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 depth_to_space.""" 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_depth_to_space_tests(options): 24 """Make a set of tests to do depth_to_space.""" 25 26 test_parameters = [{ 27 "dtype": [tf.int32, tf.uint8, tf.int64], 28 "input_shape": [[2, 3, 4, 16]], 29 "block_size": [2, 4], 30 "fully_quantize": [False], 31 }, { 32 "dtype": [tf.float32], 33 "input_shape": [[2, 3, 4, 16]], 34 "block_size": [2, 4], 35 "fully_quantize": [True, False], 36 }] 37 38 def build_graph(parameters): 39 input_tensor = tf.compat.v1.placeholder( 40 dtype=parameters["dtype"], 41 name="input", 42 shape=parameters["input_shape"]) 43 out = tf.compat.v1.depth_to_space( 44 input_tensor, block_size=parameters["block_size"]) 45 return [input_tensor], [out] 46 47 def build_inputs(parameters, sess, inputs, outputs): 48 if not parameters["fully_quantize"]: 49 input_values = create_tensor_data(parameters["dtype"], 50 parameters["input_shape"]) 51 else: 52 input_values = create_tensor_data( 53 parameters["dtype"], 54 parameters["input_shape"], 55 min_value=-1, 56 max_value=1) 57 return [input_values], sess.run( 58 outputs, feed_dict=dict(zip(inputs, [input_values]))) 59 60 make_zip_of_tests(options, test_parameters, build_graph, build_inputs) 61