class_docstr: Pruning schedule with constant sparsity, applied at any step.
class_docstr_tok: ["Pruning","schedule","with","constant","sparsity",",","applied","at","any","step","."]
docstr: Initializes a Pruning schedule with constant sparsity.
  
  Sparsity is applied at every step.
  
  Args:
    target_sparsity: Target sparsity as float, in [0, 1] interval.
docstr_tok: ["Initializes","a","Pruning","schedule","with","constant","sparsity",".","Sparsity","is","applied","at","every","step",".","Args",":","target_sparsity",":","Target","sparsity","as","float",",","in","[","0",",","1","]","interval","."]
code: def __init__(self, target_sparsity):
      """Initializes a Pruning schedule with constant sparsity.
  
      Sparsity is applied at every step.
  
      Args:
        target_sparsity: Target sparsity as float, in [0, 1] interval.
      """
      self.target_sparsity = target_sparsity
  
file_path: model-optimization/tensorflow_model_optimization/python/core/sparsity/keras/tools/sparsity_tooling.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import metrics
  from tensorflow_model_optimization.python.core.sparsity.keras import prune
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_schedule
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_wrapper
label_desc: Use image node_id 1 to create a new StepIndependentConstantSparsity object from inherited base classes: pruning_schedule with example: obj = StepIndependentConstantSparsity(target_sparsity)