tf.contrib.eager.metrics.Mean

Class Mean

Inherits From: Metric

Defined in tensorflow/contrib/eager/python/metrics_impl.py.

Computes the (weighted) mean of the given values.

__init__

__init__(
    name=None,
    dtype=tf.dtypes.double,
    use_global_variables=False
)

Initialize self. See help(type(self)) for accurate signature.

Properties

name

variables

Methods

tf.contrib.eager.metrics.Mean.__call__

__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().

tf.contrib.eager.metrics.Mean.add_variable

add_variable(
    name,
    shape=None,
    dtype=None,
    initializer=None
)

Only for use by descendants of Metric.

tf.contrib.eager.metrics.Mean.aggregate

aggregate(metrics)

Adds in the state from a list of metrics.

Default implementation sums all the metric variables.

Args:

• metrics: A list of metrics with the same type as self.

Raises:

• ValueError: If metrics contains invalid data.

tf.contrib.eager.metrics.Mean.build

build(
    *args,
    **kwargs
)

Method to create variables.

Called by __call__() before call() for the first time.

Args:

• *args: * **kwargs: The arguments to the first invocation of __call__(). build() may use the shape and/or dtype of these arguments when deciding how to create variables.

tf.contrib.eager.metrics.Mean.call

call(
    values,
    weights=None
)

Accumulate statistics for computing the mean.

For example, if values is [1, 3, 5, 7] then the mean is 4. If the weights were specified as [1, 1, 0, 0] then the mean would be 2.

Args:

• values: Tensor with the per-example value.
• weights: Optional weighting of each example. Defaults to 1.

Returns:

The arguments, for easy chaining.

tf.contrib.eager.metrics.Mean.init_variables

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.

tf.contrib.eager.metrics.Mean.result

result(write_summary=True)

Returns the result of the Metric.

Args:

• write_summary: bool indicating whether to feed the result to the summary before returning.

Returns:

aggregated metric as float.

Raises:

• ValueError: if the optional argument is not bool

tf.contrib.eager.metrics.Mean.value

value()

In graph mode returns the result Tensor while in eager the callable.