#   Copyright (c) 2020 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.

# Test set_value op in static mode

from __future__ import print_function

import unittest
import numpy as np

import paddle


class TestSetValueBase(unittest.TestCase):
    def setUp(self):
        paddle.enable_static()
        self.set_dtype()
        self.set_value()
        self.set_shape()
        self.data = np.ones(self.shape).astype(self.dtype)
        self.program = paddle.static.Program()

    def set_shape(self):
        self.shape = [2, 3, 4]

    def set_value(self):
        self.value = 6

    def set_dtype(self):
        self.dtype = "float32"

    def _call_setitem(self, x):
        x[0, 0] = self.value

    def _get_answer(self):
        self.data[0, 0] = self.value


class TestSetValueApi(TestSetValueBase):
    def _run_static(self):
        paddle.enable_static()
        with paddle.static.program_guard(self.program):
            x = paddle.ones(shape=self.shape, dtype=self.dtype)
            self._call_setitem(x)

        exe = paddle.static.Executor(paddle.CPUPlace())
        out = exe.run(self.program, fetch_list=[x])
        paddle.disable_static()
        return out

    def _run_dynamic(self):
        paddle.disable_static()
        x = paddle.ones(shape=self.shape, dtype=self.dtype)
        self._call_setitem(x)
        out = x.numpy()
        paddle.enable_static()
        return out

    def test_api(self):
        static_out = self._run_static()
        dynamic_out = self._run_dynamic()
        self._get_answer()

        error_msg = "\nIn {} mode: \nExpected res = \n{}, \n\nbut received : \n{}"
        self.assertTrue(
            (self.data == static_out).all(),
            msg=error_msg.format("static", self.data, static_out))
        self.assertTrue(
            (self.data == dynamic_out).all(),
            msg=error_msg.format("dynamic", self.data, dynamic_out))


# 1. Test different type of item: int, Python slice, Paddle Tensor
# 1.1 item is int
class TestSetValueItemInt(TestSetValueApi):
    def _call_setitem(self, x):
        x[0] = self.value

    def _get_answer(self):
        self.data[0] = self.value


# 1.2 item is slice
# 1.2.1 step is 1
class TestSetValueItemSlice(TestSetValueApi):
    def _call_setitem(self, x):
        x[0:2] = self.value

    def _get_answer(self):
        self.data[0:2] = self.value


class TestSetValueItemSlice2(TestSetValueApi):
    def _call_setitem(self, x):
        x[0:-1] = self.value

    def _get_answer(self):
        self.data[0:-1] = self.value


class TestSetValueItemSlice3(TestSetValueApi):
    def _call_setitem(self, x):
        x[0:-1, 0:2] = self.value

    def _get_answer(self):
        self.data[0:-1, 0:2] = self.value


class TestSetValueItemSlice4(TestSetValueApi):
    def _call_setitem(self, x):
        x[0:, 1:2, :] = self.value

    def _get_answer(self):
        self.data[0:, 1:2, :] = self.value


class TestSetValueItemSliceInWhile(TestSetValueApi):
    def _call_setitem(self, x):
        def cond(i, x):
            return i < 1

        def body(i, x):
            x[i] = self.value
            i = i + 1
            return i, x

        i = paddle.zeros(shape=(1, ), dtype='int32')
        i, x = paddle.fluid.layers.while_loop(cond, body, [i, x])

    def _get_answer(self):
        self.data[0] = self.value


# 1.2.2 step > 1
class TestSetValueItemSliceStep(TestSetValueApi):
    def set_shape(self):
        self.shape = [5, 5, 5]

    def _call_setitem(self, x):
        x[0:2:2] = self.value

    def _get_answer(self):
        self.data[0:2:2] = self.value


class TestSetValueItemSliceStep2(TestSetValueApi):
    def set_shape(self):
        self.shape = [7, 5, 5]

    def _call_setitem(self, x):
        x[0:-1:3] = self.value

    def _get_answer(self):
        self.data[0:-1:3] = self.value


class TestSetValueItemSliceStep3(TestSetValueApi):
    def _call_setitem(self, x):
        x[0:-1, 0:2, ::2] = self.value

    def _get_answer(self):
        self.data[0:-1, 0:2, ::2] = self.value


class TestSetValueItemSliceStep4(TestSetValueApi):
    def _call_setitem(self, x):
        x[0:, 1:2:2, :] = self.value

    def _get_answer(self):
        self.data[0:, 1:2:2, :] = self.value


# 1.2.3 step < 0
class TestSetValueItemSliceNegetiveStep(TestSetValueApi):
    def set_shape(self):
        self.shape = [5, 2]

    def set_value(self):
        self.value = np.array([3, 4])

    def _call_setitem(self, x):
        x[5:2:-1] = self.value

    def _get_answer(self):
        self.data[5:2:-1] = self.value


class TestSetValueItemSliceNegetiveStep2(TestSetValueApi):
    def set_shape(self):
        self.shape = [5]

    def set_value(self):
        self.value = np.array([3, 4])

    def _call_setitem(self, x):
        x[1::-1] = self.value

    def _get_answer(self):
        self.data[1::-1] = self.value


class TestSetValueItemSliceNegetiveStep3(TestSetValueApi):
    def set_shape(self):
        self.shape = [3]

    def set_value(self):
        self.value = np.array([3, 4, 5])

    def _call_setitem(self, x):
        x[::-1] = self.value

    def _get_answer(self):
        self.data[::-1] = self.value


class TestSetValueItemSliceNegetiveStep4(TestSetValueApi):
    def set_shape(self):
        self.shape = [3, 4, 5]

    def _call_setitem(self, x):
        x[2:0:-1, 0:2, ::-1] = self.value

    def _get_answer(self):
        self.data[2:0:-1, 0:2, ::-1] = self.value


# 1.3 item is Ellipsis


class TestSetValueItemEllipsis1(TestSetValueApi):
    def _call_setitem(self, x):
        x[0:, ..., 1:] = self.value

    def _get_answer(self):
        self.data[0:, ..., 1:] = self.value


class TestSetValueItemEllipsis2(TestSetValueApi):
    def _call_setitem(self, x):
        x[0:, ...] = self.value

    def _get_answer(self):
        self.data[0:, ...] = self.value


class TestSetValueItemEllipsis3(TestSetValueApi):
    def _call_setitem(self, x):
        x[..., 1:] = self.value

    def _get_answer(self):
        self.data[..., 1:] = self.value


class TestSetValueItemEllipsis4(TestSetValueApi):
    def _call_setitem(self, x):
        x[...] = self.value

    def _get_answer(self):
        self.data[...] = self.value


# 1.4 item is Paddle Tensor
class TestSetValueItemTensor(TestSetValueApi):
    def _call_setitem(self, x):
        zero = paddle.full([1], 0, dtype="int32")
        x[zero] = self.value

    def _get_answer(self):
        self.data[0] = self.value


class TestSetValueItemTensor2(TestSetValueApi):
    def _call_setitem(self, x):
        zero = paddle.full([1], 0, dtype="int32")
        two = paddle.full([1], 2, dtype="int64")
        x[zero:two] = self.value

    def _get_answer(self):
        self.data[0:2] = self.value


class TestSetValueItemTensor3(TestSetValueApi):
    def _call_setitem(self, x):
        zero = paddle.full([1], 0, dtype="int32")
        two = paddle.full([1], 2, dtype="int64")
        x[zero:-1, 0:two] = self.value

    def _get_answer(self):
        self.data[0:-1, 0:2] = self.value


class TestSetValueItemTensor4(TestSetValueApi):
    def _call_setitem(self, x):
        zero = paddle.full([1], 0, dtype="int32")
        two = paddle.full([1], 2, dtype="int64")
        x[0:-1, zero:2, 0:6:two] = self.value

    def _get_answer(self):
        self.data[0:-1, 0:2, ::2] = self.value


class TestSetValueItemTensor5(TestSetValueApi):
    def _call_setitem(self, x):
        zero = paddle.full([1], 0, dtype="int32")
        two = paddle.full([1], 2, dtype="int64")
        x[zero:, 1:2:two, :] = self.value

    def _get_answer(self):
        self.data[0:, 1:2:2, :] = self.value


class TestSetValueItemTensor6(TestSetValueApi):
    def set_shape(self):
        self.shape = [3, 4, 5]

    def _call_setitem(self, x):
        minus1 = paddle.full([1], -1, dtype="int32")
        zero = paddle.full([1], 0, dtype="int32")
        x[2:zero:minus1, 0:2, 10:-6:minus1] = self.value

    def _get_answer(self):
        self.data[2:0:-1, 0:2, ::-1] = self.value


# 2. Test different type of value: int, float, numpy.ndarray, Tensor
# 2.1 value is int32, int64, float32, float64, bool


def create_test_value_int32(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = 7

        def set_dtype(self):
            self.dtype = "int32"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueInt32")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_int32(TestSetValueItemInt)
create_test_value_int32(TestSetValueItemSlice)
create_test_value_int32(TestSetValueItemSlice2)
create_test_value_int32(TestSetValueItemSlice3)
create_test_value_int32(TestSetValueItemSlice4)


def create_test_value_int64(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = 7

        def set_dtype(self):
            self.dtype = "int64"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueInt64")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_int64(TestSetValueItemInt)
create_test_value_int64(TestSetValueItemSlice)
create_test_value_int64(TestSetValueItemSlice2)
create_test_value_int64(TestSetValueItemSlice3)
create_test_value_int64(TestSetValueItemSlice4)


def create_test_value_fp32(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = 3.3

        def set_dtype(self):
            self.dtype = "float32"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueFp32")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_fp32(TestSetValueItemInt)
create_test_value_fp32(TestSetValueItemSlice)
create_test_value_fp32(TestSetValueItemSlice2)
create_test_value_fp32(TestSetValueItemSlice3)
create_test_value_fp32(TestSetValueItemSlice4)


def create_test_value_fp64(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = 2.0**127  # float32:[-2^128, 2^128)

        def set_dtype(self):
            self.dtype = "float64"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueFp64")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_fp64(TestSetValueItemInt)
create_test_value_fp64(TestSetValueItemSlice)
create_test_value_fp64(TestSetValueItemSlice2)
create_test_value_fp64(TestSetValueItemSlice3)
create_test_value_fp64(TestSetValueItemSlice4)


def create_test_value_bool(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = 0

        def set_dtype(self):
            self.dtype = "bool"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueBool")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_bool(TestSetValueItemInt)
create_test_value_bool(TestSetValueItemSlice)
create_test_value_bool(TestSetValueItemSlice2)
create_test_value_bool(TestSetValueItemSlice3)
create_test_value_bool(TestSetValueItemSlice4)


# 2.2 value is numpy.array (int32, int64, float32, float64, bool)
def create_test_value_numpy_int32(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = np.array([5])

        def set_dtype(self):
            self.dtype = "int32"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyInt32")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_numpy_int32(TestSetValueItemInt)
create_test_value_numpy_int32(TestSetValueItemSlice)
create_test_value_numpy_int32(TestSetValueItemSlice2)
create_test_value_numpy_int32(TestSetValueItemSlice3)
create_test_value_numpy_int32(TestSetValueItemSlice4)


def create_test_value_numpy_int64(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = np.array([1])

        def set_dtype(self):
            self.dtype = "int64"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyInt64")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_numpy_int64(TestSetValueItemInt)
create_test_value_numpy_int64(TestSetValueItemSlice)
create_test_value_numpy_int64(TestSetValueItemSlice2)
create_test_value_numpy_int64(TestSetValueItemSlice3)
create_test_value_numpy_int64(TestSetValueItemSlice4)


def create_test_value_numpy_fp32(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = np.array([1])

        def set_dtype(self):
            self.dtype = "float32"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyFp32")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_numpy_fp32(TestSetValueItemInt)
create_test_value_numpy_fp32(TestSetValueItemSlice)
create_test_value_numpy_fp32(TestSetValueItemSlice2)
create_test_value_numpy_fp32(TestSetValueItemSlice3)
create_test_value_numpy_fp32(TestSetValueItemSlice4)


def create_test_value_numpy_fp64(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = np.array([2**127]).astype("float64")

        def set_dtype(self):
            self.dtype = "float64"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyFp64")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_numpy_fp64(TestSetValueItemInt)
create_test_value_numpy_fp64(TestSetValueItemSlice)
create_test_value_numpy_fp64(TestSetValueItemSlice2)
create_test_value_numpy_fp64(TestSetValueItemSlice3)
create_test_value_numpy_fp64(TestSetValueItemSlice4)


def create_test_value_numpy_bool(parent):
    class TestValueInt(parent):
        def set_value(self):
            self.value = np.array([0])

        def set_dtype(self):
            self.dtype = "bool"

    cls_name = "{0}_{1}".format(parent.__name__, "ValueNumpyBool")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_numpy_bool(TestSetValueItemInt)
create_test_value_numpy_bool(TestSetValueItemSlice)
create_test_value_numpy_bool(TestSetValueItemSlice2)
create_test_value_numpy_bool(TestSetValueItemSlice3)
create_test_value_numpy_bool(TestSetValueItemSlice4)


# 2.3 value is a Paddle Tensor (int32, int64, float32, float64, bool)
def create_test_value_tensor_int32(parent):
    class TestValueInt(parent):
        def set_dtype(self):
            self.dtype = "int32"

        def _call_setitem(self, x):
            value = paddle.full(shape=[1], fill_value=3, dtype=self.dtype)
            x[0, 1] = value

        def _get_answer(self):
            self.data[0, 1] = 3

    cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorInt32")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_tensor_int32(TestSetValueItemInt)
create_test_value_tensor_int32(TestSetValueItemSlice)
create_test_value_tensor_int32(TestSetValueItemSlice2)
create_test_value_tensor_int32(TestSetValueItemSlice3)
create_test_value_tensor_int32(TestSetValueItemSlice4)


def create_test_value_tensor_int64(parent):
    class TestValueInt(parent):
        def set_dtype(self):
            self.dtype = "int64"

        def _call_setitem(self, x):
            value = paddle.full(shape=[1], fill_value=3, dtype=self.dtype)
            x[0, 1] = value

        def _get_answer(self):
            self.data[0, 1] = 3

    cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorInt64")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_tensor_int64(TestSetValueItemInt)
create_test_value_tensor_int64(TestSetValueItemSlice)
create_test_value_tensor_int64(TestSetValueItemSlice2)
create_test_value_tensor_int64(TestSetValueItemSlice3)
create_test_value_tensor_int64(TestSetValueItemSlice4)


def create_test_value_tensor_fp32(parent):
    class TestValueInt(parent):
        def set_dtype(self):
            self.dtype = "float32"

        def _call_setitem(self, x):
            value = paddle.full(shape=[1], fill_value=3, dtype=self.dtype)
            x[0, 1] = value

        def _get_answer(self):
            self.data[0, 1] = 3

    cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorFp32")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_tensor_fp32(TestSetValueItemInt)
create_test_value_tensor_fp32(TestSetValueItemSlice)
create_test_value_tensor_fp32(TestSetValueItemSlice2)
create_test_value_tensor_fp32(TestSetValueItemSlice3)
create_test_value_tensor_fp32(TestSetValueItemSlice4)


def create_test_value_tensor_fp64(parent):
    class TestValueInt(parent):
        def set_dtype(self):
            self.dtype = "float64"

        def _call_setitem(self, x):
            value = paddle.full(shape=[1], fill_value=3, dtype=self.dtype)
            x[0, 1] = value

        def _get_answer(self):
            self.data[0, 1] = 3

    cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorFp64")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_tensor_fp64(TestSetValueItemInt)
create_test_value_tensor_fp64(TestSetValueItemSlice)
create_test_value_tensor_fp64(TestSetValueItemSlice2)
create_test_value_tensor_fp64(TestSetValueItemSlice3)
create_test_value_tensor_fp64(TestSetValueItemSlice4)


def create_test_value_tensor_bool(parent):
    class TestValueInt(parent):
        def set_dtype(self):
            self.dtype = "bool"

        def _call_setitem(self, x):
            value = paddle.full(shape=[1], fill_value=False, dtype=self.dtype)
            x[0, 1] = value

        def _get_answer(self):
            self.data[0, 1] = False

    cls_name = "{0}_{1}".format(parent.__name__, "ValueTensorBool")
    TestValueInt.__name__ = cls_name
    globals()[cls_name] = TestValueInt


create_test_value_tensor_bool(TestSetValueItemInt)
create_test_value_tensor_bool(TestSetValueItemSlice)
create_test_value_tensor_bool(TestSetValueItemSlice2)
create_test_value_tensor_bool(TestSetValueItemSlice3)
create_test_value_tensor_bool(TestSetValueItemSlice4)


# 3. Test different shape of value
class TestSetValueValueShape1(TestSetValueApi):
    def set_value(self):
        self.value = np.array([3, 4, 5, 6])  # shape is (4,)

    def _call_setitem(self, x):
        x[0] = self.value

    def _get_answer(self):
        self.data[0] = self.value


class TestSetValueValueShape2(TestSetValueApi):
    def set_value(self):
        self.value = np.array([[3, 4, 5, 6]])  # shape is (1,4)

    def _call_setitem(self, x):
        x[0:1] = self.value

    def _get_answer(self):
        self.data[0:1] = self.value


class TestSetValueValueShape3(TestSetValueApi):
    def set_value(self):
        self.value = np.array(
            [[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]])  # shape is (3,4)

    def _call_setitem(self, x):
        x[0] = self.value

    def _get_answer(self):
        self.data[0] = self.value


class TestSetValueValueShape4(TestSetValueApi):
    def set_value(self):
        self.value = np.array(
            [[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]]).astype(
                self.dtype)  # shape is (3,4)

    def _call_setitem(self, x):
        x[0] = paddle.assign(self.value)  # x is Paddle.Tensor

    def _get_answer(self):
        self.data[0] = self.value


class TestSetValueValueShape5(TestSetValueApi):
    def set_value(self):
        self.value = np.array([3, 3, 3]).astype(self.dtype)

    def set_shape(self):
        self.shape = [3, 4]

    def _call_setitem(self, x):
        x[:, 0] = paddle.assign(self.value)  # x is Paddle.Tensor

    def _get_answer(self):
        self.data[:, 0] = self.value


# 4. Test error
class TestError(TestSetValueBase):
    def _value_type_error(self):
        with self.assertRaisesRegexp(
                TypeError,
                "Only support to assign an integer, float, numpy.ndarray or paddle.Tensor"
        ):
            x = paddle.ones(shape=self.shape, dtype=self.dtype)
            value = [1]
            x[0] = value

    def _dtype_error(self):
        with self.assertRaisesRegexp(
                TypeError,
                "When assign a numpy.ndarray, integer or float to a paddle.Tensor, "
        ):
            y = paddle.ones(shape=self.shape, dtype="float16")
            y[0] = 1

    def _step_error(self):
        with self.assertRaisesRegexp(ValueError, "step can not be 0"):
            x = paddle.ones(shape=self.shape, dtype=self.dtype)
            x[0:1:0] = self.value

    def _ellipsis_error(self):
        with self.assertRaisesRegexp(
                IndexError, "An index can only have a single ellipsis"):
            x = paddle.ones(shape=self.shape, dtype=self.dtype)
            x[..., ...] = self.value
        with self.assertRaisesRegexp(ValueError, "the start or end is None"):
            x = paddle.ones(shape=self.shape, dtype=self.dtype)
            one = paddle.ones([1])
            x[::one] = self.value

    def _broadcast_mismatch(self):
        program = paddle.static.Program()
        with paddle.static.program_guard(program):
            x = paddle.ones(shape=self.shape, dtype=self.dtype)
            value = np.array([3, 4, 5, 6, 7])
            x[0] = value
        exe = paddle.static.Executor(paddle.CPUPlace())
        with self.assertRaisesRegexp(ValueError,
                                     "Broadcast dimension mismatch."):
            exe.run(program)

    def test_error(self):
        paddle.enable_static()
        with paddle.static.program_guard(self.program):
            self._value_type_error()
            self._dtype_error()
            self._step_error()
        self._broadcast_mismatch()


# 5. Test backward


class Model(paddle.nn.Layer):
    def __init__(self):
        super(Model, self).__init__()
        self.conv = paddle.nn.Conv2D(12, 12, 3)

    def forward(self, x, y):
        x = self.conv(x)
        y = self.conv(y)
        var = y.flatten()

        x[0, :, 0, 0] = var
        loss = paddle.mean(x)
        return loss, var, x


class TestBackward(unittest.TestCase):
    def test_static(self):
        paddle.enable_static()
        main_program = paddle.static.Program()
        startup_program = paddle.static.Program()

        x_np = np.random.random(size=(4, 4)).astype('float32')
        y_np = np.random.random(size=(4, 4)).astype('float32')
        label_np = np.random.randint(2, size=(4, 1)).astype('int64')

        with paddle.static.program_guard(main_program, startup_program):
            x = paddle.static.data(name="x", shape=[4, 4], dtype='float32')
            y = paddle.static.data(name="y", shape=[4, 4], dtype='float32')

            label = paddle.static.data(
                name="label", shape=[4, 1], dtype='int64')

            z = paddle.add(x, y)
            var = y[0, :]
            z[0, :] = var

            prediction = paddle.static.nn.fc(x=z, size=2, activation='softmax')

            cost = paddle.nn.functional.cross_entropy(
                input=prediction, label=label)
            loss = paddle.mean(cost)
            sgd = paddle.optimizer.SGD(learning_rate=0.01)
            sgd.minimize(loss)

        exe = paddle.static.Executor(paddle.CPUPlace())
        exe.run(startup_program)

        var_grad, z_grad = exe.run(
            main_program,
            feed={"x": x_np,
                  "y": y_np,
                  "label": label_np},
            fetch_list=[var.name + "@GRAD", z.name + "@GRAD"])

        self.assertTrue((var_grad == z_grad[0, :]).all())

    def test_dynamic(self):
        paddle.disable_static()
        model = Model()
        x = paddle.ones([1, 12, 3, 3]).astype("float32")
        y = paddle.ones([1, 12, 3, 3]).astype("float32")
        loss, var, x = model(x, y)
        loss.backward()

        self.assertTrue(var.grad.shape == x.grad[0, :, 0, 0].shape)
        self.assertTrue((var.grad == x.grad[0, :, 0, 0]).all())


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