# Copyright (C) 2018-2022 Intel Corporation # SPDX-License-Identifier: Apache-2.0 import numpy as np import pytest import tensorflow as tf from common.tf_layer_test_class import CommonTFLayerTest class TestSelect(CommonTFLayerTest): def _prepare_input(self, inputs_info): assert 'cond' in inputs_info, "Test error: inputs_info must contain `cond`" assert 'x' in inputs_info, "Test error: inputs_info must contain `x`" assert 'y' in inputs_info, "Test error: inputs_info must contain `y`" cond_shape = inputs_info['cond'] x_shape = inputs_info['x'] y_shape = inputs_info['y'] inputs_data = {} inputs_data['cond'] = np.random.randint(0, 2, cond_shape).astype(bool) inputs_data['x'] = np.random.randint(-100, 100, x_shape).astype(np.float32) inputs_data['y'] = np.random.randint(-100, 100, y_shape).astype(np.float32) return inputs_data def create_select_net(self, cond_shape, x_shape, y_shape): tf.compat.v1.reset_default_graph() # Create the graph and model with tf.compat.v1.Session() as sess: cond = tf.compat.v1.placeholder(tf.bool, cond_shape, 'cond') x = tf.compat.v1.placeholder(tf.float32, x_shape, 'x') y = tf.compat.v1.placeholder(tf.float32, y_shape, 'y') tf.raw_ops.Select(condition=cond, x=x, y=y, name='select') tf.compat.v1.global_variables_initializer() tf_net = sess.graph_def return tf_net, None test_data_basic = [ dict(cond_shape=[], x_shape=[3, 2, 4], y_shape=[3, 2, 4]), dict(cond_shape=[2], x_shape=[2, 4, 5], y_shape=[2, 4, 5]), dict(cond_shape=[2, 3, 4], x_shape=[2, 3, 4], y_shape=[2, 3, 4]), ] @pytest.mark.parametrize("params", test_data_basic) @pytest.mark.precommit_tf_fe @pytest.mark.nightly def test_select_basic(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend, use_old_api): if not use_new_frontend: pytest.skip("Select tests are not passing for the legacy frontend.") self._test(*self.create_select_net(**params), ie_device, precision, ir_version, temp_dir=temp_dir, use_new_frontend=use_new_frontend, use_old_api=use_old_api)