ModelState Class
Model status.
- Inheritance
-
azure.ai.anomalydetector._model_base.ModelModelState
Constructor
ModelState(*args: Any, **kwargs: Any)
Variables
Name | Description |
---|---|
epoch_ids
|
This indicates the number of passes of the entire training dataset the algorithm has completed. |
train_losses
|
List of metrics used to assess how the model fits the training data for each epoch. |
validation_losses
|
List of metrics used to assess how the model fits the validation set for each epoch. |
latencies_in_seconds
|
Latency for each epoch. |
Methods
clear | |
copy | |
get | |
items | |
keys | |
pop | |
popitem | |
setdefault | |
update | |
values |
clear
clear() -> None
copy
copy()
get
get(key: str, default: Any = None) -> Any
Parameters
Name | Description |
---|---|
key
Required
|
|
default
|
Default value: None
|
items
items() -> ItemsView
keys
keys() -> KeysView
pop
pop(key: ~typing.Any, default: ~typing.Any = <object object>) -> Any
Parameters
Name | Description |
---|---|
key
Required
|
|
default
|
|
popitem
popitem() -> Tuple[str, Any]
setdefault
setdefault(key: ~typing.Any, default: ~typing.Any = <object object>) -> Any
Parameters
Name | Description |
---|---|
key
Required
|
|
default
|
|
update
update(*args: Any, **kwargs: Any) -> None
values
values() -> ValuesView
Attributes
epoch_ids
This indicates the number of passes of the entire training dataset the algorithm has completed.
epoch_ids: List[int] | None
latencies_in_seconds
Latency for each epoch.
latencies_in_seconds: List[float] | None
train_losses
List of metrics used to assess how the model fits the training data for each epoch.
train_losses: List[float] | None
validation_losses
List of metrics used to assess how the model fits the validation set for each epoch.
validation_losses: List[float] | None
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Azure SDK for Python