00c7da0f5f
* Revert submodule changes * Fix build on Win * Fix precommit: set correct shapes for broadcasting; disable check with ref for use_new_frontend mode * fix precommit * Fix precommits * Temporary skip new tests on GPU with FP16 * Resolve review comments, trigger CI * Resolve review comments * Resolve review comments
81 lines
3.3 KiB
Python
81 lines
3.3 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import pytest
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from common.tf_layer_test_class import CommonTFLayerTest
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class TestBatchToSpace(CommonTFLayerTest):
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def create_batch_to_space_net(self, in_shape, crops_value, block_shape_value, out_shape, ir_version, use_new_frontend):
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"""
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Tensorflow net IR net
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Input->BatchToSpace => Input->BatchToSpace
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"""
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#
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# Create Tensorflow model
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#
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import tensorflow as tf
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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(tf.float32, in_shape, 'Input')
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crops = tf.constant(crops_value)
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block_shape = tf.constant(block_shape_value)
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tf.batch_to_space_nd(x, block_shape, crops, name='Operation')
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tf.compat.v1.global_variables_initializer()
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tf_net = sess.graph_def
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#
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# Create reference IR net
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# Please, specify 'type': 'Input' for input node
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# Moreover, do not forget to validate ALL layer attributes!!!
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#
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ref_net = None
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return tf_net, ref_net
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test_data_4D = [
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dict(in_shape=[4, 1, 1, 3], block_shape_value=[1], crops_value=[[0, 0]],
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out_shape=[4, 1, 1, 3]),
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dict(in_shape=[4, 1, 1, 3], block_shape_value=[2, 2], crops_value=[[0, 0], [0, 0]],
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out_shape=[1, 2, 2, 3]),
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dict(in_shape=[60, 100, 30, 30], block_shape_value=[3, 2], crops_value=[[1, 5], [4, 1]],
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out_shape=[2, 2, 1, 1]),
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# todo: enable these tests after supporting the general case on CPU
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# dict(in_shape=[4, 1, 1, 1], block_shape_value=[2, 1, 2], crops_value=[[0, 0], [0, 0], [0, 0]],
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# out_shape=[]),
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# dict(in_shape=[12, 1, 1, 3], block_shape_value=[3, 2, 2], crops_value=[[1, 0], [0, 1], [1, 1]],
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# out_shape=[1, 2, 1, 4]),
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# dict(in_shape=[36, 2, 2, 3], block_shape_value=[2, 3, 3], crops_value=[[1, 0], [0, 0], [2, 2]],
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# out_shape=[2, 3, 6, 5])
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]
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@pytest.mark.parametrize("params", test_data_4D)
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@pytest.mark.nightly
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def test_batch_to_space_4D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend):
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self._test(*self.create_batch_to_space_net(**params, ir_version=ir_version, use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir, use_new_frontend=use_new_frontend)
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test_data_5D = [
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dict(in_shape=[72, 2, 1, 4, 2], block_shape_value=[3, 4, 2], crops_value=[[1, 2], [0, 0], [3, 0]],
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out_shape=[3, 3, 4, 5, 2]),
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# todo: enable these tests after supporting the general case on CPU
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# dict(in_shape=[144, 2, 1, 4, 1], block_shape_value=[3, 4, 2, 2],
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# crops_value=[[1, 2], [0, 0], [3, 0], [0, 0]], out_shape=[3, 3, 4, 5, 2]),
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]
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@pytest.mark.parametrize("params", test_data_5D)
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@pytest.mark.nightly
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def test_batch_to_space_5D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend):
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self._test(*self.create_batch_to_space_net(**params, ir_version=ir_version, use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir, use_new_frontend=use_new_frontend)
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