def construct(symbol):
symbolname = symbol.__name__
inplace = symbolname.endswith('_inplace')
if inplace:
msg = "inplace"
else:
msg = "no_inplace"
n = "Elemwise{%s,%s}" % (symbolname, msg)
if inplace:
scalar_op = getattr(scal, symbolname[:-len('_inplace')])
inplace_scalar_op = scalar_op.__class__(scal.transfer_type(0))
rval = elemwise.Elemwise(inplace_scalar_op, {0: 0},
name=n,
nfunc_spec=(nfunc and (nfunc, nin, nout)))
else:
scalar_op = getattr(scal, symbolname)
rval = elemwise.Elemwise(scalar_op,
name=n,
nfunc_spec=(nfunc and (nfunc, nin, nout)))
if getattr(symbol, '__doc__', False):
rval.__doc__ = symbol.__doc__ + '\n' + rval.__doc__
# for the meaning of this see the ./epydoc script
# it makes epydoc display rval as if it were a function, not an object
rval.__epydoc_asRoutine = symbol
rval.__module__ = 'tensor'
pprint.assign(rval, printing.FunctionPrinter(symbolname))
return rval
def construct_elemwise(name, doc_str, scalar_op):
n = "Elemwise{%s, no_inplace}" % (name, )
rval = elemwise.Elemwise(scalar_op,
name=n,
nfunc_spec=(None and (None, None, None)))
rval.__doc__ = doc_str + '\n' + rval.__doc__
rval.__module__ = 'tensor'
return rval
os.path.dirname(theano.__file__),
"..",
"doc",
"library",
"tensor",
"nnet",
"sigmoid_prec.png",
)
plt.savefig(fname)
print("New picture saved at", fname)
print(val_ultra.max())
print(val_ultra.min())
scalar_sigmoid = ScalarSigmoid(scalar.upgrade_to_float, name="scalar_sigmoid")
sigmoid = elemwise.Elemwise(scalar_sigmoid, name="sigmoid")
sigmoid_inplace = elemwise.Elemwise(
ScalarSigmoid(scalar.transfer_type(0)),
inplace_pattern={0: 0},
name="sigmoid_inplace",
)
pprint.assign(sigmoid, printing.FunctionPrinter("sigmoid"))
class UltraFastScalarSigmoid(scalar.UnaryScalarOp):
"""
This is just speed opt. Not for stability.
"""
def grad(self, (x, ), (gz, )):
if x.type in complex_types:
raise NotImplementedError()
elif x.type in float_types:
return gz * 2. / numpy.sqrt(numpy.pi) * exp(-x * x),
else:
return None,
def c_code(self, node, name, (x, ), (z, ), sub):
if node.inputs[0].type in complex_types:
raise NotImplementedError('type not supported', type)
return "%(z)s = erf(%(x)s);" % locals()
erf = elemwise.Elemwise(Erf(upgrade_to_float, name='Terf'))
class Erfc(UnaryScalarOp):
def impl(self, x):
return scipy.special.erfc(x)
def grad(self, (x, ), (gz, )):
if x.type in complex_types:
raise NotImplementedError()
elif x.type in float_types:
return -gz * 2. / numpy.sqrt(numpy.pi) * exp(-x * x),
else:
return None,
def c_code(self, node, name, (x, ), (z, ), sub):
elif node.inputs[0].type == scalar.float64:
return """%(z)s = %(x)s < -709.0 ? 0.0 : %(x)s > 19.0 ? 1.0 : 1.0 /(1.0+exp(-%(x)s));""" % locals(
)
else:
raise NotImplementedError('only floatingpoint is implemented')
def c_code_cache_version(self):
v = super(ScalarSigmoid, self).c_code_cache_version()
if v:
return (2, ) + v
else:
return v
scalar_sigmoid = ScalarSigmoid(scalar.upgrade_to_float, name='scalar_sigmoid')
sigmoid = elemwise.Elemwise(scalar_sigmoid, name='sigmoid')
sigmoid_inplace = elemwise.Elemwise(
ScalarSigmoid(scalar.transfer_type(0)),
inplace_pattern={0: 0},
name='sigmoid_inplace',
)
pprint.assign(sigmoid, printing.FunctionPrinter('sigmoid'))
class ScalarSoftplus(scalar.UnaryScalarOp):
@staticmethod
def static_impl(x):
if x < -30.0:
return 0.0
return [x > 0.0]
def c_code(self, node, name, (x,), (z,), sub):
"""
.. todo::
WRITEME
"""
if node.inputs[0].type == scalar.float32:
return """%(z)s = %(x)s < 0.0f ? 0.0 : %(x)s;""" % locals()
elif node.inputs[0].type == scalar.float64:
return """%(z)s = %(x)s < 0.0 ? 0.0 : %(x)s;""" % locals()
else:
raise NotImplementedError('only floatingpoint is implemented')
def c_code_cache_version(self):
"""
.. todo::
WRITEME
"""
v = super(ScalarRectifier, self).c_code_cache_version()
if v:
return (2,) + v
else:
return v
scalar_rectifier = ScalarRectifier(scalar.upgrade_to_float,
name='scalar_rectifier')
rectifier = elemwise.Elemwise(scalar_rectifier, name='rectifier')
