def __init__(self, model):
super(Keras2Emitter, self).__init__()
from six import string_types as _string_types
if isinstance(model, _string_types):
network_path = model
else:
network_path = model[0]
weight_path = model[1]
self.IR_graph = IRGraph(network_path)
self.IR_graph.build()
def __init__(self, model):
from six import string_types as _string_types
super(CaffeEmitter, self).__init__()
if isinstance(model, _string_types):
network_path = model
else:
network_path = model[0]
self._load_weights(model[1])
self.IR_graph = IRGraph(network_path)
super(CaffeEmitter, self)._build()
def __init__(self, model):
super(PytorchEmitter, self).__init__()
if isinstance(model, _string_types):
network_path = model
else:
network_path = model[0]
weight_path = model[1]
self.init_code = str()
self.IR_graph = IRGraph(network_path)
self.IR_graph.build()
self._load_weights(weight_path)
def __init__(self, architecture, weight):
super(CoreMLEmitter, self).__init__()
if os.path.exists(architecture) == False:
raise ValueError("IR architecture file [{}] is not found.".format(architecture))
else:
self.IR_graph = IRGraph(architecture)
self.IR_graph.build()
if os.path.exists(weight) == False:
raise ValueError("IR weight file [{}] is not found.".format(weight))
else:
self._load_weights(weight)
def __init__(self, model):
from six import string_types as _string_types
super(CntkEmitter, self).__init__()
if isinstance(model, _string_types):
network_path = model
else:
network_path = model[0]
self._load_weights(model[1])
self.IR_graph = IRGraph(network_path)
super(CntkEmitter, self)._build()
self.yolo_parameter = []
folder = Folder(self.IR_graph, self.weights_dict)
folder.fold()
def __init__(self, model):
super(TensorflowEmitter, self).__init__()
from six import string_types as _string_types
if isinstance(model, _string_types):
network_path = model
else:
network_path = model[0]
self._load_weights(model[1])
self.IR_graph = IRGraph(network_path)
super(TensorflowEmitter, self)._build()
folder = Folder(self.IR_graph, self.weights_dict)
folder.fold()
def __init__(self, model, ctx='cpu'):
super(MyPytorchEmitter, self).__init__()
if isinstance(model, _string_types):
network_path = model
else:
network_path = model[0]
weight_path = model[1]
self.ctx = ctx
self.init_code = str()
self.IR_graph = IRGraph(network_path)
self.IR_graph.build()
self._load_weights(weight_path)
self.weights_dict = MyPytorchEmitter.convert(self.weights_dict)
folder = Folder(self.IR_graph, self.weights_dict)
folder.fold()
def __init__(self, model):
super(Keras2Emitter, self).__init__()
from six import string_types as _string_types
if isinstance(model, _string_types):
network_path = model
else:
network_path = model[0]
weight_path = model[1]
self._load_weights(weight_path)
self.IR_graph = IRGraph(network_path)
self.IR_graph.build()
self.yolo_parameter = []
self.region_parameter = []
self.layers_codes_count = dict()
folder = Folder(self.IR_graph, self.weights_dict)
folder.fold()
def __init__(self, model):
from six import string_types as _string_types
if isinstance(model, _string_types):
network_path = model
self.weight_loaded = False
elif len(model) == 4:
network_path = model[0]
weight_path = model[1]
self.input_shape = model[2]
self.output_weights_file = model[3]
self.weights = np.load(weight_path).item()
self.weight_loaded = True
self.output_weights = dict()
else:
raise ValueError("the # of input arguments [{}] is not supported" % len(model))
self.IR_graph = IRGraph(network_path)
self.IR_graph.build()
def __init__(self, model):
super(MXNetEmitter, self).__init__()
from six import string_types as _string_types
if isinstance(model, _string_types):
network_path = model
self.weight_loaded = False
elif len(model) == 3:
network_path = model[0]
weight_path = model[1]
self.output_weights_file = model[2]
self.output_weights = dict()
self._load_weights(weight_path)
self.weights = self.weights_dict
else:
raise ValueError("the # of input arguments [{}] is not supported" % len(model))
self.IR_graph = IRGraph(network_path)
self.IR_graph.build()
folder = Folder(self.IR_graph, self.weights)
folder.fold()
def __init__(self, graphfile, weightfile=None):
print("Initializing network...")
self.graphfile = graphfile
self.weightfile = weightfile
self.IR_graph = IRGraph(self.graphfile)
self.IR_graph.build()
self.IR_graph.model = 1
if self.weightfile is None:
logging.info("No weights file loaded\n")
else:
logging.info("Load weights...\n")
try:
self.weights_dict = np.load(self.weightfile,
allow_pickle=True).item()
except:
self.weights_dict = np.load(self.weightfile,
encoding='bytes',
allow_pickle=True).item()
self.analyze_net()
print("Network analyzed successfully...\n")
