# Copyright (C) 2018-2023 Intel Corporation # SPDX-License-Identifier: Apache-2.0 import platform import numpy as np import pytest import tensorflow as tf from common.tf_layer_test_class import CommonTFLayerTest class TestXlog1py(CommonTFLayerTest): def _prepare_input(self, inputs_info): assert 'x' in inputs_info assert 'y' in inputs_info x_shape = inputs_info['x'] y_shape = inputs_info['y'] inputs_data = {} # x = [-3 ,3] y = [1, 2] # generate x in way to have zeros inputs_data['x'] = (6 * np.random.random(size=x_shape).astype(np.float32) - 3) * \ np.random.randint(2, size=x_shape).astype(np.float32) inputs_data['y'] = np.random.random(size=y_shape).astype(np.float32) + 1 return inputs_data def create_xlog1py_net(self, input_shape, input_type): self.input_type = input_type tf.compat.v1.reset_default_graph() # Create the graph and model with tf.compat.v1.Session() as sess: x = tf.compat.v1.placeholder(input_type, input_shape, 'x') y = tf.compat.v1.placeholder(input_type, input_shape, 'y') tf.raw_ops.Xlog1py(x=x, y=y) tf.compat.v1.global_variables_initializer() tf_net = sess.graph_def return tf_net, None test_data_basic = [ dict(input_shape=[10, 20], input_type=np.float32), dict(input_shape=[2, 3, 4], input_type=np.float32), ] @pytest.mark.parametrize("params", test_data_basic) @pytest.mark.precommit_tf_fe @pytest.mark.nightly @pytest.mark.xfail(condition=platform.system() == 'Darwin' and platform.machine() == 'arm64', reason='Ticket - 122716') def test_xlog1py_basic(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend, use_old_api): self._test(*self.create_xlog1py_net(**params), ie_device, precision, ir_version, temp_dir=temp_dir, use_new_frontend=use_new_frontend, use_old_api=use_old_api)