def make_node(self, x, v, sorter=None):
x = basic.as_tensor(x, ndim=1)
v = basic.as_tensor(v)
out_type = v.type.clone(dtype='int64')
if sorter is None:
return theano.Apply(self, [x, v], [out_type()])
else:
sorter = basic.as_tensor(sorter, ndim=1)
if sorter.type not in basic.int_vector_types:
raise TypeError('sorter must be an integer vector',
sorter.type)
return theano.Apply(self, [x, v, sorter], [out_type()])
def make_node(self, x, v, sorter=None):
x = basic.as_tensor(x, ndim=1)
v = basic.as_tensor(v)
out_type = v.type.clone(dtype='int64')
if sorter is None:
return theano.Apply(self, [x, v], [out_type()])
else:
sorter = basic.as_tensor(sorter, ndim=1)
if sorter.type not in basic.int_vector_types:
raise TypeError('sorter must be an integer vector',
sorter.type)
return theano.Apply(self, [x, v, sorter], [out_type()])
def make_node(self, x, v, sorter=None):
x = basic.as_tensor(x, ndim=1)
v = basic.as_tensor(v)
out_type = v.type.clone(dtype="int64")
if sorter is None:
return theano.Apply(self, [x, v], [out_type()])
else:
sorter = basic.as_tensor(sorter, ndim=1)
if theano.configdefaults.python_int_bitwidth() == 32 and sorter.dtype == "int64":
raise TypeError("numpy.searchsorted with Python 32bit do not support a" " sorter of int64.")
if sorter.type not in basic.int_vector_types:
raise TypeError("sorter must be an integer vector", sorter.type)
return theano.Apply(self, [x, v, sorter], [out_type()])
def make_node(self, x, v, sorter=None):
x = basic.as_tensor(x, ndim=1)
v = basic.as_tensor(v)
out_type = v.type.clone(dtype="int64")
if sorter is None:
return theano.Apply(self, [x, v], [out_type()])
else:
sorter = basic.as_tensor(sorter, ndim=1)
if PYTHON_INT_BITWIDTH == 32 and sorter.dtype == "int64":
raise TypeError(
"numpy.searchsorted with Python 32bit do not support a"
" sorter of int64.")
if sorter.type not in basic.int_vector_types:
raise TypeError("sorter must be an integer vector",
sorter.type)
return theano.Apply(self, [x, v, sorter], [out_type()])
def make_node(self, x, v, sorter=None):
x = basic.as_tensor(x, ndim=1)
v = basic.as_tensor(v)
out_type = v.type.clone(dtype='int64')
if sorter is None:
return theano.Apply(self, [x, v], [out_type()])
else:
sorter = basic.as_tensor(sorter, ndim=1)
if (theano.configdefaults.python_int_bitwidth() == 32 and
sorter.dtype == 'int64'):
raise TypeError(
"numpy.searchsorted with Python 32bit do not support a"
" sorter of int64.")
if sorter.type not in basic.int_vector_types:
raise TypeError('sorter must be an integer vector',
sorter.type)
return theano.Apply(self, [x, v, sorter], [out_type()])