# Copyright (c) 2021  PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import paddle
from onnxbase import APIOnnx
from onnxbase import randtool


class Net(paddle.nn.Layer):
    """
    simple Net
    """

    def __init__(self):
        super(Net, self).__init__()

    def forward(self, inputs):
        """
        forward
        """
        x = paddle.split(inputs, num_or_sections=2, axis=1)
        return x


# def test_split_9():
#     """
#     api: paddle.split
#     op version: 9
#     """
#     op = Net()
#     op.eval()
#     # net, name, ver_list, delta=1e-6, rtol=1e-5
#     obj = APIOnnx(op, 'split', [9])
#     obj.set_input_data("input_data",
#                        paddle.to_tensor(
#                            randtool("float", -1, 1, [3, 10]).astype('float32')))
#     obj.run()
#
#
# def test_split_10():
#     """
#     api: paddle.split
#     op version: 10
#     """
#     op = Net()
#     op.eval()
#     # net, name, ver_list, delta=1e-6, rtol=1e-5
#     obj = APIOnnx(op, 'split', [10])
#     obj.set_input_data("input_data",
#                        paddle.to_tensor(
#                            randtool("float", -1, 1, [3, 10]).astype('float32')))
#     obj.run()
#
#
# def test_split_11():
#     """
#     api: paddle.split
#     op version: 11
#     """
#     op = Net()
#     op.eval()
#     # net, name, ver_list, delta=1e-6, rtol=1e-5
#     obj = APIOnnx(op, 'split', [11])
#     obj.set_input_data("input_data",
#                        paddle.to_tensor(
#                            randtool("float", -1, 1, [3, 10]).astype('float32')))
#     obj.run()
#
#
# def test_split_12():
#     """
#     api: paddle.split
#     op version: 12
#     """
#     op = Net()
#     op.eval()
#     # net, name, ver_list, delta=1e-6, rtol=1e-5
#     obj = APIOnnx(op, 'split', [12])
#     obj.set_input_data("input_data",
#                        paddle.to_tensor(
#                            randtool("float", -1, 1, [3, 10]).astype('float32')))
#     obj.run()
