def test_yaml_server_loading():
file_path = "yaml/konduit.yaml"
server = server_from_file(file_path)
try:
running_server = server_from_file(file_path, start_server=True)
finally:
running_server.stop()
def test_word_tokenizer_serving_from_file():
file_path = "yaml/konduit_word_tokenizer_minimal.yaml"
server = server_from_file(file_path)
try:
running_server = server_from_file(file_path, start_server=True)
finally:
running_server.stop()
def test_wordpiece_tokenizer_serving_two_steps():
file_path = "yaml/konduit_wordpiece_tokenizer_two_steps.yaml"
server = server_from_file(file_path)
try:
running_server = server_from_file(file_path, start_server=True)
finally:
running_server.stop()
def test_tensor_flow_serving():
file_path = "yaml/konduit_tensorflow.yaml"
try:
server = server_from_file(file_path=file_path)
finally:
server.stop()
del server
def test_dl4j_samediff_serving():
file_path = "yaml/konduit_samediff.yaml"
try:
server = server_from_file(file_path=file_path)
finally:
server.stop()
del server
def test_tf_simple_serving():
file_path = "yaml/konduit_tf_simple.yaml"
try:
server = server_from_file(file_path=file_path)
finally:
server.stop()
del server
def test_json_minimal_loading():
file_path = "yaml/konduit_minimal.json"
try:
server = server_from_file(file_path, use_yaml=False, start_server=True)
client = client_from_file(file_path, use_yaml=False)
finally:
server.stop()
del server, client
def serve(config, start_server):
"""Serve a pipeline from a konduit configuration"""
from konduit.load import store_pid
from konduit.load import server_from_file
server = server_from_file(file_path=config, start_server=start_server)
store_pid(config, server.process.pid)
logging.info(">>> Started a Konduit server with PID " +
str(server.process.pid))
def test_yaml_server_python_prediction():
try:
konduit_yaml_path = "yaml/konduit_tf_inference.yaml"
img = np.load("../data/input_layer.npy")
server = server_from_file(konduit_yaml_path, start_server=True)
client = client_from_file(konduit_yaml_path)
predicted = client.predict(data_input={"input_layer": img})
result = dict(zip(np.arange(10), predicted[0].round(3)))
# {0: 0.0, 1: 0.0, 2: 0.001, 3: 0.001, 4: 0.0, 5: 0.0, 6: 0.0, 7: 0.998, 8: 0.0, 9: 0.0}
assert round(result.get(7) * 1000) == 998
server.stop()
finally:
server.stop()
def test_pid_creation_removal():
file_path = "yaml/konduit.yaml"
running_server = server_from_file(file_path, start_server=True)
# store the pid of this server and forget the Python object
pid = running_server.process.pid
store_pid(file_path=file_path, pid=running_server.process.pid)
del running_server
# retrieve the pid internally and kill the process
recov_pid = pop_pid(file_path=file_path)
assert pid == recov_pid
stop_server_by_pid(recov_pid)
def test_tensor_flow_serving():
file_path = "yaml/konduit_tensorflow.yaml"
server = server_from_file(file_path=file_path)
del server
def test_dl4j_samediff_serving():
file_path = "yaml/konduit_samediff.yaml"
server = server_from_file(file_path=file_path)
del server
def test_dl4j_cg_serving():
file_path = "yaml/konduit_dl4j_cg.yaml"
server = server_from_file(file_path=file_path)
del server
def test_tf_simple_serving():
file_path = "yaml/konduit_tf_simple.yaml"
server = server_from_file(file_path=file_path)
del server
def test_keras_serving():
file_path = "yaml/konduit_keras.yaml"
server = server_from_file(file_path=file_path)
del server
def test_yaml_minimal_loading():
file_path = "yaml/konduit_minimal.yaml"
server = server_from_file(file_path, use_yaml=True, start_server=True)
client = client_from_file(file_path, use_yaml=True)
del server, client
