不支持 'Unknown' 类型的输入。支持的类型:[azureml.data.tabular_dataset.TabularDataset、azureml.pipeline.core
Input of type 'Unknown' is not supported. Supported types: [azureml.data.tabular_dataset.TabularDataset, azureml.pipeline.core
training_data 可以是数据框或数据集。
但是,当我使用数据框时出现此错误:
ConfigException: ConfigException:
Message: Input of type 'Unknown' is not supported. Supported types: [azureml.data.tabular_dataset.TabularDataset, azureml.pipeline.core.pipeline_output_dataset.PipelineOutputTabularDataset]
InnerException: None
ErrorResponse
{
"error": {
"code": "UserError",
"message": "Input of type 'Unknown' is not supported. Supported types: [azureml.data.tabular_dataset.TabularDataset, azureml.pipeline.core.pipeline_output_dataset.PipelineOutputTabularDataset]",
"details_uri": "https://aka.ms/AutoMLConfig",
"target": "training_data",
"inner_error": {
"code": "BadArgument",
"inner_error": {
"code": "ArgumentInvalid",
"inner_error": {
"code": "InvalidInputDatatype"
}
}
}
}
}
我的代码真的很简单:
client = CosmosClient(HOST, MASTER_KEY)
database = client.get_database_client(database=DATABASE_ID)
container = database.get_container_client(CONTAINER_ID)
item_list = list(container.read_all_items(max_item_count=10))
df = pd.DataFrame(item_list)
from azureml.core.workspace import Workspace
ws = Workspace.from_config()
from azureml.automl.core.forecasting_parameters import ForecastingParameters
forecasting_parameters = ForecastingParameters(time_column_name='EventEnqueuedUtcTime',
forecast_horizon=50,
time_series_id_column_names=["eui"],
freq='H',
target_lags='auto',
target_rolling_window_size=10)
from azureml.core.workspace import Workspace
from azureml.core.experiment import Experiment
from azureml.train.automl import AutoMLConfig
from azureml.core.compute import ComputeTarget, AmlCompute
import logging
amlcompute_cluster_name = "computecluster"
compute_target = ComputeTarget(workspace=ws, name=amlcompute_cluster_name)
experiment_name = 'iot-forecast'
experiment = Experiment(ws, experiment_name)
automl_config = AutoMLConfig(task='forecasting',
primary_metric='normalized_root_mean_squared_error',
experiment_timeout_minutes=100,
enable_early_stopping=True,
training_data=df,
compute_target = compute_target,
label_column_name='TempC_DS',
n_cross_validations=5,
enable_ensembling=False,
verbosity=logging.INFO,
forecasting_parameters=forecasting_parameters)
remote_run = experiment.submit(automl_config, show_output=True)
我在这里错过了什么?
看来您正在尝试远程 运行 实验,AFAIK 并根据文档 here :
您可以参考这篇文章来了解创建Azure ML TabularDataset
training_data 可以是数据框或数据集。
但是,当我使用数据框时出现此错误:
ConfigException: ConfigException:
Message: Input of type 'Unknown' is not supported. Supported types: [azureml.data.tabular_dataset.TabularDataset, azureml.pipeline.core.pipeline_output_dataset.PipelineOutputTabularDataset]
InnerException: None
ErrorResponse
{
"error": {
"code": "UserError",
"message": "Input of type 'Unknown' is not supported. Supported types: [azureml.data.tabular_dataset.TabularDataset, azureml.pipeline.core.pipeline_output_dataset.PipelineOutputTabularDataset]",
"details_uri": "https://aka.ms/AutoMLConfig",
"target": "training_data",
"inner_error": {
"code": "BadArgument",
"inner_error": {
"code": "ArgumentInvalid",
"inner_error": {
"code": "InvalidInputDatatype"
}
}
}
}
}
我的代码真的很简单:
client = CosmosClient(HOST, MASTER_KEY)
database = client.get_database_client(database=DATABASE_ID)
container = database.get_container_client(CONTAINER_ID)
item_list = list(container.read_all_items(max_item_count=10))
df = pd.DataFrame(item_list)
from azureml.core.workspace import Workspace
ws = Workspace.from_config()
from azureml.automl.core.forecasting_parameters import ForecastingParameters
forecasting_parameters = ForecastingParameters(time_column_name='EventEnqueuedUtcTime',
forecast_horizon=50,
time_series_id_column_names=["eui"],
freq='H',
target_lags='auto',
target_rolling_window_size=10)
from azureml.core.workspace import Workspace
from azureml.core.experiment import Experiment
from azureml.train.automl import AutoMLConfig
from azureml.core.compute import ComputeTarget, AmlCompute
import logging
amlcompute_cluster_name = "computecluster"
compute_target = ComputeTarget(workspace=ws, name=amlcompute_cluster_name)
experiment_name = 'iot-forecast'
experiment = Experiment(ws, experiment_name)
automl_config = AutoMLConfig(task='forecasting',
primary_metric='normalized_root_mean_squared_error',
experiment_timeout_minutes=100,
enable_early_stopping=True,
training_data=df,
compute_target = compute_target,
label_column_name='TempC_DS',
n_cross_validations=5,
enable_ensembling=False,
verbosity=logging.INFO,
forecasting_parameters=forecasting_parameters)
remote_run = experiment.submit(automl_config, show_output=True)
我在这里错过了什么?
看来您正在尝试远程 运行 实验,AFAIK 并根据文档 here :
您可以参考这篇文章来了解创建Azure ML TabularDataset