示例#1
0
    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)
示例#2
0
    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)