f32530f0d7
Remove useless and confusing comments Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com> Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
94 lines
4.6 KiB
Python
94 lines
4.6 KiB
Python
# Copyright (C) 2018-2022 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.layer_test_class import check_ir_version
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from common.tf_layer_test_class import CommonTFLayerTest
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from unit_tests.utils.graph import build_graph
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class TestBucketize(CommonTFLayerTest):
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def create_bucketize_net(self, input_shape, input_type, boundaries_size, ir_version,
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use_new_frontend):
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"""
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Tensorflow net: IR net:
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Input => Input Boundaries
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| \ /
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Bucketize Bucketize
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{attrs: boundaries}
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"""
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tf.compat.v1.reset_default_graph()
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with tf.compat.v1.Session() as sess:
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x = tf.compat.v1.placeholder(input_type, input_shape, 'Input')
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constant_value = np.arange(-boundaries_size * 5, boundaries_size * 5, 10,
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dtype=np.float32)
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# TODO: Bucketize is not tested here. Need to re-write the test
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tf.compat.v1.global_variables_initializer()
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tf_net = sess.graph_def
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# create reference IR net
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ref_net = None
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if check_ir_version(10, None, ir_version) and not use_new_frontend:
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nodes_attributes = {
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'input': {'kind': 'op', 'type': 'Parameter'},
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'input_data': {'shape': input_shape, 'kind': 'data'},
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'boundaries_input_data': {'shape': constant_value.shape, 'kind': 'data'},
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'boundaries': {'type': 'Const', 'kind': 'op'},
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'boundaries_data': {'kind': 'data', 'shape': constant_value.shape},
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'bucketize': {'kind': 'op', 'type': 'Bucketize'},
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'bucketize_data': {'shape': input_shape, 'kind': 'data'},
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'result': {'kind': 'op', 'type': 'Result'}
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}
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ref_net = build_graph(nodes_attributes,
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[('input', 'input_data'),
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('input_data', 'bucketize', {'in': 0}),
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('boundaries_input_data', 'boundaries'),
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('boundaries', 'boundaries_data'),
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('boundaries_data', 'bucketize', {'in': 1}),
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('bucketize', 'bucketize_data'),
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('bucketize_data', 'result')
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])
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return tf_net, ref_net
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test_data_float32 = [
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dict(input_shape=[5], input_type=tf.float32, boundaries_size=1),
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dict(input_shape=[5], input_type=tf.float32, boundaries_size=3),
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pytest.param(dict(input_shape=[4, 8], input_type=tf.float32, boundaries_size=5),
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marks=pytest.mark.precommit_tf_fe),
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dict(input_shape=[2, 4, 7], input_type=tf.float32, boundaries_size=10),
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dict(input_shape=[2, 4, 7, 8], input_type=tf.float32, boundaries_size=12),
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dict(input_shape=[2, 4, 7, 8, 10], input_type=tf.float32, boundaries_size=14)]
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@pytest.mark.parametrize("params", test_data_float32)
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@pytest.mark.nightly
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def test_bucketize_float32(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_bucketize_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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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_int32 = [
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dict(input_shape=[5], input_type=tf.int32, boundaries_size=1),
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dict(input_shape=[5], input_type=tf.int32, boundaries_size=3),
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dict(input_shape=[4, 8], input_type=tf.int32, boundaries_size=5),
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dict(input_shape=[2, 4, 7], input_type=tf.int32, boundaries_size=10),
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dict(input_shape=[2, 4, 7, 8], input_type=tf.float32, boundaries_size=12),
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dict(input_shape=[2, 4, 7, 8, 10], input_type=tf.float32, boundaries_size=14)]
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@pytest.mark.parametrize("params", test_data_int32)
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@pytest.mark.nightly
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def test_bucketize_int32(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_bucketize_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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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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