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 less_equal.""" 16from __future__ import absolute_import 17from __future__ import division 18from __future__ import print_function 19 20import tensorflow.compat.v1 as tf 21from tensorflow.lite.testing.zip_test_utils import create_tensor_data 22from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests 23from tensorflow.lite.testing.zip_test_utils import register_make_test_function 24 25 26@register_make_test_function() 27def make_less_equal_tests(options): 28 """Make a set of tests to do less_equal.""" 29 30 test_parameters = [{ 31 "input_dtype": [tf.float32, tf.int32, tf.int64], 32 "input_shape_pair": [([1, 1, 1, 3], [1, 1, 1, 3]), 33 ([2, 3, 4, 5], [2, 3, 4, 5]), ([2, 3, 3], [2, 3]), 34 ([5, 5], [1]), ([10], [2, 4, 10])], 35 "fully_quantize": [False], 36 }, { 37 "input_dtype": [tf.float32], 38 "input_shape_pair": [([1, 1, 1, 3], [1, 1, 1, 3]), ([2, 3, 3], [2, 3])], 39 "fully_quantize": [True], 40 }] 41 42 # High dimension broadcasting support in MLIR converter. 43 if options.use_experimental_converter: 44 test_parameters = test_parameters + [ 45 { 46 "input_dtype": [tf.float32, tf.int32], 47 "input_shape_pair": [([6, 5, 4, 3, 2, 1], [4, 3, 2, 1]), 48 ([6, 5, 4, 3, 2, 1], [None, 3, 2, 1]), 49 ([6, 5, None, 3, 2, 1], [None, 3, 2, 1])], 50 "fully_quantize": [False], 51 "dynamic_size_value": [4, 1], 52 }, 53 ] 54 55 def populate_dynamic_shape(parameters, input_shape): 56 return [ 57 parameters["dynamic_size_value"] if x is None else x 58 for x in input_shape 59 ] 60 61 def build_graph(parameters): 62 """Build the less_equal op testing graph.""" 63 input_value1 = tf.compat.v1.placeholder( 64 dtype=parameters["input_dtype"], 65 name="input1", 66 shape=parameters["input_shape_pair"][0]) 67 input_value2 = tf.compat.v1.placeholder( 68 dtype=parameters["input_dtype"], 69 name="input2", 70 shape=parameters["input_shape_pair"][1]) 71 out = tf.less_equal(input_value1, input_value2) 72 return [input_value1, input_value2], [out] 73 74 def build_inputs(parameters, sess, inputs, outputs): 75 input_shape_1 = populate_dynamic_shape(parameters, 76 parameters["input_shape_pair"][0]) 77 input_shape_2 = populate_dynamic_shape(parameters, 78 parameters["input_shape_pair"][1]) 79 80 input_value1 = create_tensor_data(parameters["input_dtype"], input_shape_1) 81 input_value2 = create_tensor_data(parameters["input_dtype"], input_shape_2) 82 return [input_value1, input_value2], sess.run( 83 outputs, feed_dict=dict(zip(inputs, [input_value1, input_value2]))) 84 85 make_zip_of_tests( 86 options, 87 test_parameters, 88 build_graph, 89 build_inputs, 90 expected_tf_failures=4) 91