我正在尝试通过提供的示例从google colab调用经过训练的模型。
但是有一个错误。
谁知道这是beta错误还是我没有正确设置某些东西?
谢谢。
代码
Map<LocalDate, MenuChart2.Statistics> last3MPerDay =
menuPriceByDayService.findAllOrderByUpdateDate(menu, DateUtils.quarterlyDate(), 92)
.stream()
.sorted(comparing(MenuPriceByDay::getUpdateDate))
.collect(Collectors
.toMap(MenuPriceByDay::getUpdateLocalDate, p -> new MenuChart2().new Statistics( p.getMinPrice().doubleValue());
TreeMap<LocalDate, , MenuChart2.Statistics> last3MPerDaySorted = new TreeMap<LocalDate, MenuChart2.Statistics>(last3MPerDay);
错误信息^
from google.cloud import automl_v1beta1 as automl
automl_client = automl.AutoMlClient()
# Create client for prediction service.
prediction_client =
automl.PredictionServiceClient().from_service_account_json(
'XXXXX.json')
# Get the full path of the model.
model_full_id = automl_client.model_path(
project_id, compute_region, model_id
)
# Read the file content for prediction.
#with open(file_path, "rb") as content_file:
snippet = "fsfsf" #content_file.read()
# Set the payload by giving the content and type of the file.
payload = {"text_snippet": {"content": snippet, "mime_type": "text/plain"}}
# params is additional domain-specific parameters.
# currently there is no additional parameters supported.
params = {}
response = prediction_client.predict(model_full_id, payload, params)
print("Prediction results:")
for result in response.payload:
print("Predicted class name: {}".format(result.display_name))
print("Predicted class score: {}".format(result.classification.score))
答案 0 :(得分:0)
您必须使用支持AutoML beta的区域。这对我有用:
create_dataset("myproj-123456", "us-central1", "my_dataset_id", "en", "de")
答案 1 :(得分:0)
$ git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git
$ cd / home / MY_USER / python-docs-samples / language / automl /
我为[1]设置了环境变量:
我输入了:
$ python automl_natural_language_dataset.py create_dataset automltest1 False
数据集名称:projects / 198768927566 / locations / us-central1 / datasets / TCN7889001684301386365 数据集ID:TCN7889001684301386365 数据集显示名称:automltest1 文本分类数据集元数据: category_type:MULTICLASS
数据集示例计数:0 数据集创建时间: 秒:1569367227 纳米:873147000
我为设置环境变量:
请注意,我已经在步骤5中得到了它。
python automl_natural_language_dataset.py import_data $ DATASET_ID“ gs://$PROJECT_ID-lcm/complaints_manual.csv”
正在处理导入... 数据集已导入。