check_desired_sparsity.py

for layer in model.layers:
	if isinstance(layer, pruning_wrapper.PruneLowMagnitude):
	    for weight in layer.layer.get_prunable_weights():
	        print(np.allclose(
	            target_sparsity, get_sparsity(tf.keras.backend.get_value(weight)), 
	            rtol=1e-6, atol=1e-6)
            )

def get_sparsity(weights):
    return 1.0 - np.count_nonzero(weights) / float(weights.size)