class_docstr: Base class for weight constraints.
  
  A `Constraint` instance works like a stateless function.
  Users who subclass this
  class should override the `__call__` method, which takes a single
  weight parameter and return a projected version of that parameter
  (e.g. normalized or clipped). Constraints can be used with various Keras
  layers via the `kernel_constraint` or `bias_constraint` arguments.
  
  Here's a simple example of a non-negative weight constraint:
  
  >>> class NonNegative(tf.keras.constraints.Constraint):
  ...
  ...  def __call__(self, w):
  ...    return w * tf.cast(tf.math.greater_equal(w, 0.), w.dtype)
  
  >>> weight = tf.constant((-1.0, 1.0))
  >>> NonNegative()(weight)
  <tf.Tensor: shape=(2,), dtype=float32, numpy=array([0.,  1.], dtype=float32)>
  
  >>> tf.keras.layers.Dense(4, kernel_constraint=NonNegative())
docstr: Applies the constraint to the input weight variable.
  
  By default, the inputs weight variable is not modified.
  Users should override this method to implement their own projection
  function.
  
  Args:
    w: Input weight variable.
  
  Returns:
    Projected variable (by default, returns unmodified inputs).
docstr_tok: ["Applies","the","constraint","to","the","input","weight","variable",".","By","default",",","the","inputs","weight","variable","is","not","modified",".","Users","should","override","this","method","to","implement","their","own","projection","function",".","Args",":","w",":","Input","weight","variable",".","Returns",":","Projected","variable","(","by","default",",","returns","unmodified","inputs",")","."]
code: def __call__(self, w):
      """Applies the constraint to the input weight variable.
  
      By default, the inputs weight variable is not modified.
      Users should override this method to implement their own projection
      function.
  
      Args:
        w: Input weight variable.
  
      Returns:
        Projected variable (by default, returns unmodified inputs).
      """
      return w
  
imports: from tensorflow.python.framework import tensor_shape
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.utils.generic_utils import deserialize_keras_object
  from tensorflow.python.keras.utils.generic_utils import serialize_keras_object
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import while_loop
  from tensorflow.tools.docs import doc_controls
label_desc: Use image node_id 1 for calling the Constraint obj's underlying member method code with example usage: obj.__call__(w) and returns: w