#   Copyright (c) 2022 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 .layer_function_generator import (
    generate_layer_fn,
    generate_activation_fn,
    generate_inplace_fn,
    add_sample_code,
)
from ..fluid.data_feeder import check_variable_and_dtype
from ..fluid.framework import in_dygraph_mode, _in_legacy_dygraph
from ..framework import LayerHelper
from .. import _C_ops, _legacy_C_ops

__deprecated_func_name__ = {
    'tanh_shrink': 'tanhshrink',
    'logsigmoid': 'log_sigmoid',
}

__activations_noattr__ = [
    'sigmoid',
    'silu',
    'logsigmoid',
    'tanh_shrink',
    'softplus',
    'softsign',
    'tanh',
]

__unary_func__ = [
    'expm1',
    'atan',
    'sqrt',
    'rsqrt',
    'abs',
    'ceil',
    'floor',
    'cos',
    'tan',
    'acos',
    'sin',
    'sinh',
    'asin',
    'cosh',
    'round',
    'reciprocal',
    'square',
    'acosh',
    'asinh',
    'atanh',
]

__inplace_unary_func__ = [
    'exp_',
    'sqrt_',
    'rsqrt_',
    'ceil_',
    'floor_',
    'round_',
    'reciprocal_',
]

__all__ = []

for _OP in set(__all__):
    globals()[_OP] = generate_layer_fn(_OP)

# It is a hot fix in some unittest using:
#   fluid.layers.scale(x=x, scale=10.0, out=out_var)
# e.g.: test_program_code.py, test_dist_train.py
globals()['_scale'] = generate_layer_fn('scale')

globals()['_elementwise_div'] = generate_layer_fn('elementwise_div')

__all__ += __activations_noattr__
__all__ += __unary_func__
__all__ += __inplace_unary_func__

for _OP in set(__activations_noattr__):
    _new_OP = _OP
    if _OP in __deprecated_func_name__:
        _new_OP = __deprecated_func_name__[_OP]
    _func = generate_activation_fn(_OP)
    globals()[_OP] = _func

for _OP in set(__unary_func__):
    _new_OP = _OP
    if _OP in __deprecated_func_name__:
        _new_OP = __deprecated_func_name__[_OP]
    _func = generate_activation_fn(_OP)
    globals()[_OP] = _func

for _OP in set(__inplace_unary_func__):
    _new_OP = _OP
    if _OP in __deprecated_func_name__:
        _new_OP = __deprecated_func_name__[_OP]
    _func = generate_inplace_fn(_OP)
    globals()[_OP] = _func

add_sample_code(
    globals()["sigmoid"],
    r"""
Examples:
    .. code-block:: python

        import paddle
        import paddle.nn.functional as F

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = F.sigmoid(x)
        print(out)
        # [0.40131234 0.450166   0.52497919 0.57444252]

""",
)

add_sample_code(
    globals()["silu"],
    r"""
Examples:
    .. code-block:: python

        import paddle
        import paddle.nn.functional as F

        x = paddle.to_tensor([1.0, 2.0, 3.0, 4.0])
        out = F.silu(x)
        print(out)
        # [ 0.7310586 1.7615942 2.8577224, 3.9280552 ]

""",
)

add_sample_code(
    globals()["logsigmoid"],
    r"""
Examples:
    .. code-block:: python

        import paddle
        import paddle.nn.functional as F

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = F.log_sigmoid(x)
        print(out)
        # [-0.91301525 -0.79813887 -0.64439666 -0.55435524]

""",
)

add_sample_code(
    globals()["expm1"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.expm1(x)
        print(out)
        # [-0.32967997, -0.18126924,  0.10517092,  0.34985882]

""",
)

add_sample_code(
    globals()["tanh"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.tanh(x)
        print(out)
        # [-0.37994896 -0.19737532  0.09966799  0.29131261]

""",
)

add_sample_code(
    globals()["atan"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.atan(x)
        print(out)
        # [-0.38050638 -0.19739556  0.09966865  0.29145679]

""",
)

add_sample_code(
    globals()["tanh_shrink"],
    r"""
Examples:
    .. code-block:: python

        import paddle
        import paddle.nn.functional as F

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = F.tanhshrink(x)
        print(out)
        # [-0.020051, -0.00262468, 0.000332005, 0.00868739]

""",
)

add_sample_code(
    globals()["sqrt"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([0.1, 0.2, 0.3, 0.4])
        out = paddle.sqrt(x)
        print(out)
        # [0.31622777 0.4472136  0.54772256 0.63245553]

""",
)

add_sample_code(
    globals()["rsqrt"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([0.1, 0.2, 0.3, 0.4])
        out = paddle.rsqrt(x)
        print(out)
        # [3.16227766 2.23606798 1.82574186 1.58113883]

""",
)

add_sample_code(
    globals()["abs"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.abs(x)
        print(out)
        # [0.4 0.2 0.1 0.3]

""",
)

add_sample_code(
    globals()["ceil"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.ceil(x)
        print(out)
        # [-0. -0.  1.  1.]

""",
)

add_sample_code(
    globals()["floor"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.floor(x)
        print(out)
        # [-1. -1.  0.  0.]

""",
)

add_sample_code(
    globals()["cos"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.cos(x)
        print(out)
        # [0.92106099 0.98006658 0.99500417 0.95533649]

""",
)

add_sample_code(
    globals()["tan"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.tan(x)
        print(out)
        # [-0.42279324, -0.20271005, 0.10033467, 0.30933627]

""",
)

add_sample_code(
    globals()["acos"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.acos(x)
        print(out)
        # [1.98231317 1.77215425 1.47062891 1.26610367]

""",
)

add_sample_code(
    globals()["sin"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.sin(x)
        print(out)
        # [-0.38941834 -0.19866933  0.09983342  0.29552021]

""",
)

add_sample_code(
    globals()["asin"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.asin(x)
        print(out)
        # [-0.41151685 -0.20135792  0.10016742  0.30469265]

""",
)

add_sample_code(
    globals()["cosh"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.cosh(x)
        print(out)
        # [1.08107237 1.02006676 1.00500417 1.04533851]

""",
)

add_sample_code(
    globals()["sinh"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.sinh(x)
        print(out)
        # [-0.41075233 -0.201336    0.10016675  0.30452029]

""",
)

add_sample_code(
    globals()["asinh"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.asinh(x)
        print(out)
        # [-0.39003533, -0.19869010,  0.09983408,  0.29567307]

""",
)

add_sample_code(
    globals()["acosh"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([1., 3., 4., 5.])
        out = paddle.acosh(x)
        print(out)
        # [0.        , 1.76274729, 2.06343699, 2.29243159]

""",
)

add_sample_code(
    globals()["atanh"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.atanh(x)
        print(out)
        # [-0.42364895, -0.20273256,  0.10033535,  0.30951962]

""",
)

add_sample_code(
    globals()["round"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.5, -0.2, 0.6, 1.5])
        out = paddle.round(x)
        print(out)
        # [-1. -0.  1.  2.]

""",
)

add_sample_code(
    globals()["reciprocal"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.reciprocal(x)
        print(out)
        # [-2.5        -5.         10.          3.33333333]

""",
)

add_sample_code(
    globals()["square"],
    r"""
Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.square(x)
        print(out)
        # [0.16 0.04 0.01 0.09]

""",
)

add_sample_code(
    globals()["softplus"],
    r"""
Examples:
    .. code-block:: python

        import paddle
        import paddle.nn.functional as F

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = F.softplus(x)
        print(out)
        # [0.513015, 0.598139, 0.744397, 0.854355]

""",
)

add_sample_code(
    globals()["softsign"],
    r"""
Examples:
    .. code-block:: python

        import paddle
        import paddle.nn.functional as F

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = F.softsign(x)
        print(out)
        # [-0.285714, -0.166667, 0.0909091, 0.230769]

""",
)


def exp(x, name=None):
    """

    Computes exp of x element-wise with a natural number `e` as the base.

    .. math::
        out = e^x

    Args:
        x (Tensor): Input of Exp operator, an N-D Tensor, with data type float32, float64 or float16.
        name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.

    Returns:
        Tensor. Output of Exp operator, a Tensor with shape same as input.

    Examples:
        .. code-block:: python

            import paddle

            x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
            out = paddle.exp(x)
            print(out)
            # [0.67032005 0.81873075 1.10517092 1.34985881]

    """
    if in_dygraph_mode():
        return _C_ops.exp(x)
    if _in_legacy_dygraph():
        return _legacy_C_ops.exp(x)

    check_variable_and_dtype(
        x,
        'x',
        [
            'int32',
            'int64',
            'float16',
            'float32',
            'float64',
            'complex64',
            'complex128',
        ],
        'exp',
    )
    helper = LayerHelper('exp', **locals())
    out = helper.create_variable_for_type_inference(dtype=x.dtype)
    helper.append_op(type='exp', inputs={"X": x}, outputs={"Out": out})
    return out


__all__ += ['erf']

_erf_ = generate_layer_fn('erf')


def erf(x, name=None):
    if in_dygraph_mode():
        return _C_ops.erf(x)

    locals_var = locals().copy()
    kwargs = dict()
    for name, val in locals_var.items():
        if val is not None:
            kwargs[name] = val
    return _erf_(**kwargs)


erf.__doc__ = r"""
:strong:`Erf Operator`
For more details, see `Error function <https://en.wikipedia.org/wiki/Error_function>`_.

Equation:
    ..  math::
        out = \frac{2}{\sqrt{\pi}} \int_{0}^{x}e^{- \eta^{2}}d\eta

Args:

    x (Tensor): The input tensor, it's data type should be float32, float64.
    name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.

Returns:

    Tensor: The output of Erf, dtype: float32 or float64, the same as the input, shape: the same as the input.

Examples:

    .. code-block:: python

        import paddle

        x = paddle.to_tensor([-0.4, -0.2, 0.1, 0.3])
        out = paddle.erf(x)
        print(out)
        # [-0.42839236 -0.22270259  0.11246292  0.32862676]
"""