# 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
import paddle
import paddle.fluid as fluid
from op_test import OpTest


# Correct: General.
class TestUnsqueezeOp(OpTest):
    def setUp(self):
        self.init_test_case()
        self.op_type = "unsqueeze"
        self.inputs = {"X": np.random.random(self.ori_shape).astype("float64")}
        self.init_attrs()
        self.outputs = {"Out": self.inputs["X"].reshape(self.new_shape)}

    def test_check_output(self):
        self.check_output()

    def test_check_grad(self):
        self.check_grad(["X"], "Out")

    def init_test_case(self):
        self.ori_shape = (3, 40)
        self.axes = (1, 2)
        self.new_shape = (3, 1, 1, 40)

    def init_attrs(self):
        self.attrs = {"axes": self.axes}


# Correct: Single input index.
class TestUnsqueezeOp1(TestUnsqueezeOp):
    def init_test_case(self):
        self.ori_shape = (20, 5)
        self.axes = (-1, )
        self.new_shape = (20, 5, 1)


# Correct: Mixed input axis.
class TestUnsqueezeOp2(TestUnsqueezeOp):
    def init_test_case(self):
        self.ori_shape = (20, 5)
        self.axes = (0, -1)
        self.new_shape = (1, 20, 5, 1)


# Correct: There is duplicated axis.
class TestUnsqueezeOp3(TestUnsqueezeOp):
    def init_test_case(self):
        self.ori_shape = (10, 2, 5)
        self.axes = (0, 3, 3)
        self.new_shape = (1, 10, 2, 1, 1, 5)


# Correct: Reversed axes.
class TestUnsqueezeOp4(TestUnsqueezeOp):
    def init_test_case(self):
        self.ori_shape = (10, 2, 5)
        self.axes = (3, 1, 1)
        self.new_shape = (10, 1, 1, 2, 5, 1)


class API_TestUnsqueeze(unittest.TestCase):
    def test_out(self):
        with fluid.program_guard(fluid.Program(), fluid.Program()):
            data1 = fluid.layers.data('data1', shape=[-1, 10], dtype='float64')
            result_squeeze = fluid.layers.unsqueeze(data1, axes=[1])
            place = fluid.CPUPlace()
            exe = fluid.Executor(place)
            input1 = np.random.random([5, 1, 10]).astype('float64')
            input = np.squeeze(input1, axis=1)
            result, = exe.run(feed={"data1": input},
                              fetch_list=[result_squeeze])
            self.assertTrue(np.allclose(input1, result))


class TestUnsqueezeOpError(unittest.TestCase):
    def test_errors(self):
        with fluid.program_guard(fluid.Program(), fluid.Program()):
            # The type of axis in split_op should be int or Variable.
            def test_axes_type():
                x6 = fluid.layers.data(
                    shape=[-1, 10], dtype='float16', name='x3')
                fluid.layers.unsqueeze(x6, axes=3.2)

            self.assertRaises(TypeError, test_axes_type)


class API_TestUnsqueeze2(unittest.TestCase):
    def test_out(self):
        with fluid.program_guard(fluid.Program(), fluid.Program()):
            data1 = fluid.data('data1', shape=[-1, 10], dtype='float64')
            data2 = fluid.data('data2', shape=[1], dtype='int32')
            result_squeeze = fluid.layers.unsqueeze(data1, axes=data2)
            place = fluid.CPUPlace()
            exe = fluid.Executor(place)
            input1 = np.random.random([5, 1, 10]).astype('float64')
            input2 = np.array([1]).astype('int32')
            input = np.squeeze(input1, axis=1)
            result1, = exe.run(feed={"data1": input,
                                     "data2": input2},
                               fetch_list=[result_squeeze])
            self.assertTrue(np.allclose(input1, result1))


class API_TestUnsqueeze3(unittest.TestCase):
    def test_out(self):
        with fluid.program_guard(fluid.Program(), fluid.Program()):
            data1 = fluid.data('data1', shape=[-1, 10], dtype='float64')
            data2 = fluid.data('data2', shape=[1], dtype='int32')
            result_squeeze = fluid.layers.unsqueeze(data1, axes=[data2, 3])
            place = fluid.CPUPlace()
            exe = fluid.Executor(place)
            input1 = np.random.random([5, 1, 10, 1]).astype('float64')
            input2 = np.array([1]).astype('int32')
            input = np.squeeze(input1)
            result1, = exe.run(feed={"data1": input,
                                     "data2": input2},
                               fetch_list=[result_squeeze])
            self.assertTrue(np.allclose(input1, result1))


class API_TestDyUnsqueeze(unittest.TestCase):
    def test_out(self):
        with fluid.dygraph.guard():
            input_1 = np.random.random([5, 1, 10]).astype("int32")
            input1 = np.squeeze(input_1, axis=1)
            input = fluid.dygraph.to_variable(input_1)
            output = fluid.layers.unsqueeze(input, axes=[1])
            out_np = output.numpy()
            self.assertTrue(np.allclose(input1, out_np))


class API_TestDyUnsqueeze2(unittest.TestCase):
    def test_out(self):
        with fluid.dygraph.guard():
            input_1 = np.random.random([5, 1, 10]).astype("int32")
            input1 = np.squeeze(input_1, axis=1)
            input = fluid.dygraph.to_variable(input_1)
            output = fluid.layers.unsqueeze(input, axes=1)
            out_np = output.numpy()
            self.assertTrue(np.allclose(input1, out_np))


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