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SivananthamandGitHub
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* Fix python linter Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Format e2e tests Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Format hack, docs Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Add py-fmt target Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Update python lint workflow Signed-off-by: Sivanantham Chinnaiyan <[email protected]> * Rebase master Signed-off-by: Sivanantham Chinnaiyan <[email protected]> --------- Signed-off-by: Sivanantham Chinnaiyan <[email protected]>
73 lines
2.2 KiB
Python
73 lines
2.2 KiB
Python
import argparse
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import json
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import base64
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import grpc
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from tensorflow.contrib.util import make_tensor_proto
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from tensorflow_serving.apis import predict_pb2
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from tensorflow_serving.apis import prediction_service_pb2_grpc
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def predict(host, port, hostname, model, signature_name, input_path):
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# If hostname not set, we assume the host is a valid knative dns.
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if hostname:
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host_option = (
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(
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"grpc.ssl_target_name_override",
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hostname,
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),
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)
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else:
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host_option = None
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channel = grpc.insecure_channel(
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target="{host}:{port}".format(host=host, port=port), options=host_option
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)
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stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)
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with open(input_path) as json_file:
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data = json.load(json_file)
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image = data["instances"][0]["image_bytes"]["b64"]
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key = data["instances"][0]["key"]
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# Call classification model to make prediction
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request = predict_pb2.PredictRequest()
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request.model_spec.name = model
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request.model_spec.signature_name = signature_name
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image = base64.b64decode(image)
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request.inputs["image_bytes"].CopyFrom(make_tensor_proto(image, shape=[1]))
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request.inputs["key"].CopyFrom(make_tensor_proto(key, shape=[1]))
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result = stub.Predict(request, 10.0)
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print(result)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--host", help="Ingress Host Name", default="localhost", type=str
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)
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parser.add_argument("--port", help="Ingress Port", default=80, type=int)
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parser.add_argument("--model", help="TensorFlow Model Name", type=str)
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parser.add_argument(
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"--signature_name",
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help="Signature name of saved TensorFlow model",
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default="serving_default",
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type=str,
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)
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parser.add_argument("--hostname", help="Service Host Name", default="", type=str)
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parser.add_argument(
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"--input_path",
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help="Prediction data input path",
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default="./input.json",
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type=str,
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)
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args = parser.parse_args()
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predict(
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args.host,
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args.port,
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args.hostname,
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args.model,
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args.signature_name,
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args.input_path,
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)
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