[mode] move recurrent models in brainpy.dnn model into brainpy.dyn module

Author: chaoming0625

brainpy/_add_deprecations.py

@@ -101,6 +101,30 @@
 }
 dyn.__getattr__ = deprecation_getattr2('brainpy.dyn', dyn.__deprecations)
 
+dnn.__deprecations = {
+  'NVAR': ('brainpy.dnn.NVAR', 'brainpy.dyn.NVAR', dyn.NVAR),
+  'Reservoir': ('brainpy.dnn.Reservoir', 'brainpy.dyn.Reservoir', dyn.Reservoir),
+  'RNNCell': ('brainpy.dnn.RNNCell', 'brainpy.dyn.RNNCell', dyn.RNNCell),
+  'GRUCell': ('brainpy.dnn.GRUCell', 'brainpy.dyn.GRUCell', dyn.GRUCell),
+  'LSTMCell': ('brainpy.dnn.LSTMCell', 'brainpy.dyn.LSTMCell', dyn.LSTMCell),
+  'Conv1dLSTMCell': ('brainpy.dnn.Conv1dLSTMCell', 'brainpy.dyn.Conv1dLSTMCell', dyn.Conv1dLSTMCell),
+  'Conv2dLSTMCell': ('brainpy.dnn.Conv2dLSTMCell', 'brainpy.dyn.Conv2dLSTMCell', dyn.Conv2dLSTMCell),
+  'Conv3dLSTMCell': ('brainpy.dnn.Conv3dLSTMCell', 'brainpy.dyn.Conv3dLSTMCell', dyn.Conv3dLSTMCell),
+}
+dnn.__getattr__ = deprecation_getattr2('brainpy.dnn', dnn.__deprecations)
+
+layers.__deprecations = {
+  'NVAR': ('brainpy.layers.NVAR', 'brainpy.dyn.NVAR', dyn.NVAR),
+  'Reservoir': ('brainpy.layers.Reservoir', 'brainpy.dyn.Reservoir', dyn.Reservoir),
+  'RNNCell': ('brainpy.layers.RNNCell', 'brainpy.dyn.RNNCell', dyn.RNNCell),
+  'GRUCell': ('brainpy.layers.GRUCell', 'brainpy.dyn.GRUCell', dyn.GRUCell),
+  'LSTMCell': ('brainpy.layers.LSTMCell', 'brainpy.dyn.LSTMCell', dyn.LSTMCell),
+  'Conv1dLSTMCell': ('brainpy.layers.Conv1dLSTMCell', 'brainpy.dyn.Conv1dLSTMCell', dyn.Conv1dLSTMCell),
+  'Conv2dLSTMCell': ('brainpy.layers.Conv2dLSTMCell', 'brainpy.dyn.Conv2dLSTMCell', dyn.Conv2dLSTMCell),
+  'Conv3dLSTMCell': ('brainpy.layers.Conv3dLSTMCell', 'brainpy.dyn.Conv3dLSTMCell', dyn.Conv3dLSTMCell),
+}
+layers.__getattr__ = deprecation_getattr2('brainpy.layers', layers.__deprecations)
+
 
 connect.__deprecations = {
     'one2one': ('brainpy.connect.one2one', 'brainpy.connect.One2One', connect.One2One),

brainpy/_src/dnn/__init__.py

@@ -3,9 +3,6 @@
 from .base import *
 from .activations import *
 from .dropout import *
-from .nvar import *
-from .reservoir import *
-from .rnncells import *
 from .conv import *
 from .normalization import *
 from .pooling import *

brainpy/_src/dyn/rates/__init__.py

@@ -1,3 +1,8 @@
 # -*- coding: utf-8 -*-
 
 from .populations import *
+from .reservoir import *
+from .nvar import *
+from .rnncells import *
+
+

brainpy/_src/dnn/nvar.py renamed to brainpy/_src/dyn/rates/nvar.py

@@ -17,8 +17,7 @@
 
 
 class Reservoir(Layer):
-  r"""Reservoir node, a pool of leaky-integrator neurons
-  with random recurrent connections [1]_.
+  r"""Reservoir node, a pool of leaky-integrator neurons with random recurrent connections [1]_.
 
   Parameters
   ----------
@@ -81,8 +80,6 @@ class Reservoir(Layer):
     Distribution of noise. Must be a random variable generator
     distribution (see :py:class:`brainpy.math.random.RandomState`),
     by default "normal". 
-  seed: optional, int
-    The seed for random sampling in this node.
 
   References
   ----------
@@ -107,7 +104,6 @@ def __init__(
       noise_in: float = 0.,
       noise_rec: float = 0.,
       noise_type: str = 'normal',
-      seed: Optional[int] = None,
       mode: Optional[bm.Mode] = None,
       name: Optional[str] = None
   ):

brainpy/_src/dnn/reservoir.py renamed to brainpy/_src/dyn/rates/reservoir.py

@@ -18,13 +18,12 @@
                                 variable_,
                                 Initializer)
 from brainpy.types import ArrayType
-from .conv import _GeneralConv
+from brainpy._src.dnn.conv import _GeneralConv
+
 
 __all__ = [
   'RNNCell', 'GRUCell', 'LSTMCell',
   'Conv1dLSTMCell', 'Conv2dLSTMCell', 'Conv3dLSTMCell',
-  # deprecated
-  'VanillaRNN', 'GRU', 'LSTM',
 ]
 
 
@@ -404,50 +403,6 @@ def c(self, value):
     self.state[self.state.shape[0] // 2:, :] = value
 
 
-class VanillaRNN(RNNCell):
-  """Vanilla RNN.
-
-  .. deprecated:: 2.2.3.4
-     Use :py:class:`~.RNNCell` instead. :py:class:`~.VanillaRNN` will be removed since version 2.4.0.
-
-  """
-
-  def __init__(self, *args, **kwargs):
-    super(VanillaRNN, self).__init__(*args, **kwargs)
-    warnings.warn('Use "brainpy.layers.RNNCell" instead. '
-                  '"brainpy.layers.VanillaRNN" is deprecated and will be removed since 2.4.0.',
-                  UserWarning)
-
-
-class GRU(GRUCell):
-  """GRU.
-
-  .. deprecated:: 2.2.3.4
-     Use :py:class:`~.GRUCell` instead. :py:class:`~.GRU` will be removed since version 2.4.0.
-
-  """
-
-  def __init__(self, *args, **kwargs):
-    super(GRU, self).__init__(*args, **kwargs)
-    warnings.warn('Use "brainpy.layers.GRUCell" instead. '
-                  '"brainpy.layers.GRU" is deprecated and will be removed since 2.4.0.',
-                  UserWarning)
-
-
-class LSTM(LSTMCell):
-  """LSTM.
-
-  .. deprecated:: 2.2.3.4
-     Use :py:class:`~.LSTMCell` instead. :py:class:`~.LSTM` will be removed since version 2.4.0.
-
-  """
-
-  def __init__(self, *args, **kwargs):
-    warnings.warn('Use "brainpy.layers.LSTMCell" instead. '
-                  '"brainpy.layers.LSTM" is deprecated and will be removed since 2.4.0.',
-                  UserWarning)
-    super(LSTM, self).__init__(*args, **kwargs)
-
 
 class _ConvNDLSTMCell(Layer):
   r"""``num_spatial_dims``-D convolutional LSTM.

brainpy/_src/dnn/rnncells.py renamed to brainpy/_src/dyn/rates/rnncells.py

@@ -12,17 +12,18 @@ class Test_Reservoir(parameterized.TestCase):
               bm.BatchingMode(10),
               bm.NonBatchingMode()]
     )
-    def test_Reservoir(self,mode):
+    def test_Reservoir(self, mode):
         bm.random.seed()
-        input=bm.random.randn(10,3)
-        layer=bp.dnn.Reservoir(input_shape=3,
-                               num_out=5,
-                               mode=mode)
+        input = bm.random.randn(10, 3)
+        layer = bp.dnn.Reservoir(input_shape=3,
+                                 num_out=5,
+                                 mode=mode)
         if mode in [bm.NonBatchingMode()]:
             for i in input:
-                output=layer(i)
+                output = layer(i)
         else:
-            output=layer(input)
+            output = layer(input)
+
 
 if __name__ == '__main__':
     absltest.main()

brainpy/_src/dnn/tests/test_nvar.py renamed to brainpy/_src/dyn/rates/tests/test_nvar.py

@@ -6,4 +6,3 @@
 from .normalization import *
 from .others import *
 from .pooling import *
-from .recurrent import *