tf.clip_by_value()

Clips tensor values to a specified min and max.

tf.clip_by_value(
    t,
    clip_value_min,
    clip_value_max,
    name=None
)

Used in the tutorials:

• DeepDream
• Adversarial example using FGSM
• Neural style transfer

Given a tensor t, this operation returns a tensor of the same type and shape as t with its values clipped to clip_value_min and clip_value_max. Any values less than clip_value_min are set to clip_value_min. Any values greater than clip_value_max are set to clip_value_max.

Note: clip_value_min needs to be smaller or equal to clip_value_max for correct results.

For example:

A = tf.constant([[1, 20, 13], [3, 21, 13]])
B = tf.clip_by_value(A, clip_value_min=0, clip_value_max=3) # [[1, 3, 3],[3, 3, 3]]
C = tf.clip_by_value(A, clip_value_min=0., clip_value_max=3.) # throws `TypeError`
as input and clip_values are of different dtype

Args:

• t: A Tensor or IndexedSlices.
• clip_value_min: A 0-D (scalar) Tensor, or a Tensor with the same shape as t. The minimum value to clip by.
• clip_value_max: A 0-D (scalar) Tensor, or a Tensor with the same shape as t. The maximum value to clip by.
• name: A name for the operation (optional).

Returns:

• A clipped Tensor or IndexedSlices.

Raises:

• ValueError: If the clip tensors would trigger array broadcasting that would make the returned tensor larger than the input.
• TypeError: If dtype of the input is int32 and dtype of the clip_value_min' orclip_value_maxisfloat32`