#   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.

from ..core import AnalysisConfig, PaddleDType, PaddlePlace
from ..core import PaddleInferPredictor, PaddleInferTensor
from ..core import convert_to_mixed_precision_bind
from .. import core

import os
import numpy as np
from typing import Set

DataType = PaddleDType
PlaceType = PaddlePlace
PrecisionType = AnalysisConfig.Precision
BackendType = AnalysisConfig.Backend
Config = AnalysisConfig
Tensor = PaddleInferTensor
Predictor = PaddleInferPredictor


def tensor_copy_from_cpu(self, data):
    '''
    Support input type check based on tensor.copy_from_cpu.
    '''
    if isinstance(data, np.ndarray) or (isinstance(data, list) and len(data) > 0
                                        and isinstance(data[0], str)):
        self.copy_from_cpu_bind(data)
    else:
        raise TypeError(
            "In copy_from_cpu, we only support numpy ndarray and list[str] data type."
        )


def tensor_share_external_data(self, data):
    '''
    Support input type check based on tensor.share_external_data.
    '''
    if isinstance(data, core.LoDTensor):
        self.share_external_data_bind(data)
    else:
        raise TypeError(
            "In share_external_data, we only support LoDTensor data type.")


def convert_to_mixed_precision(model_file: str,
                               params_file: str,
                               mixed_model_file: str,
                               mixed_params_file: str,
                               mixed_precision: PrecisionType,
                               backend: BackendType,
                               keep_io_types: bool = True,
                               black_list: Set = set()):
    '''
    Convert a fp32 model to mixed precision model.

    Args:
        model_file: fp32 model file, e.g. inference.pdmodel.
        params_file: fp32 params file, e.g. inference.pdiparams.
        mixed_model_file: The storage path of the converted mixed-precision model.
        mixed_params_file: The storage path of the converted mixed-precision params.
        mixed_precision: The precision, e.g. PrecisionType.Half.
        backend: The backend, e.g. BackendType.GPU.
        keep_io_types: Whether the model input and output dtype remains unchanged.
        black_list: Operators that do not convert precision.
    '''
    mixed_model_dirname = os.path.dirname(mixed_model_file)
    mixed_params_dirname = os.path.dirname(mixed_params_file)
    if not os.path.exists(mixed_model_dirname):
        os.makedirs(mixed_model_dirname)
    if not os.path.exists(mixed_params_dirname):
        os.makedirs(mixed_params_dirname)
    convert_to_mixed_precision_bind(model_file, params_file, mixed_model_file,
                                    mixed_params_file, mixed_precision, backend,
                                    keep_io_types, black_list)


Tensor.copy_from_cpu = tensor_copy_from_cpu
Tensor.share_external_data = tensor_share_external_data
