#
# Copyright 2018-2019 IBM Corp. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from maxfw.model import MAXModelWrapper
import tensorflow as tf
from tensorflow import saved_model as sm
import logging
from config import DEFAULT_MODEL_PATH, ERR_MSG, MODEL_NAME, MODEL_LICENSE, MODEL_ID
logger = logging.getLogger()
class ModelWrapper(MAXModelWrapper):
"""Model wrapper for TensorFlow models in SavedModel format"""
MODEL_META_DATA = {
'id': MODEL_ID,
'name': MODEL_NAME,
'description': 'Converts a grayscale image to a color image.',
'type': 'Image-To-Image Translation',
'license': MODEL_LICENSE,
'source': 'https://developer.ibm.com/exchanges/models/all/max-image-colorizer'
}
def __init__(self, path=DEFAULT_MODEL_PATH):
logger.info('Loading model from: {}...'.format(path))
sess = tf.Session(graph=tf.Graph())
# Load the graph
model_graph_def = sm.loader.load(sess, [sm.tag_constants.SERVING], path)
sig_def = model_graph_def.signature_def[sm.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY]
input_name = sig_def.inputs['input_images'].name
output_name = sig_def.outputs['output_images'].name
# Set up instance variables and required inputs for inference
self.sess = sess
self.model_graph_def = model_graph_def
self.output_tensor = sess.graph.get_tensor_by_name(output_name)
self.input_name = input_name
self.output_name = output_name
logger.info('Loaded model')
def _predict(self, x):
# Run prediction on input
try:
preds = self.output_tensor.eval(feed_dict={self.input_name: x}, session=self.sess)
return preds
except tf.errors.InvalidArgumentError as e:
if 'Expected image' in e.message:
raise OSError(ERR_MSG)
else:
raise e
