
log("%s threads started - waiting for completion" % len(threads))
for thread in threads:
thread.join()
log("all threads ended")
for _, encoder, _ in encoders:
encoder.clean()
log("")
def test_parallel_encode():
from xpra.codecs.nvenc import encoder as encoder_module #@UnresolvedImport
cuda_devices = encoder_module.get_cuda_devices()
ec = getattr(encoder_module, "Encoder")
encoding = encoder_module.get_encodings()[0]
print("")
print("test_parallel_encode() will test one %s encoder using %s encoding on each of %s in parallel" % (ec, encoding, cuda_devices))
w, h = 1920, 1080
IMAGE_COUNT = 20
ENCODER_CONTEXTS_PER_DEVICE = 4
src_format = encoder_module.get_colorspaces()[0]
print("generating %s images..." % IMAGE_COUNT)
images = []
for _ in range(IMAGE_COUNT):
images += gen_src_images(src_format, w, h, 1)
sys.stdout.write(".")
sys.stdout.flush()
print("%s images generated" % IMAGE_COUNT)
encoders = []
for device_id, device_info in cuda_devices.items():
options = {"cuda_device" : device_id}
for i in range(ENCODER_CONTEXTS_PER_DEVICE):
e = ec()
e.init_context(w, h, src_format, encoding, 20, 0, options)
print("encoder %s for device %s initialized" % (i, device_id))
info = "%s / encoder %s" % (device_info, i)
encoders.append((info, e, images))
print("%s encoders initialized: %s" % (len(encoders), [e[1] for e in encoders]))
threads = []
i = 0
for info, encoder, images in encoders:
name = "Card %s : %s" % (i, info)
thread = threading.Thread(target=encoding_thread, name=name, args=(encoder, src_format, w, h, images, name))
threads.append(thread)
i += 1
print("%s threads created: %s" % (len(threads), threads))
print("starting all threads")
print("")
for thread in threads:
thread.start()
print("%s threads started - waiting for completion" % len(threads))
for thread in threads:
thread.join()
print("all threads ended")
for _, encoder, _ in encoders:
encoder.clean()
print("")