added the theano dtype floatX with THEANO_FLAGS=floatX=float{32,64} to allow…

theano/config.py

@@ -10,6 +10,7 @@ default_={
 'lib.amdlibm':False,
 'op.set_flops':False,#currently used only in ConvOp. The profile mode will print the flops/s for the op.
 'nvcc.fastmath':False,
+'scalar.floatX':'float64',
 }
 
 #default value taked from env variable
@@ -147,3 +148,5 @@ class TheanoConfig(object):
 
 config = TheanoConfig()
 
+if config.get('scalar.floatX') not in ['float32', 'float64']:
+    raise Exception("the configuration scalar.real must have value float32 or float64")

theano/sandbox/cuda/tests/test_bench_loopfusion.py

@@ -228,6 +228,11 @@ class Kouh2008(object):
 class Config(object):
     use_gpu = True
     dtype='float32'
+    dtype2=dtype
+    if dtype2=='floatX':
+        import theano.config as c
+        dtype2 = c.config.get('scalar.floatX')
+        
     rng_seed = 23498
 
     n_hid = 300
@@ -296,7 +301,7 @@ def test_bench_elemwise(n_iter=1000, **kwargs):
 
     xval = numpy.asarray(
         rng.uniform(size=(conf.ft_batchsize, x.type.shape[1])),
-        dtype=conf.dtype,
+        dtype=conf.dtype2,
         )
     yval = numpy.arange(conf.ft_batchsize)
     for i in xrange(n_iter):

theano/scalar/basic.py

@@ -56,6 +56,8 @@ def constant(x):
 class Scalar(Type):
 
     def __init__(self, dtype):
+        if dtype=='floatX':
+            dtype=config.config.get('floatX')
         self.dtype = dtype
         self.dtype_specs() # error checking
     
@@ -252,6 +254,7 @@ uint32 = Scalar('uint32')
 uint64 = Scalar('uint64')
 float32 = Scalar('float32')
 float64 = Scalar('float64')
+floatX = Scalar(config.config.get('scalar.floatX'))
 complex64 = Scalar('complex64')
 complex128 = Scalar('complex128')
 
@@ -934,6 +937,7 @@ convert_to_uint32 = Cast(uint32, name='convert_to_uint32')
 convert_to_uint64 = Cast(uint64, name='convert_to_uint64')
 convert_to_float32 = Cast(float32, name='convert_to_float32')
 convert_to_float64 = Cast(float64, name='convert_to_float64')
+convert_to_floatX = Cast(floatX, name='convert_to_floatX')
 convert_to_complex64 = Cast(complex64, name='convert_to_complex64')
 convert_to_complex128 = Cast(complex128, name='convert_to_complex128')
 
@@ -948,6 +952,7 @@ _cast_mapping = {
            'uint64': convert_to_uint64,
            'float32': convert_to_float32,
            'float64': convert_to_float64,
+           'floatX': convert_to_floatX,
            'complex64': convert_to_complex64,
            'complex128': convert_to_complex128}
 def cast(x, dtype):

theano/tensor/basic.py

@@ -282,6 +282,8 @@ class TensorType(Type):
            Optional name for this type.
         """
         self.dtype = str(dtype)
+        if self.dtype=='floatX':
+          self.dtype=config.config.get('scalar.floatX')
         self.broadcastable = tuple(broadcastable)
         self.dtype_specs() # error checking is done there
         self.name = name
@@ -608,6 +610,7 @@ cscalar = TensorType('complex64', ())
 zscalar = TensorType('complex128', ())
 fscalar = TensorType('float32', ())
 dscalar = TensorType('float64', ())
+xscalar = TensorType('floatX',())
 bscalar = TensorType('int8', ())
 wscalar = TensorType('int16', ())
 iscalar = TensorType('int32', ())
@@ -628,6 +631,7 @@ cvector = TensorType('complex64', (False, ))
 zvector = TensorType('complex128', (False, ))
 fvector = TensorType('float32', (False, ))
 dvector = TensorType('float64', (False, ))
+xvector = TensorType('floatX', (False, ))
 bvector = TensorType('int8', (False,))
 wvector = TensorType('int16', (False,))
 ivector = TensorType('int32', (False, ))
@@ -645,6 +649,7 @@ cmatrix = TensorType('complex64', (False, False))
 zmatrix = TensorType('complex128', (False, False))
 fmatrix = TensorType('float32', (False, False))
 dmatrix = TensorType('float64', (False, False))
+xmatrix = TensorType('floatX', (False, False))
 bmatrix = TensorType('int8', (False, False))
 wmatrix = TensorType('int16', (False, False))
 imatrix = TensorType('int32', (False, False))
@@ -662,6 +667,7 @@ crow = TensorType('complex64', (True, False))
 zrow = TensorType('complex128', (True, False))
 frow = TensorType('float32', (True, False))
 drow = TensorType('float64', (True, False))
+xrow = TensorType('floatX', (True, False))
 brow = TensorType('int8', (True, False))
 wrow = TensorType('int16', (True, False))
 irow = TensorType('int32', (True, False))
@@ -675,6 +681,7 @@ ccol = TensorType('complex64', (False, True))
 zcol = TensorType('complex128', (False, True))
 fcol = TensorType('float32', (False, True))
 dcol = TensorType('float64', (False, True))
+xcol = TensorType('floatX', (False, True))
 bcol = TensorType('int8', (False, True))
 wcol = TensorType('int16', (False, True))
 icol = TensorType('int32', (False, True))
@@ -688,6 +695,7 @@ ctensor3 = TensorType('complex64', (False,)*3)
 ztensor3 = TensorType('complex128', (False,)*3)
 ftensor3 = TensorType('float32', (False,)*3)
 dtensor3 = TensorType('float64', (False,)*3)
+xtensor3 = TensorType('floatX', (False,)*3)
 btensor3 = TensorType('int8', (False,)*3)
 wtensor3 = TensorType('int16', (False,)*3)
 itensor3 = TensorType('int32', (False,)*3)
@@ -697,6 +705,7 @@ ctensor4 = TensorType('complex64', (False,)*4)
 ztensor4 = TensorType('complex128', (False,)*4)
 ftensor4 = TensorType('float32', (False,)*4)
 dtensor4 = TensorType('float64', (False,)*4)
+xtensor4 = TensorType('floatX', (False,)*4)
 btensor4 = TensorType('int8', (False,)*4)
 wtensor4 = TensorType('int16', (False,)*4)
 itensor4 = TensorType('int32', (False,)*4)
@@ -1093,6 +1102,9 @@ _convert_to_float32 = _conversion(elemwise.Elemwise(scal.convert_to_float32), 'f
 _convert_to_float64 = _conversion(elemwise.Elemwise(scal.convert_to_float64), 'float64')
 """Cast to double-precision floating point"""
 
+_convert_to_floatX = _conversion(elemwise.Elemwise(scal.convert_to_floatX), 'floatX')
+"""Cast to floatX floating point"""
+
 _convert_to_complex64  = _conversion(elemwise.Elemwise(scal.convert_to_complex64), 'complex64')
 """Cast to single-precision complex"""
 
@@ -1110,6 +1122,7 @@ _cast_mapping = {
            'uint64': _convert_to_uint64,
            'float32': _convert_to_float32,
            'float64': _convert_to_float64,
+           'floatX': _convert_to_floatX,
            'complex64': _convert_to_complex64,
            'complex128': _convert_to_complex128}
 @constructor