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test_tf_CheckNumerics.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
OPS = {
"tf.raw_ops.CheckNumerics": tf.raw_ops.CheckNumerics,
"tf.raw_ops.CheckNumericsV2": tf.raw_ops.CheckNumericsV2
}
class TestCheckNumerics(CommonTFLayerTest):
def _prepare_input(self, inputs_info):
assert 'x:0' in inputs_info
x_shape = inputs_info['x:0']
assert 'y:0' in inputs_info
y_shape = inputs_info['y:0']
inputs_data = {}
inputs_data['x:0'] = np.random.randint(-10, 10, x_shape).astype(self.input_type)
inputs_data['y:0'] = np.random.randint(-10, 10, y_shape).astype(self.input_type)
return inputs_data
def create_check_numerics_net(self, input_shape, input_type, op):
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')
z = tf.raw_ops.AddV2(x=x, y=y)
op(tensor=z, message="z is invalid")
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
return tf_net, None
test_data_basic = [
[[2, 6], np.float32, 'tf.raw_ops.CheckNumerics'],
[[3, 4, 5], np.float32, 'tf.raw_ops.CheckNumericsV2'],
]
@pytest.mark.parametrize("input_shape, input_type, op", test_data_basic)
@pytest.mark.precommit
@pytest.mark.nightly
def test_check_numerics_basic(self, input_shape, input_type, op, ie_device, precision, ir_version, temp_dir,
use_legacy_frontend):
params = dict(input_shape=input_shape, input_type=input_type, op=OPS[op])
self._test(*self.create_check_numerics_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_legacy_frontend=use_legacy_frontend)