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TensorFlow 1 version View source on GitHub

Clips tensor values to a specified min and max.


  • tf.compat.v1.clip_by_value
  • tf.compat.v2.clip_by_value

Used in the tutorials:

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.

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


  • 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).


A clipped Tensor or IndexedSlices.


  • 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`