how to save tensorflow model with tf.estimator - tensorflow

Question

I have the following example code to train and evaluate a cnn mnist model using tensorflow's estimator api:
def model_fn(features, labels, mode):
images = tf.reshape(features, [-1, 28, 28, 1])
model = Model()
logits = model(images)
predicted_logit = tf.argmax(input=logits, axis=1, output_type=tf.int32)
if mode == tf.estimator.ModeKeys.PREDICT:
probabilities = tf.nn.softmax(logits)
predictions = {
'predicted_logit': predicted_logit,
'probabilities': probabilities
}
return tf.estimator.EstimatorSpec(mode=mode, predictions=predictions)
else:
...
def mnist_train_and_eval(_):
train_data, train_labels, eval_data, eval_labels, val_data, val_labels = get_mnist_data()
# Create a input function to train
train_input_fn = tf.estimator.inputs.numpy_input_fn(
x= train_data,
y=train_labels,
batch_size=_BATCH_SIZE,
num_epochs=1,
shuffle=True)
# Create a input function to eval
eval_input_fn = tf.estimator.inputs.numpy_input_fn(
x= eval_data,
y=eval_labels,
batch_size=_BATCH_SIZE,
num_epochs=1,
shuffle=False)
# Create a estimator with model_fn
image_classifier = tf.estimator.Estimator(model_fn=model_fn, model_dir=_MODEL_DIR)
# Finally, train and evaluate the model after each epoch
for _ in range(_NUM_EPOCHS):
image_classifier.train(input_fn=train_input_fn)
metrics = image_classifier.evaluate(input_fn=eval_input_fn)
How can I use the estimator.export_savedmodel to save the trained model for later inference? How should I write the serving_input_receiver_fn?
Thank you very much for your help!

Answer 1

You create a function with a dictionary of input features. Placeholder should match the shape of your image, with first dimension for batch_size.
def serving_input_receiver_fn():
x = tf.placeholder(tf.float32, [None, Shape])
inputs = {'x': x}
return tf.estimator.export.ServingInputReceiver(features=inputs, receiver_tensors=inputs)
Or you can use TensorServingInputReceiver which doesn't required dict mapping
inputs = tf.placeholder(tf.float32, [None, 32*32*3])
tf.estimator.export.TensorServingInputReceiver(inputs, inputs)
This function returns new instance of ServingInputReceiver, which is passed to export_savedmodel or tf.estimator.FinalExporter
...
image_classifier.export_savedmodel(saved_dir, serving_input_receiver_fn)