tf_agents.bandits.metrics.tf_metrics.SuboptimalArmsMetric
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Computes the number of suboptimal arms with respect to a baseline.
Inherits From: TFStepMetric
tf_agents.bandits.metrics.tf_metrics.SuboptimalArmsMetric(
baseline_action_fn: Callable[[tf_agents.typing.types.Tensor], tf_agents.typing.types.Tensor],
name: Optional[Text] = 'SuboptimalArmsMetric',
dtype: float = tf.float32
)
Args |
|---|
baseline_action_fn
|
function that computes the action used as a baseline
for computing the metric.
|
name
|
(str) name of the metric
|
dtype
|
dtype of the metric value.
|
Methods
call
View source
call(
trajectory
)
Update the metric value.
| Args |
|---|
trajectory
|
A tf_agents.trajectory.Trajectory
|
| Returns |
|---|
|
The arguments, for easy chaining.
|
init_variables
View source
init_variables()
Initializes this Metric's variables.
Should be called after variables are created in the first execution
of __call__(). If using graph execution, the return value should be
run() in a session before running the op returned by __call__().
(See example above.)
| Returns |
|---|
|
If using graph execution, this returns an op to perform the
initialization. Under eager execution, the variables are reset to their
initial values as a side effect and this function returns None.
|
reset
View source
reset()
Resets the values being tracked by the metric.
result
View source
result()
Computes and returns a final value for the metric.
tf_summaries
View source
tf_summaries(
train_step=None, step_metrics=()
)
Generates summaries against train_step and all step_metrics.
| Args |
|---|
train_step
|
(Optional) Step counter for training iterations. If None, no
metric is generated against the global step.
|
step_metrics
|
(Optional) Iterable of step metrics to generate summaries
against.
|
| Returns |
|---|
|
A list of summaries.
|
__call__
View source
__call__(
*args, **kwargs
)
Returns op to execute to update this metric for these inputs.
Returns None if eager execution is enabled.
Returns a graph-mode function if graph execution is enabled.
| Args |
|---|
*args
|
|
**kwargs
|
A mini-batch of inputs to the Metric, passed on to call().
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf_agents.bandits.metrics.tf_metrics.SuboptimalArmsMetric\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/agents/blob/v0.19.0/tf_agents/bandits/metrics/tf_metrics.py#L84-L126) |\n\nComputes the number of suboptimal arms with respect to a baseline.\n\nInherits From: [`TFStepMetric`](../../../../tf_agents/metrics/tf_metric/TFStepMetric) \n\n tf_agents.bandits.metrics.tf_metrics.SuboptimalArmsMetric(\n baseline_action_fn: Callable[[../../../../tf_agents/typing/types/Tensor], ../../../../tf_agents/typing/types/Tensor],\n name: Optional[Text] = 'SuboptimalArmsMetric',\n dtype: float = tf.float32\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------------|--------------------------------------------------------------------------------|\n| `baseline_action_fn` | function that computes the action used as a baseline for computing the metric. |\n| `name` | (str) name of the metric |\n| `dtype` | dtype of the metric value. |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `call`\n\n[View source](https://github.com/tensorflow/agents/blob/v0.19.0/tf_agents/bandits/metrics/tf_metrics.py#L109-L123) \n\n call(\n trajectory\n )\n\nUpdate the metric value.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|--------------|-----------------------------------|\n| `trajectory` | A tf_agents.trajectory.Trajectory |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| The arguments, for easy chaining. ||\n\n\u003cbr /\u003e\n\n### `init_variables`\n\n[View source](https://github.com/tensorflow/agents/blob/v0.19.0/tf_agents/metrics/tf_metric.py#L61-L75) \n\n init_variables()\n\nInitializes this Metric's variables.\n\nShould be called after variables are created in the first execution\nof `__call__()`. If using graph execution, the return value should be\n`run()` in a session before running the op returned by `__call__()`.\n(See example above.)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| If using graph execution, this returns an op to perform the initialization. Under eager execution, the variables are reset to their initial values as a side effect and this function returns None. ||\n\n\u003cbr /\u003e\n\n### `reset`\n\n[View source](https://github.com/tensorflow/agents/blob/v0.19.0/tf_agents/metrics/tf_metric.py#L53-L55) \n\n reset()\n\nResets the values being tracked by the metric.\n\n### `result`\n\n[View source](https://github.com/tensorflow/agents/blob/v0.19.0/tf_agents/bandits/metrics/tf_metrics.py#L125-L126) \n\n result()\n\nComputes and returns a final value for the metric.\n\n### `tf_summaries`\n\n[View source](https://github.com/tensorflow/agents/blob/v0.19.0/tf_agents/metrics/tf_metric.py#L94-L126) \n\n tf_summaries(\n train_step=None, step_metrics=()\n )\n\nGenerates summaries against train_step and all step_metrics.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------------|-----------------------------------------------------------------------------------------------------------|\n| `train_step` | (Optional) Step counter for training iterations. If None, no metric is generated against the global step. |\n| `step_metrics` | (Optional) Iterable of step metrics to generate summaries against. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A list of summaries. ||\n\n\u003cbr /\u003e\n\n### `__call__`\n\n[View source](https://github.com/tensorflow/agents/blob/v0.19.0/tf_agents/metrics/tf_metric.py#L82-L92) \n\n __call__(\n *args, **kwargs\n )\n\nReturns op to execute to update this metric for these inputs.\n\nReturns None if eager execution is enabled.\nReturns a graph-mode function if graph execution is enabled.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|------------|--------------------------------------------------------------|\n| `*args` | \u003cbr /\u003e \u003cbr /\u003e |\n| `**kwargs` | A mini-batch of inputs to the Metric, passed on to `call()`. |\n\n\u003cbr /\u003e"]]
View source on GitHub