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 leaky_relu.""" 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_leaky_relu_tests(options): 29 """Make a set of tests to do LeakyRelu.""" 30 31 test_parameters = [{ 32 "input_shape": [[], [1], [5], [1, 10, 10, 3], [3, 3, 3, 3]], 33 "alpha": [0.1, 1.0, 2.0, -0.1, -1.0, -2.0], 34 "fully_quantize": [False, True], 35 "input_range": [(-3, 10)], 36 "quant_16x8": [False, True], 37 }] 38 39 def build_graph(parameters): 40 """Build the graph for the test case.""" 41 42 input_tensor = tf.compat.v1.placeholder( 43 dtype=tf.float32, name="input", shape=parameters["input_shape"]) 44 out = tf.nn.leaky_relu(input_tensor, alpha=parameters["alpha"]) 45 return [input_tensor], [out] 46 47 def build_inputs(parameters, sess, inputs, outputs): 48 """Build the inputs for the test case.""" 49 input_values = create_tensor_data( 50 np.float32, parameters["input_shape"], min_value=-3, max_value=10) 51 return [input_values], sess.run( 52 outputs, feed_dict=dict(zip(inputs, [input_values]))) 53 54 make_zip_of_tests(options, test_parameters, build_graph, build_inputs) 55