class_docstr: Keras test
class_docstr_tok: ["Keras","test"]
docstr: test_forward_l2_normalize
docstr_tok: ["test_forward_l2_normalize"]
code: def test_forward_l2_normalize(self, keras_mod):
      """test_forward_l2_normalize"""
      data = keras_mod.layers.Input(shape=(16, 12, 8))
      k_backend = keras_mod.backend
      l2_funcs = [
          keras_mod.layers.Lambda(
              lambda v: k_backend.l2_normalize(v, axis=-2)
          ),
          keras_mod.layers.Lambda(
              lambda v: k_backend.l2_normalize(x=v, axis=-1)
          ),
          keras_mod.layers.Lambda(
              lambda v: k_backend.l2_normalize(axis=1, x=v)
          ),
          keras_mod.layers.Lambda(
              lambda v: k_backend.l2_normalize(v, 2)
          ),
          keras_mod.layers.Lambda(
              lambda v: k_backend.l2_normalize(v, axis=3)
          ),
          keras_mod.layers.Lambda(
              lambda v: k_backend.l2_normalize(v, axis=(2, 3))
          ),
          keras_mod.layers.Lambda(
              lambda v: k_backend.l2_normalize(v, (1, 2))
          ),
          keras_mod.layers.Lambda(
              lambda v: k_backend.l2_normalize(v, axis=[-2, -1])
          ),
          keras_mod.layers.Lambda(
              lambda v: k_backend.l2_normalize(v, [-3, -2])
          ),
      ]
      for l2_func in l2_funcs:
          x = l2_func(data)
          keras_model = keras_mod.models.Model(data, x)
          verify_keras_frontend(keras_model, layout="NCHW")
          verify_keras_frontend(keras_model, layout="NHWC")
  
imports: from packaging import version
  import numpy
  from tensorflow import keras
  import keras
  import pytest
  import tvm
  from tvm import relay
  from tvm.contrib import graph_executor
  import tvm.testing
label_desc: Use image node_id 36 for calling the TestKeras obj's underlying member method code with example usage: obj.test_forward_l2_normalize(keras_mod) without return types