# HG changeset patch
# User Frederic Bastien <nouiz@nouiz.org>
# Date 1285958554 14400
# Node ID 1a3090eca2ecd2d1cf635cee0af4016f6f4cdc13
# Parent  cc1c5720eeca4e87388d1fd5b941148225c30252
make the noise type the same as the input.

diff -r cc1c5720eeca -r 1a3090eca2ec pylearn/formulas/noise.py
--- a/pylearn/formulas/noise.py	Fri Oct 01 12:56:06 2010 -0400
+++ b/pylearn/formulas/noise.py	Fri Oct 01 14:42:34 2010 -0400
@@ -37,8 +37,7 @@
             size = inp.shape,
             n = 1,
             p =  1 - noise_lvl,
-            dtype=theano.config.floatX) 
-    # QUESTION: should the dtype not default to the input dtype?
+            dtype=inp.dtype)
     return mask * input
 
 
@@ -51,8 +50,9 @@
     :type noise_lvl: tuple(float,float)
     :param noise_lvl: The %% of noise for the salt and pepper. Between 0 (no noise) and 1.
     """
-    return theano_rng.binomial( size = inp.shape, n = 1, p =  1 - noise_lvl[0], dtype=theano.config.floatX) * inp \
-                        + (inp==0) * theano_rng.binomial( size = inp.shape, n = 1, p =  noise_lvl[1], dtype=theano.config.floatX)
+    assert inp.dtype in ['float32','float64']
+    return theano_rng.binomial( size = inp.shape, n = 1, p =  1 - noise_lvl[0], dtype=inp.dtype) * inp \
+                        + (inp==0) * theano_rng.binomial( size = inp.shape, n = 1, p =  noise_lvl[1], dtype=inp.dtype)
 
 @tags.tags('noise','gauss','gaussian')
 def gaussian_noise(theano_rng,inp,noise_lvl):
@@ -63,4 +63,5 @@
     :type noise_lvl: float
     :param noise_lvl: The standard deviation of the gaussian.
     """
-    return theano_rng.normal( size = inp.shape, std = noise_lvl, dtype=theano.config.floatX) + inp
+    assert inp.dtype in ['float32','float64']
+    return theano_rng.normal( size = inp.shape, std = noise_lvl, dtype=inp.dtype) + inp