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.""" 16import tensorflow.compat.v1 as tf 17from tensorflow.lite.testing.zip_test_utils import create_tensor_data 18from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests 19from tensorflow.lite.testing.zip_test_utils import register_make_test_function 20 21 22@register_make_test_function() 23def make_less_equal_tests(options): 24 """Make a set of tests to do less_equal.""" 25 26 test_parameters = [{ 27 "input_dtype": [tf.float32, tf.int32, tf.int64], 28 "input_shape_pair": [([1, 1, 1, 3], [1, 1, 1, 3]), 29 ([2, 3, 4, 5], [2, 3, 4, 5]), ([2, 3, 3], [2, 3]), 30 ([5, 5], [1]), ([10], [2, 4, 10])], 31 "fully_quantize": [False], 32 }, { 33 "input_dtype": [tf.float32], 34 "input_shape_pair": [([1, 1, 1, 3], [1, 1, 1, 3]), ([2, 3, 3], [2, 3])], 35 "fully_quantize": [True], 36 }] 37 38 # High dimension broadcasting support in MLIR converter. 39 # Note(b/204360746): XNNPack delegate don't support high dimension. 40 if not options.skip_high_dimension_inputs: 41 test_parameters = test_parameters + [ 42 { 43 "input_dtype": [tf.float32, tf.int32], 44 "input_shape_pair": [([6, 5, 4, 3, 2, 1], [4, 3, 2, 1]), 45 ([6, 5, 4, 3, 2, 1], [None, 3, 2, 1]), 46 ([6, 5, None, 3, 2, 1], [None, 3, 2, 1])], 47 "fully_quantize": [False], 48 "dynamic_size_value": [4, 1], 49 }, 50 ] 51 52 def populate_dynamic_shape(parameters, input_shape): 53 return [ 54 parameters["dynamic_size_value"] if x is None else x 55 for x in input_shape 56 ] 57 58 def build_graph(parameters): 59 """Build the less_equal op testing graph.""" 60 input_value1 = tf.compat.v1.placeholder( 61 dtype=parameters["input_dtype"], 62 name="input1", 63 shape=parameters["input_shape_pair"][0]) 64 input_value2 = tf.compat.v1.placeholder( 65 dtype=parameters["input_dtype"], 66 name="input2", 67 shape=parameters["input_shape_pair"][1]) 68 out = tf.less_equal(input_value1, input_value2) 69 return [input_value1, input_value2], [out] 70 71 def build_inputs(parameters, sess, inputs, outputs): 72 input_shape_1 = populate_dynamic_shape(parameters, 73 parameters["input_shape_pair"][0]) 74 input_shape_2 = populate_dynamic_shape(parameters, 75 parameters["input_shape_pair"][1]) 76 77 input_value1 = create_tensor_data(parameters["input_dtype"], input_shape_1) 78 input_value2 = create_tensor_data(parameters["input_dtype"], input_shape_2) 79 return [input_value1, input_value2], sess.run( 80 outputs, feed_dict=dict(zip(inputs, [input_value1, input_value2]))) 81 82 make_zip_of_tests( 83 options, 84 test_parameters, 85 build_graph, 86 build_inputs, 87 expected_tf_failures=4) 88