mindspore2022/mindspore/nn/layer/container.py

# Copyright 2020-2021 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""container"""
from collections import OrderedDict
from abc import abstractmethod
from ..cell import Cell

__all__ = ['SequentialCell', 'CellList']


def _valid_index(cell_num, index, op_name=None):
    """Internal function, used to detect the value and type of index."""
    msg_prefix = f"For '{op_name}', the" if op_name else "The"
    if not isinstance(index, int):
        raise TypeError(f"{msg_prefix} type of 'index' should be int, but got {type(index).__name__}.")
    if not -cell_num <= index < cell_num:
        raise IndexError(f"{msg_prefix} value of 'index' should be a number in range [{-cell_num}, {cell_num}), "
                         f"but got {index}.")
    return index % cell_num


def _valid_cell(cell, op_name=None):
    """Internal function, used to check whether the input cell is a subclass of Cell."""
    if issubclass(cell.__class__, Cell):
        return True
    msg_prefix = f"For '{op_name}'," if op_name else ""
    raise TypeError(f'{msg_prefix} each cell should be subclass of Cell, but got {type(cell).__name__}.')


def _get_prefix_and_index(cells):
    """get prefix and index of parameter name in sequential cell or cell list."""
    prefix = ""
    index = 0
    if not cells:
        return prefix, index

    cell_list = list(cells.items())
    first_param, first_key = None, None
    second_param, second_key = None, None
    for key, cell in cell_list:
        try:
            _, param = next(cell.parameters_and_names())
        except StopIteration:
            continue
        if first_param is None:
            first_param = param
            first_key = key
            continue
        second_param = param
        second_key = key
        break

    if first_param is None:
        return prefix, index

    split_names = first_param.name.split(".")
    for idx, name in enumerate(split_names):
        if name == first_key:
            prefix = ".".join(split_names[:idx])
            prefix = prefix + "." if prefix else prefix
            index = idx
            if second_param is not None and second_param.name.split(".")[idx] == second_key:
                break
    return prefix, index


class _CellListBase:
    """
    An interface for base the cell as list.

    The sequential cell may be iterated using the construct method using for-in statement.
    But there are some scenarios that the construct method built-in does not fit.
    For convenience, we provide an interface that indicates the sequential
    cell may be interpreted as list of cells, so it can be accessed using
    iterator or subscript when a sequential cell instantiate is accessed
    by iterator or subscript , it will be interpreted as a list of cells.
    """
    def __init__(self):
        """Initialize _CellListBase."""
        self.__cell_as_list__ = True

    @abstractmethod
    def __len__(self):
        pass

    @abstractmethod
    def __getitem__(self, index):
        pass

    def construct(self):
        raise NotImplementedError


class SequentialCell(Cell):
    """
    Sequential cell container.

    A list of Cells will be added to it in the order they are passed in the constructor.
    Alternatively, an ordered dict of cells can also be passed in.

    Args:
        args (list, OrderedDict): List of subclass of Cell.

    Inputs:
        - **x** (Tensor) - Tensor with shape according to the first Cell in the sequence.

    Outputs:
        Tensor, the output Tensor with shape depending on the input `x` and defined sequence of Cells.

    Raises:
        TypeError: If the type of the `args` is not list or OrderedDict.

    Supported Platforms:
        ``Ascend`` ``GPU`` ``CPU``

    Examples:
        >>> conv = nn.Conv2d(3, 2, 3, pad_mode='valid', weight_init="ones")
        >>> relu = nn.ReLU()
        >>> seq = nn.SequentialCell([conv, relu])
        >>> x = Tensor(np.ones([1, 3, 4, 4]), dtype=mindspore.float32)
        >>> output = seq(x)
        >>> print(output)
        [[[[27. 27.]
           [27. 27.]]
          [[27. 27.]
           [27. 27.]]]]
    """
    def __init__(self, *args):
        """Initialize SequentialCell."""
        super(SequentialCell, self).__init__()
        self._is_dynamic_name = []
        if len(args) == 1:
            cells = args[0]
            if isinstance(cells, list):
                for index, cell in enumerate(cells):
                    self.insert_child_to_cell(str(index), cell)
                    cell.update_parameters_name(str(index) + ".")
                    self._is_dynamic_name.append(True)
            elif isinstance(cells, OrderedDict):
                for name, cell in cells.items():
                    self.insert_child_to_cell(name, cell)
                    cell.update_parameters_name(name + ".")
                    self._is_dynamic_name.append(False)
            else:
                raise TypeError(f"For '{self.__class__.__name__}', the 'args[0]' must be list or orderedDict, "
                                f"but got {type(cells).__name__}")
        else:
            for index, cell in enumerate(args):
                self.insert_child_to_cell(str(index), cell)
                cell.update_parameters_name(str(index) + ".")
                self._is_dynamic_name.append(True)
        self.cell_list = list(self._cells.values())

    def __getitem__(self, index):
        if isinstance(index, slice):
            return self.__class__(
                OrderedDict(list(self._cells.items())[index]))
        index = _valid_index(len(self), index, self.__class__.__name__)
        return list(self._cells.values())[index]

    def __setitem__(self, index, cell):
        cls_name = self.__class__.__name__
        if _valid_cell(cell, cls_name):
            prefix, _ = _get_prefix_and_index(self._cells)
            index = _valid_index(len(self), index, cls_name)
            key = list(self._cells.keys())[index]
            self._cells[key] = cell
            cell.update_parameters_name(prefix + key + ".")
            self.cell_list = list(self._cells.values())

    def __delitem__(self, index):
        cls_name = self.__class__.__name__
        if isinstance(index, int):
            index = _valid_index(len(self), index, cls_name)
            key = list(self._cells.keys())[index]
            del self._cells[key]
            del self._is_dynamic_name[index]
        elif isinstance(index, slice):
            keys = list(self._cells.keys())[index]
            for key in keys:
                del self._cells[key]
            del self._is_dynamic_name[index]
        else:
            raise TypeError(f"For '{cls_name}', the type of index should be int type or slice type, "
                            f"but got {type(index).__name__}")
        prefix, key_index = _get_prefix_and_index(self._cells)
        temp_dict = OrderedDict()
        for idx, key in enumerate(self._cells.keys()):
            cell = self._cells[key]
            if self._is_dynamic_name[idx]:
                for _, param in cell.parameters_and_names():
                    param.name = prefix + str(idx) + "." + ".".join(param.name.split(".")[key_index+1:])
                temp_dict[str(idx)] = cell
            else:
                temp_dict[key] = cell
        self._cells = temp_dict
        self.cell_list = list(self._cells.values())

    def __len__(self):
        return len(self._cells)

    def set_grad(self, flag=True):
        self.requires_grad = flag
        for cell in self._cells.values():
            cell.set_grad(flag)

    def append(self, cell):
        """
        Appends a given cell to the end of the list.

        Args:
            cell(Cell): The subcell to be appended.

        Examples:
            >>> conv = nn.Conv2d(3, 2, 3, pad_mode='valid', weight_init="ones")
            >>> bn = nn.BatchNorm2d(2)
            >>> relu = nn.ReLU()
            >>> seq = nn.SequentialCell([conv, bn])
            >>> seq.append(relu)
            >>> x = Tensor(np.ones([1, 3, 4, 4]), dtype=mindspore.float32)
            >>> output = seq(x)
            >>> print(output)
            [[[[26.999863 26.999863]
               [26.999863 26.999863]]
              [[26.999863 26.999863]
               [26.999863 26.999863]]]]
        """
        if _valid_cell(cell, self.__class__.__name__):
            prefix, _ = _get_prefix_and_index(self._cells)
            cell.update_parameters_name(prefix + str(len(self)) + ".")
            self._is_dynamic_name.append(True)
            self._cells[str(len(self))] = cell
        self.cell_list = list(self._cells.values())

    def construct(self, input_data):
        for cell in self.cell_list:
            input_data = cell(input_data)
        return input_data


class CellList(_CellListBase, Cell):
    """
    Holds Cells in a list.

    CellList can be used like a regular Python list, support
    '__getitem__', '__setitem__', '__delitem__', '__len__', '__iter__' and '__iadd__',
    but cells it contains are properly registered, and will be visible by all Cell methods.

    Args:
        args (list, optional): List of subclass of Cell.

    Supported Platforms:
        ``Ascend`` ``GPU`` ``CPU``

    Examples:
        >>> conv = nn.Conv2d(100, 20, 3)
        >>> bn = nn.BatchNorm2d(20)
        >>> relu = nn.ReLU()
        >>> cell_ls = nn.CellList([bn])
        >>> cell_ls.insert(0, conv)
        >>> cell_ls.append(relu)
        >>> print(cell_ls)
        CellList<
          (0): Conv2d<input_channels=100, output_channels=20, kernel_size=(3, 3),stride=(1, 1),  pad_mode=same,
          padding=0, dilation=(1, 1), group=1, has_bias=False, weight_init=normal, bias_init=zeros, format=NCHW>
          (1): BatchNorm2d<num_features=20, eps=1e-05, momentum=0.09999999999999998, gamma=Parameter (name=1.gamma,
          shape=(20,), dtype=Float32, requires_grad=True), beta=Parameter (name=1.beta, shape=(20,), dtype=Float32,
          requires_grad=True), moving_mean=Parameter (name=1.moving_mean, shape=(20,), dtype=Float32,
          requires_grad=False), moving_variance=Parameter (name=1.moving_variance, shape=(20,), dtype=Float32,
          requires_grad=False)>
          (2): ReLU<>
          >
    """
    def __init__(self, *args, **kwargs):
        """Initialize CellList."""
        auto_prefix = kwargs["auto_prefix"] if "auto_prefix" in kwargs.keys() else True
        _CellListBase.__init__(self)
        Cell.__init__(self, auto_prefix)
        if len(args) == 1:
            self.extend(args[0])

    def __getitem__(self, index):
        cls_name = self.__class__.__name__
        if isinstance(index, slice):
            return self.__class__(list(self._cells.values())[index])
        if isinstance(index, int):
            index = _valid_index(len(self), index, cls_name)
            return self._cells[str(index)]
        raise TypeError(f"For '{cls_name}', the type of 'index' should be int or slice, "
                        f"but got {type(index).__name__}.")

    def __setitem__(self, index, cell):
        cls_name = self.__class__.__name__
        if not isinstance(index, int) and _valid_cell(cell, cls_name):
            raise TypeError(f"For '{cls_name}', the type of 'index' should be int, "
                            f"but got {type(index).__name__}.")
        index = _valid_index(len(self), index, cls_name)
        if self._auto_prefix:
            prefix, _ = _get_prefix_and_index(self._cells)
            cell.update_parameters_name(prefix + str(index) + ".")
        self._cells[str(index)] = cell

    def __delitem__(self, index):
        cls_name = self.__class__.__name__
        if isinstance(index, int):
            index = _valid_index(len(self), index, cls_name)
            del self._cells[str(index)]
        elif isinstance(index, slice):
            keys = list(self._cells.keys())[index]
            for key in keys:
                del self._cells[key]
        else:
            raise TypeError(f"For '{cls_name}', the type of 'index' should be int or slice, "
                            f"but got {type(index).__name__}.")
        # adjust orderedDict
        prefix, key_index = _get_prefix_and_index(self._cells)
        temp_dict = OrderedDict()
        for idx, cell in enumerate(self._cells.values()):
            if self._auto_prefix:
                for _, param in cell.parameters_and_names():
                    param.name = prefix + str(idx) + "." + ".".join(param.name.split(".")[key_index+1:])
            temp_dict[str(idx)] = cell
        self._cells = temp_dict

    def __len__(self):
        return len(self._cells)

    def __iter__(self):
        return iter(self._cells.values())

    def __iadd__(self, cells):
        self.extend(cells)
        return self

    def insert(self, index, cell):
        """
        Inserts a given cell before a given index in the list.

        Args:
            index(int): The Insert index in the CellList.
            cell(Cell): The subcell to be inserted.
        """
        cls_name = self.__class__.__name__
        idx = _valid_index(len(self), index, cls_name)
        _valid_cell(cell, cls_name)
        length = len(self)
        prefix, key_index = _get_prefix_and_index(self._cells)
        while length > idx:
            if self._auto_prefix:
                tmp_cell = self._cells[str(length-1)]
                for _, param in tmp_cell.parameters_and_names():
                    param.name = prefix + str(length) + "." + ".".join(param.name.split(".")[key_index+1:])
            self._cells[str(length)] = self._cells[str(length - 1)]
            length -= 1
        self._cells[str(idx)] = cell
        if self._auto_prefix:
            cell.update_parameters_name(prefix + str(idx) + ".")

    def extend(self, cells):
        """
        Appends cells from a Python iterable to the end of the list.

        Args:
            cells(list): The subcells to be extended.

        Raises:
            TypeError: If the cells are not a list of subcells.
        """
        cls_name = self.__class__.__name__
        if not isinstance(cells, list):
            raise TypeError(f"For '{cls_name}', the new cells wanted to append "
                            f"should be instance of list, but got {type(cells).__name__}.")
        prefix, _ = _get_prefix_and_index(self._cells)
        for cell in cells:
            if _valid_cell(cell, cls_name):
                if self._auto_prefix:
                    cell.update_parameters_name(prefix + str(len(self)) + ".")
                self._cells[str(len(self))] = cell
        return self

    def append(self, cell):
        """
        Appends a given cell to the end of the list.

        Args:
            cell(Cell): The subcell to be appended.
        """
        if _valid_cell(cell, self.__class__.__name__):
            if self._auto_prefix:
                prefix, _ = _get_prefix_and_index(self._cells)
                cell.update_parameters_name(prefix + str(len(self)) + ".")
            self._cells[str(len(self))] = cell

    def set_grad(self, flag=True):
        self.requires_grad = flag
        for cell in self._cells.values():
            cell.set_grad(flag)

    def construct(self, *inputs):
        raise NotImplementedError