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.""" 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_tests(options): 29 """Make a set of tests to do l2norm.""" 30 31 # Chose a set of parameters 32 test_parameters = [{ 33 "input_shape": [[5, 7], [1, 1, 1, 1], [1, 3, 4, 3], [3, 15, 14, 3]], 34 "dim": [0, 1, 2, 3, [2, 3], -2], 35 "epsilon": [None, 1e-12, 1e-3], 36 "fully_quantize": [False], 37 }, { 38 "input_shape": [[1, 1, 1, 1], [1, 3, 4, 3], [3, 15, 14, 3]], 39 "dim": [3], 40 "epsilon": [None, 1e-12], 41 "fully_quantize": [True], 42 }, { # use another group of test so the dim is set to fuse to tfl.l2norm 43 "input_shape": [[5, 7]], 44 "dim": [1], 45 "epsilon": [None, 1e-12], 46 "fully_quantize": [True], 47 }] 48 49 def build_graph(parameters): 50 input_tensor = tf.compat.v1.placeholder( 51 dtype=tf.float32, name="input", shape=parameters["input_shape"]) 52 if parameters["epsilon"]: 53 out = tf.nn.l2_normalize( 54 input_tensor, parameters["dim"], epsilon=parameters["epsilon"]) 55 else: 56 out = tf.nn.l2_normalize(input_tensor, parameters["dim"]) 57 return [input_tensor], [out] 58 59 def build_inputs(parameters, sess, inputs, outputs): 60 input_values = create_tensor_data( 61 np.float32, parameters["input_shape"], min_value=-1, max_value=1) 62 return [input_values], sess.run( 63 outputs, feed_dict=dict(zip(inputs, [input_values]))) 64 65 make_zip_of_tests( 66 options, 67 test_parameters, 68 build_graph, 69 build_inputs, 70 expected_tf_failures=9) 71