48 lines
1.9 KiB
Python
48 lines
1.9 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import pytest
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import tensorflow as tf
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from common.tf_layer_test_class import CommonTFLayerTest
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class TestCheckNumerics(CommonTFLayerTest):
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def _prepare_input(self, inputs_info):
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assert 'x' in inputs_info
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x_shape = inputs_info['x']
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assert 'y' in inputs_info
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y_shape = inputs_info['y']
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inputs_data = {}
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inputs_data['x'] = np.random.randint(-10, 10, x_shape).astype(self.input_type)
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inputs_data['y'] = np.random.randint(-10, 10, y_shape).astype(self.input_type)
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return inputs_data
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def create_check_numerics_net(self, input_shape, input_type, op):
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self.input_type = input_type
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tf.compat.v1.reset_default_graph()
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# Create the graph and model
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with tf.compat.v1.Session() as sess:
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x = tf.compat.v1.placeholder(input_type, input_shape, 'x')
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y = tf.compat.v1.placeholder(input_type, input_shape, 'y')
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z = tf.raw_ops.AddV2(x=x, y=y)
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op(tensor=z, message="z is invalid")
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tf.compat.v1.global_variables_initializer()
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tf_net = sess.graph_def
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return tf_net, None
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test_data_basic = [
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dict(input_shape=[2, 6], input_type=np.float32, op=tf.raw_ops.CheckNumerics),
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dict(input_shape=[3, 4, 5], input_type=np.float32, op=tf.raw_ops.CheckNumericsV2),
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]
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@pytest.mark.parametrize("params", test_data_basic)
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@pytest.mark.precommit_tf_fe
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@pytest.mark.nightly
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def test_check_numerics_basic(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, use_old_api):
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self._test(*self.create_check_numerics_net(**params),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, use_old_api=use_old_api)
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