#   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.

from __future__ import print_function

import unittest
import numpy as np
from op_test import OpTest
import paddle
from paddle.fluid import core
from paddle.fluid.op import Operator


class TestShapeOp(OpTest):
    def setUp(self):
        self.op_type = "shape"
        self.python_api = paddle.shape
        self.config()
        self.shape = [2, 3]
        input = np.zeros(self.shape)
        self.inputs = {'Input': input}
        self.outputs = {'Out': np.array(self.shape)}

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

    def test_check_output(self):
        self.check_output(check_eager=True)


class case1(TestShapeOp):
    def config(self):
        self.shape = [2]


class case2(TestShapeOp):
    def config(self):
        self.shape = [1, 2, 3]


class TestShapeWithSelectedRows(unittest.TestCase):
    def get_places(self):
        places = [core.CPUPlace()]
        if core.is_compiled_with_cuda():
            places.append(core.CUDAPlace(0))
        return places

    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("float32")

        # 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)

        # initialize input variable Out
        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():
            self.check_with_place(place)


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