部署的Tensorflow为Inception-V3服务并运行测试。工作正常。如何在Tensorflow服务中进行批处理?
现在,想为Inception-V3服务的批处理。 例如想要发送10个图像进行预测而不是一个。
如何做到这一点?要更新哪些文件(inception_saved_model.py或inception_client.py)?这些更新是什么样子的?以及图像如何传递给服务 - 它是以包含图像的文件夹的形式传递的?
感谢您对此问题的深入了解。任何与此相关的代码片段都会非常有用。
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更新inception_client.py
# Copyright 2016 Google Inc. 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.
# ==============================================================================
#!/usr/bin/env python2.7
"""Send JPEG image to tensorflow_model_server loaded with inception model.
"""
from __future__ import print_function
"""Send JPEG image to tensorflow_model_server loaded with inception model.
"""
from __future__ import print_function
# This is a placeholder for a Google-internal import.
from grpc.beta import implementations
import tensorflow as tf
from tensorflow.python.platform import flags
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('image', '', 'path to image in JPEG format')
FLAGS = tf.app.flags.FLAGS
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
#with open(FLAGS.image, 'rb') as f:
# See prediction_service.proto for gRPC request/response details.
#data = f.read()
#request = predict_pb2.PredictRequest()
#request.model_spec.name = 'inception'
#request.model_spec.signature_name = 'predict_images'
# request.inputs['images'].CopyFrom(
# tf.contrib.util.make_tensor_proto(data, shape=[1]))
# result = stub.Predict(request, 10.0) # 10 secs timeout
# print(result)
# Build a batch of images
request = predict_pb2.PredictRequest()
request.model_spec.name = 'inception'
request.model_spec.signature_name = 'predict_images'
image_data = []
for image in FLAGS.image.split(','):
with open(image, 'rb') as f:
image_data.append(f.read())
request.inputs['images'].CopyFrom(
tf.contrib.util.make_tensor_proto(image_data, shape=[len(image_data)]))
result = stub.Predict(request, 10.0) # 10 secs timeout
print(result)
if __name__ == '__main__':
tf.app.run()
您能检查粘贴代码的缩进吗? (这可能是堆栈溢出格式化的问题,但它可能隐藏了一个错误。)当前出现的错误是什么? – mrry
看起来像堆栈溢出格式问题。将尝试解决这个问题。这里是error.bazel-bin/tensorflow_serving/example/inception_batch_client --server = localhost:9000 -image =/home/gpuadmin/serving/images/boat.jpg,/ home/gpuadmin/serving/images/boat.jpg 回溯(最近一次调用最后一次): 文件“/home/gpuadmin/serving/bazel-bin/tensorflow_serving/example/inception_batch_client.runfiles/tf_serving/tensorflow_serving/example/inception_batch_client.py”,第63行,在 中打开图像,'rb')为f: IOError:[Errno 2]没有这样的文件或目录:'' –
由于您正尝试读取未找到的文件而引发错误。它似乎试图打开''''(空字符串),所以也许'FLAGS.image'没有正确的格式?也许尝试打印'FLAGS.image.split(',')'来找出发生了什么问题? – mrry