def parse_net(num_layers, cfg, weights):
net = None
counters = {}
stack = []
cfg_walker = CFGReader(cfg)
weights_walker = WeightsReader(weights)
output_index = []
for ith, layer in enumerate(cfg_walker):
if ith > num_layers and num_layers > 0:
break
layer_name = layer['name']
counters.setdefault(layer_name, 0)
counters[layer_name] += 1
scope = "{}{}{}".format(args.prefix, layer['name'],
counters[layer_name])
net = get_cfg_layer(net,
layer_name,
layer,
weights_walker,
stack,
output_index,
scope=scope)
stack.append(net)
print(ith, net)
for ind in output_index:
print('Output layer:', stack[ind])
return output_index
def parse_net(num_layers,
cfg,
weights,
training=False,
const_inits=True,
verbose=True):
net = None
counters = {}
stack = []
cfg_walker = CFGReader(cfg)
weights_walker = WeightsReader(weights)
output_index = []
num_layers = int(num_layers)
print('len')
print(len(weights_walker.transpose.flat))
for ith, layer in enumerate(cfg_walker):
if ith > num_layers and num_layers > 0:
break
layer_name = layer['name']
counters.setdefault(layer_name, 0)
counters[layer_name] += 1
scope = "{}{}{}".format(args.prefix, layer['name'],
counters[layer_name])
net = get_cfg_layer(net,
layer_name,
layer,
weights_walker,
stack,
output_index,
scope,
training=training,
const_inits=const_inits,
verbose=verbose)
# Exclude `net` layer from stack (for correct layer indexing)
# See https://github.com/jinyu121/DW2TF/issues/30
# See https://github.com/AlexeyAB/darknet/issues/487#issuecomment-374902735
if layer['name'] != 'net':
stack.append(net)
if verbose:
print(ith, net)
if verbose:
for ind in output_index:
print("=> Output layer: ", stack[ind])
def parse_net(num_layers,
cfg,
weights,
training=False,
const_inits=True,
verbose=True):
net = None
counters = {}
stack = []
cfg_walker = CFGReader(cfg)
weights_walker = WeightsReader(weights)
output_index = []
num_layers = int(num_layers)
for ith, layer in enumerate(cfg_walker):
if ith > num_layers and num_layers > 0:
break
layer_name = layer['name']
counters.setdefault(layer_name, 0)
counters[layer_name] += 1
scope = "{}{}{}".format(args.prefix, layer['name'],
counters[layer_name])
net = get_cfg_layer(net,
layer_name,
layer,
weights_walker,
stack,
output_index,
scope,
training=training,
const_inits=const_inits,
verbose=verbose)
stack.append(net)
if verbose:
print(ith, net)
if verbose:
for ind in output_index:
print("=> Output layer: ", stack[ind])