# 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' must be int, but got {type(index).__name__}.")
if not -cell_num <= index < cell_num:
raise IndexError(f"{msg_prefix} value of 'index' must 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 must 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
[docs]class SequentialCell(Cell):
"""
Sequential Cell container. For more details about Cell, please refer to
`Cell <https://www.mindspore.cn/docs/en/r1.8/api_python/nn/mindspore.nn.Cell.html#mindspore.nn.Cell>`_.
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.
Note:
SequentialCell and torch.nn.ModuleList are different, ModuleList is a list for storing modules. However,
the layers in a Sequential are connected in a cascading way.
Args:
args (list, OrderedDict): List or OrderedDict 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:
>>> from mindspore import Tensor
>>> import mindspore
>>> import mindspore.nn as nn
>>> import numpy as np
>>>
>>> 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.]]]]
>>> from collections import OrderedDict
>>> d = OrderedDict()
>>> d["conv"] = conv
>>> d["relu"] = relu
>>> seq = nn.SequentialCell(d)
>>> 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 must 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)
[docs] def append(self, cell):
"""
Appends a given Cell to the end of the list.
Args:
cell(Cell): The Cell to be appended.
Examples:
>>> from mindspore import Tensor
>>> import mindspore
>>> import mindspore.nn as nn
>>> import numpy as np
>>>
>>> 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
[docs]class CellList(_CellListBase, Cell):
"""
Holds Cells in a list. For more details about Cell, please refer to
`Cell <https://www.mindspore.cn/docs/en/r1.8/api_python/nn/mindspore.nn.Cell.html#mindspore.nn.Cell>`_.
CellList can be used like a regular Python list, the Cells it contains have been initialized.
Args:
args (list, optional): List of subclass of Cell.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> import mindspore.nn as nn
>>>
>>> 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)
>>> cell_ls.extend([relu, 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' must 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' must 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' must 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
[docs] 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 Cell 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) + ".")
[docs] def extend(self, cells):
"""
Appends Cells from a Python iterable to the end of the list.
Args:
cells(list): The Cells to be extended.
Raises:
TypeError: If the argument cells are not a list of Cells.
"""
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
[docs] 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