def __init__(self, model):
super(Keras2Parser, self).__init__()
# load model files into Keras graph
if isinstance(model, _string_types):
model = _keras.models.load_model(
model,
custom_objects={
'relu6':
_keras.applications.mobilenet.relu6,
'DepthwiseConv2D':
_keras.applications.mobilenet.DepthwiseConv2D
})
self.weight_loaded = True
elif isinstance(model, tuple):
model = self._load_model(model[0], model[1])
else:
assert False
# _keras.utils.plot_model(model, "model.png", show_shapes = True)
# Build network graph
self.data_format = _keras.backend.image_data_format()
self.keras_graph = Keras2Graph(model)
self.keras_graph.build()
self.lambda_layer_count = 0
def __init__(self, model):
super(Keras2Parser, self).__init__()
# load model files into Keras graph
if isinstance(model, _string_types):
# try:
# # Keras 2.1.6
# from keras.applications.mobilenet import relu6
# from keras.applications.mobilenet import DepthwiseConv2D
# model = _keras.models.load_model(
# model,
# custom_objects={
# 'relu6': _keras.applications.mobilenet.relu6,
# 'DepthwiseConv2D': _keras.applications.mobilenet.DepthwiseConv2D
# }
# )
# except:
# Keras. 2.2.2
import tensorflow.keras.layers as layers
from tensorflow.keras.initializers import VarianceScaling
from mmdnn.conversion.keras.metrics import F1Score
model = _keras.models.load_model(model,
custom_objects={
'relu6':
layers.ReLU(6, name='relu6'),
'DepthwiseConv2D':
layers.DepthwiseConv2D,
'AudioVarianceScaling':
VarianceScaling,
'F1Score':
F1Score
})
self.weight_loaded = True
elif isinstance(model, tuple):
model = self._load_model(model[0], model[1])
else:
assert False
# _keras.utils.plot_model(model, "model.png", show_shapes = True)
# Build network graph
self.data_format = _keras.backend.image_data_format()
self.keras_graph = Keras2Graph(model)
self.keras_graph.build()
self.lambda_layer_count = 0
def __init__(self, model):
super(Keras2Parser, self).__init__()
# load model files into Keras graph
if isinstance(model, _string_types):
model = _keras.models.load_model(model)
elif isinstance(model, tuple):
model = self._load_model(model[0], model[1])
else:
assert False
# _keras.utils.plot_model(model, "model.png", show_shapes = True)
# Build network graph
self.data_format = _keras.backend.image_data_format()
self.keras_graph = Keras2Graph(model)
self.keras_graph.build()