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fix for TCC mode cards(tesla), was conflict with plaidML initialization.

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iperov 2019-04-19 10:37:43 +04:00
commit 7fe4cd4643
1 changed files with 29 additions and 23 deletions
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52
nnlib/device.py
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@ -274,28 +274,34 @@ has_nvml_cap = False
#- CUDA build of DFL #- CUDA build of DFL
has_nvidia_device = os.environ.get("DFL_FORCE_HAS_NVIDIA_DEVICE", "0") == "1" has_nvidia_device = os.environ.get("DFL_FORCE_HAS_NVIDIA_DEVICE", "0") == "1"
plaidML_devices = [] plaidML_devices = None
def get_plaidML_devices():
# Using plaidML OpenCL backend to determine system devices and has_nvidia_device global plaidML_devices
try: global has_nvidia_device
os.environ['PLAIDML_EXPERIMENTAL'] = 'false' #this enables work plaidML without run 'plaidml-setup' if plaidML_devices is None:
import plaidml plaidML_devices = []
ctx = plaidml.Context() # Using plaidML OpenCL backend to determine system devices and has_nvidia_device
for d in plaidml.devices(ctx, return_all=True)[0]: try:
details = json.loads(d.details) os.environ['PLAIDML_EXPERIMENTAL'] = 'false' #this enables work plaidML without run 'plaidml-setup'
if details['type'] == 'CPU': #skipping opencl-CPU import plaidml
continue ctx = plaidml.Context()
if 'nvidia' in details['vendor'].lower(): for d in plaidml.devices(ctx, return_all=True)[0]:
has_nvidia_device = True details = json.loads(d.details)
plaidML_devices += [ {'id':d.id, if details['type'] == 'CPU': #skipping opencl-CPU
'globalMemSize' : int(details['globalMemSize']), continue
'description' : d.description.decode() if 'nvidia' in details['vendor'].lower():
}] has_nvidia_device = True
ctx.shutdown() plaidML_devices += [ {'id':d.id,
except: 'globalMemSize' : int(details['globalMemSize']),
pass 'description' : d.description.decode()
}]
plaidML_devices_count = len(plaidML_devices) ctx.shutdown()
except:
pass
return plaidML_devices
if not has_nvidia_device:
get_plaidML_devices()
#choosing backend #choosing backend
@ -324,7 +330,7 @@ if device.backend is None and not force_tf_cpu:
if force_plaidML or (device.backend is None and not has_nvidia_device): if force_plaidML or (device.backend is None and not has_nvidia_device):
#tensorflow backend was failed without has_nvidia_device , or forcing plaidML, trying to use plaidML backend #tensorflow backend was failed without has_nvidia_device , or forcing plaidML, trying to use plaidML backend
if plaidML_devices_count == 0: if len(get_plaidML_devices()) == 0:
#print ("plaidML: No capable OpenCL devices found. Falling back to tensorflow backend.") #print ("plaidML: No capable OpenCL devices found. Falling back to tensorflow backend.")
device.backend = None device.backend = None
else: else: