def __init__(self, net, layer_idx):
self.data = None
self.label = None
self.shmem = []
self.name = net._layer_names[layer_idx]
handles = self.name.split('-', 1)
# print "Allocating shared memory for %s." % handles[0]
handle = prepend_pid(handles[0])
shmem, arr = create_shmem_ndarray('/'+handle,
net.blobs[handles[0]].data.shape,
np.float32,
flags=posix_ipc.O_CREAT)
self.data = arr
self.shmem.append(shmem)
if len(handles) == 2:
handle = prepend_pid(handles[1])
shmem, arr = create_shmem_ndarray('/'+handle,
net.blobs[handles[1]].data.shape,
np.float32,
flags=posix_ipc.O_CREAT)
self.label = arr
self.shmem.append(shmem)
net.set_input_arrays(self.data, self.label, layer_idx)
else:
if SharedData._null_array is None:
SharedData._null_array = np.empty(
(self.data.shape[0], 1, 1, 1),
dtype=np.float32)
print("[SharedData] Warning: didn't specify a handle for the "
"label in layer", layer_idx, ". Should not be used in net.",
file=sys.stderr)
net.set_input_arrays(self.data, SharedData._null_array, layer_idx)
def __init__(self, net, param_name):
self.caffe_grads = []
self.shared_grads = []
self.shmem = []
for i, param in enumerate(net.params[param_name]):
# Typically, we'll have two, a weight and bias.
handle = prepend_pid(param_name + '_' + SharedGradient.POSTFIX[i])
shmem, arr = create_shmem_ndarray('/' + handle,
param.diff.shape,
np.float32,
flags=posix_ipc.O_CREAT)
self.caffe_grads.append(param.diff)
self.shared_grads.append(arr)
self.shmem.append(shmem)