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test_tf_AdjustHue.py
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# Copyright (C) 2018-2025 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
rng = np.random.default_rng(2323534)
class TestAdjustHue(CommonTFLayerTest):
def _prepare_input(self, inputs_info):
assert 'images:0' in inputs_info
if self.special_case == 'Black Image':
images_shape = inputs_info['images:0']
inputs_data = {}
inputs_data['images:0'] = np.zeros(images_shape).astype(self.input_type)
elif self.special_case == 'Grayscale Image':
images_shape = inputs_info['images:0']
inputs_data = {}
inputs_data['images:0'] = np.ones(images_shape).astype(self.input_type) * np.random.rand()
else:
images_shape = inputs_info['images:0']
inputs_data = {}
inputs_data['images:0'] = rng.uniform(0, 1.0, images_shape).astype(self.input_type)
inputs_data['delta:0'] = rng.uniform(0, 1.0, []).astype(np.float32)
return inputs_data
def create_adjust_hue_net(self, input_shape, input_type, special_case):
self.special_case = special_case
self.input_type = input_type
tf.compat.v1.reset_default_graph()
# Create the graph and model
with tf.compat.v1.Session() as sess:
images = tf.compat.v1.placeholder(input_type, input_shape, 'images')
delta = tf.compat.v1.placeholder(np.float32, [], 'delta')
tf.raw_ops.AdjustHue(images=images, delta=delta)
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
return tf_net, None
@pytest.mark.parametrize('input_shape', [[2, 5, 3], [2, 4, 4, 3], [3, 4, 12, 12, 3]])
@pytest.mark.parametrize('input_type', [np.float32])
@pytest.mark.parametrize('special_case', [None, 'Black Image', 'Grayscale Image'])
@pytest.mark.precommit
@pytest.mark.nightly
def test_adjust_hue_basic(self, input_shape, input_type, special_case,
ie_device, precision, ir_version, temp_dir,
use_legacy_frontend):
self._test(*self.create_adjust_hue_net(input_shape, input_type, special_case),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)