model_base_path: 模型所在目录。
nohup tensorflow_model_server \ --rest_api_port=8501 \ --model_name=fashion_model \ --model_base_path="/tmp/tfx" >server.log 2>&1 & $ tail server.log To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2021-04-13 15:12:10.706648: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:206] Restoring SavedModel bundle. 2021-04-13 15:12:10.726722: I external/org_tensorflow/tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2599990000 Hz 2021-04-13 15:12:10.756506: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:190] Running initialization op on SavedModel bundle at path: /tmp/tfx/1 2021-04-13 15:12:10.759935: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:277] SavedModel load for tags { serve }; Status: success: OK. Took 110653 microseconds. 2021-04-13 15:12:10.760277: I tensorflow_serving/servables/tensorflow/saved_model_warmup_util.cc:59] No warmup data file found at /tmp/tfx/1/assets.extra/tf_serving_warmup_requests 2021-04-13 15:12:10.760486: I tensorflow_serving/core/loader_harness.cc:87] Successfully loaded servable version {name: fashion_model version: 1} 2021-04-13 15:12:10.763938: I tensorflow_serving/model_servers/server.cc:371] Running gRPC ModelServer at 0.0.0.0:8500 ... [evhttp_server.cc : 238] NET_LOG: Entering the event loop ... 2021-04-13 15:12:10.765308: I tensorflow_serving/model_servers/server.cc:391] Exporting HTTP/REST API at:localhost:8501 ... 访问服务随机显示一张测试图：
def show(idx, title): plt.figure() plt.imshow(test_images[idx].reshape(28,28)) plt.axis('off') plt.title('\n\n{}'.format(title), fontdict={'size': 16}) import random rando = random.randint(0,len(test_images)-1) show(rando, 'An Example Image: {}'.format(class_names[test_labels[rando]]))
创建 JSON 对象，给到三张要预测的图：
import json data = json.dumps({"signature_name": "serving_default", "instances": test_images[0:3].tolist()}) print('Data: {} ... {}'.format(data[:50], data[len(data)-52:])) Data: {"signature_name": "serving_default", "instances": ... [0.0], [0.0], [0.0], [0.0], [0.0], [0.0], [0.0]]]]} REST 请求最新模型版本进行预测：
!pip install -q requests import requests headers = {"content-type": "application/json"} json_response = requests.post('http://localhost:8501/v1/models/fashion_model:predict', data=data, headers=headers) predictions = json.loads(json_response.text)['predictions'] show(0, 'The model thought this was a {} (class {}), and it was actually a {} (class {})'.format( class_names[np.argmax(predictions[0])], np.argmax(predictions[0]), class_names[test_labels[0]], test_labels[0]))