//"""Update 'ref' by adding 'value' to it.
//
// This operation outputs "ref" after the update is done.
// This makes it easier to chain operations that need to use the reset value.
//
// Args:
// ref: A mutable `Tensor`. Must be one of the following types:
// `float32`, `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`,
// `int8`, `complex64`, `complex128`, `qint8`, `quint8`, `qint32`, `half`.
// Should be from a `Variable` node.
// value: A `Tensor`. Must have the same type as `ref`.
// The value to be added to the variable.
// use_locking: An optional `bool`. Defaults to `False`.
// If True, the addition will be protected by a lock;
// otherwise the behavior is undefined, but may exhibit less contention.
// name: A name for the operation (optional).
//
// Returns:
// Same as "ref". Returned as a convenience for operations that want
// to use the new value after the variable has been updated.
public static Tensor assign_add <T>(IVariableV1 @ref,
T value,
bool use_locking = false,
string name = null)
{
if (tf.executing_eagerly())
{
return(@ref.assign_add(value, use_locking: use_locking, name: name));
}
else
{
return(gen_state_ops.assign_add(@ref, value, use_locking: use_locking, name: name));
}
}
public Tensor update_state(Tensor values, Tensor sample_weight = null)
{
if (sample_weight != null)
{
(values, sample_weight) = losses_utils.squeeze_or_expand_dimensions(
values, sample_weight: sample_weight);
sample_weight = math_ops.cast(sample_weight, dtype: values.dtype);
values = math_ops.multiply(values, sample_weight);
}
Tensor update_total_op = null;
var value_sum = math_ops.reduce_sum(values);
tf_with(ops.control_dependencies(new[] { value_sum }), ctl =>
{
var update_total_op = total.assign_add(value_sum);
});
Tensor num_values = null;
if (_reduction == ReductionV2.WEIGHTED_MEAN)
{
if (sample_weight == null)
{
num_values = math_ops.cast(array_ops.size(values), _dtype);
}
else
{
num_values = math_ops.reduce_sum(sample_weight);
}
}
return(tf_with(ops.control_dependencies(new[] { update_total_op }), ctl
=> count.assign_add(num_values)));
}
//"""Update 'ref' by adding 'value' to it.
//
// This operation outputs "ref" after the update is done.
// This makes it easier to chain operations that need to use the reset value.
//
// Args:
// ref: A mutable `Tensor`. Must be one of the following types:
// `float32`, `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`,
// `int8`, `complex64`, `complex128`, `qint8`, `quint8`, `qint32`, `half`.
// Should be from a `Variable` node.
// value: A `Tensor`. Must have the same type as `ref`.
// The value to be added to the variable.
// use_locking: An optional `bool`. Defaults to `False`.
// If True, the addition will be protected by a lock;
// otherwise the behavior is undefined, but may exhibit less contention.
// name: A name for the operation (optional).
//
// Returns:
// Same as "ref". Returned as a convenience for operations that want
// to use the new value after the variable has been updated.
public static ITensorOrOperation assign_add <T>(IVariableV1 @ref,
T value,
bool use_locking = false,
string name = null)
=> @ref.assign_add(value, use_locking: use_locking, name: name);
