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 dynamic_rnn.""" 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 24from tensorflow.python.framework import test_util 25from tensorflow.python.ops import rnn 26 27 28@register_make_test_function("make_dynamic_rnn_tests") 29@test_util.enable_control_flow_v2 30def make_dynamic_rnn_tests(options): 31 """Make a set of tests to do basic Lstm cell.""" 32 33 test_parameters = [ 34 { 35 "dtype": [tf.float32], 36 "num_batches": [4, 2], 37 "time_step_size": [4, 3], 38 "input_vec_size": [3, 2], 39 "num_cells": [4, 2], 40 }, 41 ] 42 43 def build_graph(parameters): 44 """Build a simple graph with BasicLSTMCell.""" 45 num_batches = parameters["num_batches"] 46 time_step_size = parameters["time_step_size"] 47 input_vec_size = parameters["input_vec_size"] 48 num_cells = parameters["num_cells"] 49 input_shape = (num_batches, time_step_size, input_vec_size) 50 51 input_tensor = tf.placeholder(dtype=parameters["dtype"], shape=input_shape) 52 lstm_cell = tf.nn.rnn_cell.BasicLSTMCell(num_cells, activation=tf.nn.relu) 53 54 output, _ = rnn.dynamic_rnn( 55 lstm_cell, input_tensor, dtype=parameters["dtype"]) 56 return [input_tensor], [output] 57 58 def build_inputs(parameters, sess, inputs, outputs): 59 """Feed inputs, assign variables, and freeze graph.""" 60 sess.run(tf.global_variables_initializer()) 61 62 num_batches = parameters["num_batches"] 63 time_step_size = parameters["time_step_size"] 64 input_vec_size = parameters["input_vec_size"] 65 input_shape = (num_batches, time_step_size, input_vec_size) 66 input_value = create_tensor_data(parameters["dtype"], input_shape) 67 68 output_values = sess.run( 69 outputs, feed_dict=dict(zip(inputs, [input_value]))) 70 return [input_value], output_values 71 72 make_zip_of_tests( 73 options, 74 test_parameters, 75 build_graph, 76 build_inputs, 77 use_frozen_graph=True) 78