#   Copyright (c) 2018 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 unittest

import numpy as np
from get_test_cover_info import (
    XPUOpTestWrapper,
    create_test_class,
    get_xpu_op_support_types,
)
from op_test_xpu import XPUOpTest

import paddle
from paddle.fluid import core
from paddle.fluid.tests.unittests.op import Operator

paddle.enable_static()


class XPUTestShapeOp(XPUOpTestWrapper):
    def __init__(self):
        self.op_name = "shape"
        self.use_dynamic_create_class = False

    class TestShapeOp(XPUOpTest):
        def setUp(self):
            self.dtype = self.in_type
            self.op_type = "shape"
            self.config()
            input = np.zeros(self.shape)
            self.inputs = {'Input': input.astype(self.dtype)}
            self.outputs = {'Out': np.array(self.shape)}

        def config(self):
            self.shape = [2, 3]

        def test_check_output(self):
            if paddle.is_compiled_with_xpu():
                place = paddle.XPUPlace(0)
                self.check_output_with_place(place)

    class TestShapeOp1(TestShapeOp):
        def config(self):
            self.shape = [2]

    class TestShapeOp2(TestShapeOp):
        def config(self):
            self.shape = [1, 2, 3]

    class TestShapeOp3(TestShapeOp):
        def config(self):
            self.shape = [1, 2, 3, 4]

    class TestShapeOp4(TestShapeOp):
        def config(self):
            self.shape = [1, 2, 3, 4, 1024]

    class TestShapeOp5(TestShapeOp):
        def config(self):
            self.shape = [1, 2, 3, 4, 1, 201]

    class TestShapeWithSelectedRows(unittest.TestCase):
        def setUp(self):
            self.dtype = self.in_type

        def get_places(self):
            return [core.CPUPlace(), core.XPUPlace(0)]

        def check_with_place(self, place):
            scope = core.Scope()
            x_rows = [0, 1, 5, 4, 19]
            height = 20
            row_numel = 2

            np_array = np.ones((len(x_rows), row_numel)).astype(self.dtype)

            # initialize input variable X
            x = scope.var('X').get_selected_rows()
            x.set_rows(x_rows)
            x.set_height(height)
            x_tensor = x.get_tensor()
            x_tensor.set(np_array, place)
            out_shape = scope.var("Out").get_tensor()
            op = Operator("shape", Input="X", Out="Out")

            op.run(scope, place)

            out_shape = np.array(out_shape).tolist()
            self.assertListEqual([5, 2], out_shape)

        def test_check_output(self):
            for place in self.get_places():
                if (
                    type(place) is paddle.fluid.libpaddle.CPUPlace
                    and self.dtype == np.float16
                ):
                    # fp16 not available on cpu
                    pass
                else:
                    self.check_with_place(place)


support_types = get_xpu_op_support_types("shape")
for stype in support_types:
    create_test_class(globals(), XPUTestShapeOp, stype)

if __name__ == '__main__':
    unittest.main()
