!1081 format nn. and change quant.py

Merge pull request !1081 from SanjayChan/formast

mindspore/nn/layer/__init__.py

@@ -17,24 +17,26 @@ Layer.
 
 The high-level components(Cells) used to construct the neural network.
 """
-from .activation import Softmax, LogSoftmax, ReLU, ReLU6, Tanh, GELU, ELU, Sigmoid, PReLU, get_activation, LeakyReLU, HSigmoid, HSwish
-from .normalization import BatchNorm1d, BatchNorm2d, LayerNorm, GroupNorm, GlobalBatchNorm
-from .container import SequentialCell, CellList
-from .conv import Conv2d, Conv2dTranspose
-from .lstm import LSTM
-from .basic import Dropout, Flatten, Dense, ClipByNorm, Norm, OneHot, Pad, Unfold
-from .embedding import Embedding
-from .pooling import AvgPool2d, MaxPool2d, AvgPool1d
-from .image import ImageGradients, SSIM, PSNR
+from . import activation, normalization, container, conv, lstm, basic, embedding, pooling, image, quant
+from .activation import *
+from .normalization import *
+from .container import *
+from .conv import *
+from .lstm import *
+from .basic import *
+from .embedding import *
+from .pooling import *
+from .image import *
+from .quant import *
 
-__all__ = ['Softmax', 'LogSoftmax', 'ReLU', 'ReLU6', 'Tanh', 'GELU', 'Sigmoid',
-           'PReLU', 'get_activation', 'LeakyReLU', 'HSigmoid', 'HSwish', 'ELU',
-           'BatchNorm1d', 'BatchNorm2d', 'LayerNorm', 'GroupNorm', 'GlobalBatchNorm',
-           'SequentialCell', 'CellList',
-           'Conv2d', 'Conv2dTranspose',
-           'LSTM',
-           'Dropout', 'Flatten', 'Dense', 'ClipByNorm', 'Norm', 'OneHot',
-           'Embedding',
-           'AvgPool2d', 'MaxPool2d', 'AvgPool1d', 'Pad', 'Unfold',
-           'ImageGradients', 'SSIM', 'PSNR',
-           ]
+__all__ = []
+__all__.extend(activation.__all__)
+__all__.extend(normalization.__all__)
+__all__.extend(container.__all__)
+__all__.extend(conv.__all__)
+__all__.extend(lstm.__all__)
+__all__.extend(basic.__all__)
+__all__.extend(embedding.__all__)
+__all__.extend(pooling.__all__)
+__all__.extend(image.__all__)
+__all__.extend(quant.__all__)

mindspore/nn/layer/activation.py

@@ -22,6 +22,21 @@ from mindspore.common.tensor import Tensor
 from mindspore._extends import cell_attr_register
 from ..cell import Cell
 
+__all__ = ['Softmax',
+           'LogSoftmax',
+           'ReLU',
+           'ReLU6',
+           'Tanh',
+           'GELU',
+           'Sigmoid',
+           'PReLU',
+           'get_activation',
+           'LeakyReLU',
+           'HSigmoid',
+           'HSwish',
+           'ELU',
+           ]
+
 
 class Softmax(Cell):
     r"""
@@ -54,6 +69,7 @@ class Softmax(Cell):
         >>> softmax(input_x)
         [0.03168  0.01166  0.0861  0.636  0.2341]
     """
+
     def __init__(self, axis=-1):
         super(Softmax, self).__init__()
         self.softmax = P.Softmax(axis)
@@ -128,6 +144,7 @@ class ELU(Cell):
         >>> elu(input_x)
 
     """
+
     def __init__(self, alpha=1.0):
         super(ELU, self).__init__()
         self.elu = P.Elu(alpha)
@@ -156,6 +173,7 @@ class ReLU(Cell):
         >>> relu(input_x)
         [0.  2.  0.  2.  0.]
     """
+
     def __init__(self):
         super(ReLU, self).__init__()
         self.relu = P.ReLU()
@@ -184,6 +202,7 @@ class ReLU6(Cell):
         >>> relu6(input_x)
         [0.  0.  0.  2.  1.]
     """
+
     def __init__(self):
         super(ReLU6, self).__init__()
         self.relu6 = P.ReLU6()
@@ -221,6 +240,7 @@ class LeakyReLU(Cell):
         [[-0.2  4.  -1.6]
          [ 2   -1.   9.]]
     """
+
     def __init__(self, alpha=0.2):
         super(LeakyReLU, self).__init__()
         self.greater_equal = P.GreaterEqual()
@@ -262,6 +282,7 @@ class Tanh(Cell):
         >>> tanh(input_x)
         [0.7617  0.964  0.995  0.964 0.7617]
     """
+
     def __init__(self):
         super(Tanh, self).__init__()
         self.tanh = P.Tanh()
@@ -293,6 +314,7 @@ class GELU(Cell):
         [[-1.5880802e-01  3.9999299e+00 -3.1077917e-21]
          [ 1.9545976e+00 -2.2918017e-07  9.0000000e+00]]
     """
+
     def __init__(self):
         super(GELU, self).__init__()
         self.gelu = P.Gelu()
@@ -322,6 +344,7 @@ class Sigmoid(Cell):
         >>> sigmoid(input_x)
         [0.2688  0.11914  0.5  0.881  0.7305]
     """
+
     def __init__(self):
         super(Sigmoid, self).__init__()
         self.sigmoid = P.Sigmoid()
@@ -410,6 +433,7 @@ class HSwish(Cell):
         >>> hswish(input_x)
 
     """
+
     def __init__(self):
         super(HSwish, self).__init__()
         self.hswish = P.HSwish()
@@ -443,6 +467,7 @@ class HSigmoid(Cell):
         >>> hsigmoid(input_x)
 
     """
+
     def __init__(self):
         super(HSigmoid, self).__init__()
         self.hsigmoid = P.HSigmoid()

mindspore/nn/layer/basic.py

@@ -30,6 +30,7 @@ from ..cell import Cell
 from .activation import get_activation
 from ..._checkparam import Validator as validator
 
+__all__ = ['Dropout', 'Flatten', 'Dense', 'ClipByNorm', 'Norm', 'OneHot', 'Pad', 'Unfold']
 
 class Dropout(Cell):
     r"""

mindspore/nn/layer/container.py

@@ -15,9 +15,9 @@
 """container"""
 from collections import OrderedDict
 from abc import abstractmethod, ABCMeta
-
 from ..cell import Cell
 
+__all__ = ['SequentialCell', 'CellList']
 
 def _valid_index(cell_num, index):
     if not isinstance(index, int):

mindspore/nn/layer/conv.py

@@ -21,6 +21,7 @@ from mindspore._checkparam import check_bool, twice, check_int_positive, check_i
 from mindspore._extends import cell_attr_register
 from ..cell import Cell
 
+__all__ = ['Conv2d', 'Conv2dTranspose']
 
 class _Conv(Cell):
     """

mindspore/nn/layer/embedding.py

@@ -21,6 +21,7 @@ from mindspore.common.initializer import initializer
 from ..cell import Cell
 from ..._checkparam import Validator as validator
 
+__all__ = ['Embedding']
 
 class Embedding(Cell):
     r"""

mindspore/nn/layer/image.py

@@ -23,6 +23,7 @@ from mindspore._checkparam import Validator as validator
 from mindspore._checkparam import Rel
 from ..cell import Cell
 
+__all__ = ['ImageGradients', 'SSIM', 'PSNR']
 
 class ImageGradients(Cell):
     r"""

mindspore/nn/layer/lstm.py

@@ -19,6 +19,7 @@ from mindspore.common.parameter import Parameter
 from mindspore.common.initializer import initializer
 from mindspore._checkparam import Validator as validator
 
+__all__ = ['LSTM']
 
 class LSTM(Cell):
     r"""

mindspore/nn/layer/normalization.py

@@ -29,6 +29,8 @@ from mindspore._checkparam import check_int_positive
 from ..cell import Cell
 
 
+__all__ = ['BatchNorm1d', 'BatchNorm2d', 'LayerNorm', 'GroupNorm', 'GlobalBatchNorm']
+
 class _BatchNorm(Cell):
     """Batch Normalization base class."""
     @cell_attr_register

mindspore/nn/layer/pooling.py

@@ -21,6 +21,7 @@ from ... import context
 from ..cell import Cell
 from ..._checkparam import Rel
 
+__all__ = ['AvgPool2d', 'MaxPool2d', 'AvgPool1d']
 
 class _PoolNd(Cell):
     """N-D  AvgPool"""