A Unified Slim Client on PredictionService

The objective is unifying the clients:

• connect to a tensorflow model servable with specific name given from parameter

• capable of processing a batch of image_urls

slim_unified_client.py

• add slim_unified_client deps in example's BUILD

- ./tensorflow_serving/example/BUILD

...
py_binary(
    name = "slim_unified_client",
    srcs = [
        "slim_unified_client.py",
    ],
    srcs_version = "PY2AND3",
    deps = [
        "//tensorflow_serving/apis:predict_proto_py_pb2",
        "//tensorflow_serving/apis:prediction_service_proto_py_pb2",
        "@org_tensorflow//tensorflow:tensorflow_py",
    ],
)
...

• create slim unified client target

- ./tensorflow_serving/example/slim_unified_client.py
...

#!/usr/bin/env python2.7

"""Send image_urls to tensorflow_model_server loaded with slim model.
"""

from __future__ import print_function

import urllib2

from multiprocessing.pool import ThreadPool

# This is a placeholder for a Google-internal import.

from grpc.beta import implementations
import tensorflow as tf

from tensorflow_serving.apis import predict_pb2
from tensorflow_serving.apis import prediction_service_pb2


tf.app.flags.DEFINE_string(
  'server', 'localhost:9000', 'PredictionService host:port'
)
tf.app.flags.DEFINE_string(
  'model_name', '', 'Tensorflow Serving Model Name'
)
tf.app.flags.DEFINE_string(
  'image_urls', '', 'URL to image in JPEG format, comma separated URLs.'
)
FLAGS = tf.app.flags.FLAGS


def fetch_url(url):
    try:
        response = urllib2.urlopen(url)
        return url, response.read(), None
    except Exception as e:
        return url, None, e

def main(_):
  host, port = FLAGS.server.split(':')
  channel = implementations.insecure_channel(host, int(port))
  stub = prediction_service_pb2.beta_create_PredictionService_stub(channel)
  # Send request
  # See prediction_service.proto for gRPC request/response details.
  image_urls = FLAGS.image_urls.split(',')
  print('image_urls:', image_urls)
  image_fetch_results = ThreadPool(128).map(fetch_url, image_urls)
  image_bytes = [
    result[1] for result in image_fetch_results if result[2] is None
  ]
  for result in image_fetch_results:
    if result[2] is not None:
      print('Error in Fetch URL: {}'.format(result[2]))
  request = predict_pb2.PredictRequest()
  request.model_spec.name = FLAGS.model_name
  request.model_spec.signature_name = 'predict_images'
  request.inputs['images'].CopyFrom(
    tf.contrib.util.make_tensor_proto(
      image_bytes, shape=[len(image_bytes)]
    )
  )
  result = stub.Predict(request, 60.0)  # 60 secs timeout
  print(result)


if __name__ == '__main__':
  tf.app.run()
...

• server

# open a new terminal //src/serving
$ bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server \
    --model_name=slim_inception_resnet_v2 \
    --model_base_path=$PWD/tf_servables/slim/inception-resnet-v2 \
    --port=9000 &

# open a new terminal //src/serving
$ bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server \
    --model_name=slim_inception_v4 \
    --model_base_path=$PWD/tf_servables/slim/inception-v4 \
    --port=9090 &

• client

# open a new terminal //src/serving
$ bazel --output_user_root=./tf_bazel_cache build -c opt //tensorflow_serving/example:slim_unified_client

$ bazel-bin/tensorflow_serving/example/slim_unified_client \
    --server=localhost:9000 \
    --model_name=slim_inception_resnet_v2 \
    --image_urls=/comma/separated/urls/to/my_favoriate_image.jpg

$ bazel-bin/tensorflow_serving/example/slim_unified_client \
    --server=localhost:9090 \
    --model_name=slim_inception_v4 \
    --image_urls=/comma/separated/urls/to/my_favoriate_image.jpg

$ bazel-bin/tensorflow_serving/example/slim_unified_client \
    --server=localhost:9000 \
    --model_name=slim_inception_resnet_v2 \
    --image_url=https://upload.wikimedia.org/wikipedia/commons/d/d9/First_Student_IC_school_bus_202076.jpg,\
https://upload.wikimedia.org/wikipedia/commons/thumb/9/90/Labrador_Retriever_portrait.jpg/1200px-Labrador_Retriever_portrait.jpg,\
https://upload.wikimedia.org/wikipedia/commons/f/fd/Qantas_a380_vh-oqa_takeoff_heathrow_arp.jpg

$ bazel-bin/tensorflow_serving/example/slim_unified_client \
    --server=localhost:9090 \
    --model_name=slim_inception_v4 \
    --image_url=https://upload.wikimedia.org/wikipedia/commons/d/d9/First_Student_IC_school_bus_202076.jpg,\
https://upload.wikimedia.org/wikipedia/commons/thumb/9/90/Labrador_Retriever_portrait.jpg/1200px-Labrador_Retriever_portrait.jpg,\
https://upload.wikimedia.org/wikipedia/commons/f/fd/Qantas_a380_vh-oqa_takeoff_heathrow_arp.jpg

# note: classes, prelogits, and scores are tensors with shape [n-images] x [k-outputs]