in machine-learning-notebooks/02-mobilenet-transfer-learning-scripts/retrain.py [0:0]
def create_model_info(architecture, model_download_url):
"""Given the name of a model architecture, returns information about it.
There are different base image recognition pretrained models that can be
retrained using transfer learning, and this function translates from the name
of a model to the attributes that are needed to download and train with it.
Args:
architecture: Name of a model architecture.
Returns:
Dictionary of information about the model, or None if the name isn't
recognized
Raises:
ValueError: If architecture name is unknown.
"""
architecture = architecture.lower()
if architecture == 'inception_v3':
# pylint: disable=line-too-long
data_url = 'http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz'
# pylint: enable=line-too-long
bottleneck_tensor_name = 'pool_3/_reshape:0'
bottleneck_tensor_size = 2048
input_width = 299
input_height = 299
input_depth = 3
resized_input_tensor_name = 'Mul:0'
model_file_name = 'classify_image_graph_def.pb'
input_mean = 128
input_std = 128
elif architecture.startswith('mobilenet_'):
parts = architecture.split('_')
if len(parts) != 3 and len(parts) != 4:
tf.logging.error("Couldn't understand architecture name '%s'",
architecture)
return None
version_string = parts[1]
if (version_string != '1.0' and version_string != '0.75' and
version_string != '0.50' and version_string != '0.25'):
tf.logging.error(
""""The Mobilenet version should be '1.0', '0.75', '0.50', or '0.25',
but found '%s' for architecture '%s'""",