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test_tf_Range.py
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# Copyright (C) 2018-2023 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 TestRange(CommonTFLayerTest):
def _prepare_input(self, inputs_info):
inputs_data = {}
if self.negative_delta:
inputs_data['start'] = np.random.randint(1, 10, []).astype(self.input_type)
inputs_data['limit'] = np.random.randint(-10, 0, []).astype(self.input_type)
inputs_data['delta'] = np.random.randint(-5, -1, []).astype(self.input_type)
else:
inputs_data['start'] = np.random.randint(1, 10, []).astype(self.input_type)
inputs_data['limit'] = np.random.randint(10, 30, []).astype(self.input_type)
inputs_data['delta'] = np.random.randint(1, 5, []).astype(self.input_type)
return inputs_data
def create_range_net(self, input_type, negative_delta):
self.input_type = input_type
self.negative_delta = negative_delta
types_map = {
np.float32: tf.float32,
np.int32: tf.int32
}
assert input_type in types_map, "Incorrect test case"
tf_type = types_map[input_type]
tf.compat.v1.reset_default_graph()
# Create the graph and model
with tf.compat.v1.Session() as sess:
start = tf.compat.v1.placeholder(tf_type, [], 'start')
limit = tf.compat.v1.placeholder(tf_type, [], 'limit')
delta = tf.compat.v1.placeholder(tf_type, [], 'delta')
tf.raw_ops.Range(start=start, limit=limit, delta=delta)
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
return tf_net, None
test_data_basic = [
dict(input_type=np.float32, negative_delta=False),
dict(input_type=np.int32, negative_delta=True),
]
@pytest.mark.parametrize("params", test_data_basic)
@pytest.mark.precommit_tf_fe
@pytest.mark.nightly
def test_range_basic(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_range_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)