1# Copyright 2019 The TensorFlow Authors. All Rights Reserved. 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15"""Test configs for l2norm_shared_epsilon.""" 16from __future__ import absolute_import 17from __future__ import division 18from __future__ import print_function 19 20import numpy as np 21import tensorflow.compat.v1 as tf 22from tensorflow.lite.testing.zip_test_utils import create_tensor_data 23from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests 24from tensorflow.lite.testing.zip_test_utils import register_make_test_function 25 26 27@register_make_test_function() 28def make_l2norm_shared_epsilon_tests(options): 29 """Regression test for a bug (b/122651451).""" 30 31 # Chose a set of parameters 32 test_parameters = [{ 33 "input_shape": [[5, 7]], 34 "dim": [1], 35 "epsilon": [1e-8], 36 }] 37 38 def build_graph(parameters): 39 input_tensor = tf.compat.v1.placeholder( 40 dtype=tf.float32, name="input", shape=parameters["input_shape"]) 41 epsilon = tf.constant(parameters["epsilon"]) 42 out1 = tf.nn.l2_normalize(input_tensor, parameters["dim"], epsilon=epsilon) 43 out2 = tf.nn.l2_normalize(input_tensor, parameters["dim"], epsilon=epsilon) 44 out = out1 + out2 45 return [input_tensor], [out] 46 47 def build_inputs(parameters, sess, inputs, outputs): 48 input_values = create_tensor_data( 49 np.float32, parameters["input_shape"], min_value=-4, max_value=10) 50 return [input_values], sess.run( 51 outputs, feed_dict=dict(zip(inputs, [input_values]))) 52 53 make_zip_of_tests(options, test_parameters, build_graph, build_inputs) 54