fix activation

deepspeech/__init__.py

@@ -351,20 +351,3 @@ if not hasattr(paddle.Tensor, 'tolist'):
     logger.warn(
         "register user tolist to paddle.Tensor, remove this when fixed!")
     setattr(paddle.Tensor, 'tolist', tolist)
-
-
-########### hcak paddle.nn #############
-class GLU(nn.Layer):
-    """Gated Linear Units (GLU) Layer"""
-
-    def __init__(self, dim: int=-1):
-        super().__init__()
-        self.dim = dim
-
-    def forward(self, xs):
-        return F.glu(xs, axis=self.dim)
-
-
-if not hasattr(paddle.nn, 'GLU'):
-    logger.warn("register user GLU to paddle.nn, remove this when fixed!")
-    setattr(paddle.nn, 'GLU', GLU)

deepspeech/modules/activation.py

@@ -15,12 +15,13 @@ from collections import OrderedDict
 
 import paddle
 from paddle import nn
+from paddle.nn import functional as F
 
 from deepspeech.utils.log import Log
 
 logger = Log(__name__).getlog()
 
-__all__ = ["get_activation", "brelu", "LinearGLUBlock", "ConvGLUBlock"]
+__all__ = ["get_activation", "brelu", "LinearGLUBlock", "ConvGLUBlock", "GLU"]
 
 
 def brelu(x, t_min=0.0, t_max=24.0, name=None):
@@ -30,6 +31,17 @@ def brelu(x, t_min=0.0, t_max=24.0, name=None):
     return x.maximum(t_min).minimum(t_max)
 
 
+class GLU(nn.Layer):
+    """Gated Linear Units (GLU) Layer"""
+
+    def __init__(self, dim: int=-1):
+        super().__init__()
+        self.dim = dim
+
+    def forward(self, xs):
+        return F.glu(xs, axis=self.dim)
+
+
 class LinearGLUBlock(nn.Layer):
     """A linear Gated Linear Units (GLU) block."""
 
@@ -133,13 +145,18 @@ def get_activation(act):
     """Return activation function."""
     # Lazy load to avoid unused import
     activation_funcs = {
+        "hardshrink": paddle.nn.Hardshrink,
+        "hardswish": paddle.nn.Hardswish,
         "hardtanh": paddle.nn.Hardtanh,
         "tanh": paddle.nn.Tanh,
         "relu": paddle.nn.ReLU,
+        "relu6": paddle.nn.ReLU6,
+        "leakyrelu": paddle.nn.LeakyReLU,
         "selu": paddle.nn.SELU,
         "swish": paddle.nn.Swish,
         "gelu": paddle.nn.GELU,
-        "brelu": brelu,
+        "glu": GLU,
+        "elu": paddle.nn.ELU,
     }
 
     return activation_funcs[act]()