new version of floatX to allow to test both floatX=float{32,64} at the same time.

doc/basic_tutorial/floatX.txt

+.. _floatX:
+
+========================
+Special data type floatX
+========================
+
+Intro
+=====
+
+Their is a special data type called floatX. It is not a real datatype. It is never present in the theano graph, but their exist constructor and function that will change the floatX to float32 or float64(default) in your graph. You can change the value of floatX when you start the execution of python by setting the environement variables THEANO_GPU=floatX=float{32,64}(case sensitive). You can have the value of floatX with:
+
+import theano.config as config
+config.floatX
+
+This can help to have the same code run on the cpu in float64 and let it run on the gpu in float32. float32 is the only datatype that is currently supported on the gpu. This can give different result due to rounding error. This option help to compare those difference.
+
+Also, on the cpu, float32 are twice as fast as float64.
+
+Their exist helper function in theano.floatx that simplify using this 
+Here is the list of fonction that create/accept tensor of floatX. They are all variant of function that already exist for other datatype.
+theano.scalar.Scalar.__init__(dtype)
+theano.scalar.floatX
+theano.floatx.xscalar
+theano.floatx.xvector
+theano.floatx.xmatrix
+theano.floatx.xrow
+theano.floatx.xcol
+theano.floatx.xtensor3
+theano.floatx.xtensor4
+theano.tensor.cast(TensorVariable, dtype)
+TensorType.__init__(dtype, broadcastable, name = None, shape=None)
+
+HINT: linear algorythm are less affected by the different precision then non-linear one.
+      use numpy.asarray(x,dtype=config.floatX) to cast numpy array to floatX
+      numpy.asarray(x,dtype=config.floatX) warn copy only if needed.
+
+WARNING: theano.floatx.set_floatX() exist for our test. Don't use it for something else. If you do, it will make code hard to read and it is a sign that their is something better for you then floatX.

doc/basic_tutorial/index.txt

@@ -32,3 +32,4 @@ Now we're ready for the tour:
    examples
    module
    tools
+   floatX

theano/__init__.py

@@ -59,7 +59,8 @@ import scalar
 import sparse
 import gradient
 import gof
-
+import floatx
+floatx.set_floatX()
 
 ## import scalar_opt
 

theano/config.py

@@ -10,7 +10,6 @@ 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',
 'gpuelemwise.sync':True, #when true, wait that the gpu fct finished and check it error code.
 }
 
@@ -44,6 +43,24 @@ THEANO_DEBUGMODE_CHECK_STRIDES = bool(int(os.getenv('THEANO_DEBUGMODE_CHECK_STRI
 
 THEANO_FLAGS=os.getenv("THEANO_FLAGS","")
 
+def parse_env_flags(flags, name , default_value=None):
+    #The value in the env variable THEANO_FLAGS override the previous value
+    import pdb;pdb.set_trace()
+    val = default_value
+    for flag in flags.split(','):
+        if not flag:
+            continue
+        sp=flag.split('=',1)
+        if sp[0]==name:
+            if len(sp)==1:
+                val=True
+            else:
+                val=sp[1]
+            val=str(val)
+    return val
+
+floatX=parse_env_flags(THEANO_FLAGS,'floatX','float64')
+
 class TheanoConfig(object):
     """Return the value for a key after parsing ~/.theano.cfg and 
     the THEANO_FLAGS environment variable.
@@ -149,5 +166,6 @@ class TheanoConfig(object):
 
 config = TheanoConfig()
 
-if config.get('scalar.floatX') not in ['float32', 'float64']:
-    raise Exception("the configuration scalar.floatX must have value float32 or float64")
+if floatX not in ['float32', 'float64']:
+    raise Exception("the configuration scalar.floatX must have value float32 or float64 not", floatX)
+

theano/floatx.py

+import theano.config as config
+from theano.scalar import float32, float64
+from theano.tensor import fscalar, fvector, fmatrix, frow, fcol, ftensor3, ftensor4, dscalar, dvector, dmatrix, drow, dcol, dtensor3, dtensor4
+
+def set_floatX(dtype = config.floatX):
+  """ add the xmatrix, xvector, xscalar etc. aliases to theano.tensor
+  """
+  print "set_floatX",dtype
+  config.floatX = dtype
+  import pdb;pdb.set_trace()
+  if dtype == 'float32': prefix = 'f'
+  elif dtype == 'float64' : prefix = 'd'
+  else: raise Exception("Bad param in set_floatX(%s). Only float32 and float64 are supported"%config.floatX)
+
+  #tensor.scalar stuff
+  globals()['floatX'] = globals()[dtype]
+#  convert_to_floatX = Cast(floatX, name='convert_to_floatX')
+
+
+  #tensor.tensor stuff
+  for symbol in ('scalar', 'vector', 'matrix', 'row', 'col','tensor3','tensor4'):
+     globals()['x'+symbol] = globals()[prefix+symbol]
+  #_convert_to_floatX = _conversion(elemwise.Elemwise(scal.convert_to_floatX), 'floatX')
+  
+
+
+
+

theano/scalar/basic.py

@@ -56,8 +56,8 @@ def constant(x):
 class Scalar(Type):
 
     def __init__(self, dtype):
-        if dtype=='floatX':
-            dtype=config.config.get('floatX')
+        if dtype == 'floatX':
+            dtype = config.floatX
         self.dtype = dtype
         self.dtype_specs() # error checking
     
@@ -261,7 +261,6 @@ 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')
 
@@ -944,7 +943,6 @@ 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')
 
@@ -959,12 +957,11 @@ _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):
     """Symbolically cast `x` to a Scalar of given `dtype`.""" 
-    if dtype=='floatX': dtype = config.config.get('scalar.floatX')
+    if dtype == 'floatX': dtype = config.floatX
 
     _x = as_scalar(x)
     if _x.type.dtype == dtype:

theano/tensor/basic.py

@@ -283,7 +283,7 @@ class TensorType(Type):
         """
         self.dtype = str(dtype)
         if self.dtype=='floatX':
-          self.dtype=config.config.get('scalar.floatX')
+          self.dtype=config.floatX
         self.broadcastable = tuple(broadcastable)
         self.dtype_specs() # error checking is done there
         self.name = name
@@ -610,7 +610,6 @@ cscalar = TensorType('complex64', ())
 zscalar = TensorType('complex128', ())
 fscalar = TensorType('float32', ())
 dscalar = TensorType('float64', ())
-xscalar = TensorType('floatX',())
 bscalar = TensorType('int8', ())
 wscalar = TensorType('int16', ())
 iscalar = TensorType('int32', ())
@@ -631,7 +630,6 @@ 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, ))
@@ -649,7 +647,6 @@ 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))
@@ -667,7 +664,6 @@ 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))
@@ -681,7 +677,6 @@ 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))
@@ -695,7 +690,6 @@ 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)
@@ -705,7 +699,6 @@ 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)
@@ -1102,9 +1095,6 @@ _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"""
 
@@ -1122,13 +1112,12 @@ _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
 def cast(x, dtype):
     """Symbolically cast `x` to a Tensor of type `dtype`.""" 
-    if dtype=='floatX': dtype = config.config.get('scalar.floatX')
+    if dtype=='floatX': dtype = config.floatX
     
     _x = as_tensor_variable(x)
     if _x.type.dtype == dtype:

theano/tensor/tests/test_basic.py

@@ -2218,63 +2218,6 @@ def test_default_state():
     assert f(1) == 4.8
     assert f(2.2) == 7
 
-def test_cast_floatX():
-    floatx=config.config.get('scalar.floatX')
-
-    #float64 cast to float64 should not generate an op
-    x = dvector('x')
-    f = function([x],[cast(x,'float64')])
-#    print f.maker.env.toposort()
-    assert len(f.maker.env.toposort())==0
-
-    #float32 cast to float32 should not generate an op
-    x = fvector('x')
-    f = function([x],[cast(x,'float32')])
-#    print f.maker.env.toposort()
-    assert len(f.maker.env.toposort())==0
-
-    #floatX cast to float64
-    x = xvector('x')
-    f = function([x],[cast(x,'float64')])
-#    print f.maker.env.toposort()
-    if floatx=='float64':
-        assert len(f.maker.env.toposort()) == 0 
-    else:
-        assert len(f.maker.env.toposort()) == 1
-
-    #floatX cast to float32
-    x = xvector('x')
-    f = function([x],[cast(x,'float32')])
-#    print f.maker.env.toposort()
-    if floatx=='float32':
-        assert len(f.maker.env.toposort()) == 0 
-    else:
-        assert len(f.maker.env.toposort()) == 1
-
-    #float64 cast to floatX
-    x = dvector('x')
-    f = function([x],[cast(x,'floatX')])
-#    print f.maker.env.toposort()
-    if floatx=='float64':
-        assert len(f.maker.env.toposort()) == 0 
-    else:
-        assert len(f.maker.env.toposort()) == 1
-
-    #float32 cast to floatX
-    x = fvector('x')
-    f = function([x],[cast(x,'floatX')])
-#    print f.maker.env.toposort()
-    if floatx=='float32':
-        assert len(f.maker.env.toposort()) == 0 
-    else:
-        assert len(f.maker.env.toposort()) == 1
-
-    #floatX cast to floatX
-    x = xvector('x')
-    f = function([x],[cast(x,'floatX')])
-#    print f.maker.env.toposort()
-    assert len(f.maker.env.toposort()) == 0 
-
 if __name__ == '__main__':
     if len(sys.argv) >= 2 and sys.argv[1] == 'OPT':
         default_mode = compile.Mode(linker = 'c&py',

theano/tests/test_floatx.py

+from theano.tensor import *
+import theano.config as config
+from theano import function
+#from theano.floatx import set_floatX, xscalar, xmatrix, xrow, xcol, xvector, xtensor3, xtensor4
+import theano.floatx as FX
+
+def test_floatX():
+    def test():
+        floatx=config.floatX
+    #TODO test other fct then ?vector
+
+    #float64 cast to float64 should not generate an op
+        x = dvector('x')
+        f = function([x],[cast(x,'float64')])
+    #    print f.maker.env.toposort()
+        assert len(f.maker.env.toposort())==0
+
+    #float32 cast to float32 should not generate an op
+        x = fvector('x')
+        f = function([x],[cast(x,'float32')])
+    #    print f.maker.env.toposort()
+        assert len(f.maker.env.toposort())==0
+
+    #floatX cast to float64
+        x = FX.xvector('x')
+        f = function([x],[cast(x,'float64')])
+    #    print f.maker.env.toposort()
+        if floatx=='float64':
+            assert len(f.maker.env.toposort()) == 0 
+        else:
+            assert len(f.maker.env.toposort()) == 1
+
+    #floatX cast to float32
+        x = FX.xvector('x')
+        f = function([x],[cast(x,'float32')])
+    #    print f.maker.env.toposort()
+        if floatx=='float32':
+            assert len(f.maker.env.toposort()) == 0 
+        else:
+            assert len(f.maker.env.toposort()) == 1
+
+    #float64 cast to floatX
+        x = dvector('x')
+        f = function([x],[cast(x,'floatX')])
+    #    print f.maker.env.toposort()
+        if floatx=='float64':
+            assert len(f.maker.env.toposort()) == 0 
+        else:
+            assert len(f.maker.env.toposort()) == 1
+
+    #float32 cast to floatX
+        x = fvector('x')
+        f = function([x],[cast(x,'floatX')])
+    #    print f.maker.env.toposort()
+        if floatx=='float32':
+            assert len(f.maker.env.toposort()) == 0 
+        else:
+            assert len(f.maker.env.toposort()) == 1
+            
+    #floatX cast to floatX
+        x = FX.xvector('x')
+        f = function([x],[cast(x,'floatX')])
+    #    print f.maker.env.toposort()
+        assert len(f.maker.env.toposort()) == 0 
+
+    orig_floatx = config.floatX
+    try:
+        print 'float32'
+        FX.set_floatX('float32')
+        test()
+        print 'float64'
+        FX.set_floatX('float64')
+        test()
+    finally:
+        pass
+        FX.set_floatX(orig_floatx)