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 shape.""" 16import numpy as np 17import tensorflow.compat.v1 as tf 18from tensorflow.lite.testing.zip_test_utils import create_tensor_data 19from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests 20from tensorflow.lite.testing.zip_test_utils import register_make_test_function 21 22 23@register_make_test_function() 24def make_shape_tests(options): 25 """Make a set of tests to do shape.""" 26 27 test_parameters = [{ 28 "input_dtype": [tf.float32, tf.int32], 29 "input_shape": [[1, 4]], 30 "new_shape": [[1, 4], [4, 1], [2, 2]], 31 "out_type": [tf.int32, tf.int64], 32 }] 33 34 def build_graph(parameters): 35 """Build the shape op testing graph.""" 36 # Note that we intentionally leave out the shape from the input placeholder 37 # to prevent the Shape operation from being optimized out during conversion. 38 # TODO(haoliang): Test shape op directly after we have better support for 39 # dynamic input. Currently we need to introduce a Reshape op to prevent 40 # shape being constant-folded. 41 input_value = tf.compat.v1.placeholder( 42 dtype=parameters["input_dtype"], 43 shape=parameters["input_shape"], 44 name="input") 45 shape_of_new_shape = [len(parameters["new_shape"])] 46 new_shape = tf.compat.v1.placeholder( 47 dtype=tf.int32, shape=shape_of_new_shape, name="new_shape") 48 reshaped = tf.reshape(input_value, shape=new_shape) 49 out = tf.shape(reshaped, out_type=parameters["out_type"]) 50 return [input_value, new_shape], [out] 51 52 def build_inputs(parameters, sess, inputs, outputs): 53 input_value = create_tensor_data(parameters["input_dtype"], 54 parameters["input_shape"]) 55 new_shape = np.array(parameters["new_shape"]) 56 return [input_value, new_shape], sess.run( 57 outputs, feed_dict=dict(zip(inputs, [input_value, new_shape]))) 58 59 make_zip_of_tests(options, test_parameters, build_graph, build_inputs) 60