73 lines
3.5 KiB
Python
73 lines
3.5 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 TestDynamicPartition(CommonTFLayerTest):
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def _prepare_input(self, inputs_info):
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assert 'data' in inputs_info, "Test error: inputs_info must contain `data`"
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assert 'partitions' in inputs_info, "Test error: inputs_info must contain `partitions`"
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data_shape = inputs_info['data']
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partitions_shape = inputs_info['partitions']
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inputs_data = {}
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inputs_data['data'] = np.random.randint(-50, 50, data_shape)
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# segment_ids data must be sorted according to TensorFlow SegmentSum specification
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inputs_data['partitions'] = np.random.randint(0, 5, partitions_shape)
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return inputs_data
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def create_dynamic_partition_net(self, data_shape, partitions_shape, num_partitions, data_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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data = tf.compat.v1.placeholder(data_type, data_shape, 'data')
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partitions = tf.compat.v1.placeholder(tf.int32, partitions_shape, 'partitions')
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dynamic_partition = tf.raw_ops.DynamicPartition(data=data, partitions=partitions,
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num_partitions=num_partitions)
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for ind in range(num_partitions):
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tf.identity(dynamic_partition[ind], name='dynamic_partition_{}'.format(ind))
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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(data_shape=[6], partitions_shape=[6], num_partitions=10, data_type=tf.float32),
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dict(data_shape=[4, 3], partitions_shape=[4], num_partitions=8, data_type=tf.float32),
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dict(data_shape=[3, 4, 2], partitions_shape=[3], num_partitions=5, data_type=tf.float32),
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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_dynamic_partition_basic(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, use_old_api):
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if ie_device == 'GPU':
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pytest.xfail('104855')
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if not use_new_frontend:
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pytest.skip("DynamicPartition operation is not supported via legacy frontend.")
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self._test(*self.create_dynamic_partition_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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test_data_other_types = [
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dict(data_shape=[10], partitions_shape=[10], num_partitions=10, data_type=tf.int32),
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dict(data_shape=[7, 3], partitions_shape=[7], num_partitions=8, data_type=tf.int64),
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]
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@pytest.mark.parametrize("params", test_data_other_types)
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@pytest.mark.nightly
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def test_dynamic_partition_other_types(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, use_old_api):
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if ie_device == 'GPU':
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pytest.xfail('104855')
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if not use_new_frontend:
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pytest.skip("DynamicPartition operation is not supported via legacy frontend.")
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self._test(*self.create_dynamic_partition_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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