test_tf_BatchToSpace.py

# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0

import pytest

from common.tf_layer_test_class import CommonTFLayerTest


class TestBatchToSpace(CommonTFLayerTest):
    def create_batch_to_space_net(self, in_shape, crops_value, block_shape_value, out_shape,
                                  ir_version, use_new_frontend):
        """
            Tensorflow net                     IR net

            Input->BatchToSpace        =>      Input->BatchToSpace

        """

        import tensorflow as tf

        tf.compat.v1.reset_default_graph()

        # Create the graph and model
        with tf.compat.v1.Session() as sess:
            x = tf.compat.v1.placeholder(tf.float32, in_shape, 'Input')
            crops = tf.constant(crops_value)
            block_shape = tf.constant(block_shape_value)
            tf.compat.v1.batch_to_space(x, crops, block_shape, name='Operation')
            tf.compat.v1.global_variables_initializer()
            tf_net = sess.graph_def

        #
        #   Create reference IR net
        #   Please, specify 'type': 'Input' for input node
        #   Moreover, do not forget to validate ALL layer attributes!!!
        #

        ref_net = None

        return tf_net, ref_net

    test_data_4D = [
        dict(in_shape=[4, 1, 1, 3], block_shape_value=[1], crops_value=[[0, 0]],
             out_shape=[4, 1, 1, 3]),
        dict(in_shape=[4, 1, 1, 3], block_shape_value=[2, 2], crops_value=[[0, 0], [0, 0]],
             out_shape=[1, 2, 2, 3]),
        dict(in_shape=[60, 100, 30, 30], block_shape_value=[3, 2], crops_value=[[1, 5], [4, 1]],
             out_shape=[2, 2, 1, 1]),
        # todo: enable these tests after supporting the general case on CPU
        # dict(in_shape=[4, 1, 1, 1], block_shape_value=[2, 1, 2], crops_value=[[0, 0], [0, 0], [0, 0]],
        #      out_shape=[]),
        # dict(in_shape=[12, 1, 1, 3], block_shape_value=[3, 2, 2], crops_value=[[1, 0], [0, 1], [1, 1]],
        #      out_shape=[1, 2, 1, 4]),
        # dict(in_shape=[36, 2, 2, 3], block_shape_value=[2, 3, 3], crops_value=[[1, 0], [0, 0], [2, 2]],
        #      out_shape=[2, 3, 6, 5])
    ]

    @pytest.mark.parametrize("params", test_data_4D)
    @pytest.mark.nightly
    def test_batch_to_space_4D(self, params, ie_device, precision, ir_version, temp_dir,
                               use_new_frontend, use_old_api):
        self._test(*self.create_batch_to_space_net(**params, ir_version=ir_version,
                                                   use_new_frontend=use_new_frontend),
                   ie_device, precision, ir_version, temp_dir=temp_dir,
                   use_new_frontend=use_new_frontend, use_old_api=use_old_api)

    test_data_5D = [
        dict(in_shape=[72, 2, 1, 4, 2], block_shape_value=[3, 4, 2],
             crops_value=[[1, 2], [0, 0], [3, 0]],
             out_shape=[3, 3, 4, 5, 2]),
        # todo: enable these tests after supporting the general case on CPU
        # dict(in_shape=[144, 2, 1, 4, 1], block_shape_value=[3, 4, 2, 2],
        #      crops_value=[[1, 2], [0, 0], [3, 0], [0, 0]], out_shape=[3, 3, 4, 5, 2]),
    ]

    @pytest.mark.parametrize("params", test_data_5D)
    @pytest.mark.nightly
    def test_batch_to_space_5D(self, params, ie_device, precision, ir_version, temp_dir,
                               use_new_frontend, use_old_api):
        self._test(*self.create_batch_to_space_net(**params, ir_version=ir_version,
                                                   use_new_frontend=use_new_frontend),
                   ie_device, precision, ir_version, temp_dir=temp_dir,
                   use_new_frontend=use_new_frontend, use_old_api=use_old_api)