def set_shape(self):
# Override.
num_unique_words = self._metadata["num_unique_words"]
self._shape = utilities.Shape(num_unique_words, 1)
doc_idx = str(self._metadata["doc_idx"])
self._name = "w_" + doc_idx
def init_dcp_attr(self):
shape = u.Shape(*intf.size(self.value))
# If scalar, check sign. Else unknown sign.
if shape.size == (1, 1):
sign = u.Sign.val_to_sign(self.value)
else:
sign = u.Sign.UNKNOWN
self._dcp_attr = u.DCPAttr(sign, u.Curvature.CONSTANT, shape)
def init_dcp_attr(self):
"""Determines the curvature, sign, and shape from the arguments.
"""
sign = self.args[0].objective.args[0]._dcp_attr.sign
if isinstance(self.args[0].objective, Minimize):
curvature = u.curvature.Curvature.CONVEX
elif isinstance(self.args[0].objective, Maximize):
curvature = u.curvature.Curvature.CONCAVE
else:
raise Exception(
("You called partial_optimize with a Problem object that "
"contains neither a Minimize nor a Maximize statement; "
"this is not supported."))
self._dcp_attr = u.DCPAttr(sign, curvature, u.Shape(1, 1))
def set_shape(self):
shape = ()
if self.has_val_map():
val = self._val_map.values()[0]
if isinstance(val, int) or isinstance(val, float):
shape = (1,1)
elif isinstance(val, numpy.ndarray):
numpy_shape = val.shape
if len(numpy_shape) == 1:
shape = (numpy_shape[0], 1)
elif len(numpy_shape) == 2:
shape = (numpy_shape[0], numpy_shape[1])
else:
raise Exception(strings.BAD_RV_DIMS)
else:
raise Exception(strings.BAD_VAL_MAP)
else:
pymc_shape = ()
if isinstance(self._rv, pymc.CompletedDirichlet):
pymc_shape = self._rv.parents["D"].shape
else:
pymc_shape = self._rv.shape
if len(pymc_shape) == 0:
shape = (1,1)
elif len(pymc_shape) == 1:
shape = (pymc_shape[0], 1)
elif len(pymc_shape) == 2:
shape = (pymc_shape[0], pymc_shape[1])
else:
raise Exception(strings.BAD_RV_DIMS)
self._shape = utilities.Shape(*shape)
def shape_from_args(self):
"""Returns the shape of the transpose expression.
"""
rows, cols = self.args[0].size
return u.Shape(cols, rows)
def shape_from_args(self):
"""The sum of the argument dimensions - 1.
"""
lh_length = self.args[0].size[0]
rh_length = self.args[1].size[0]
return u.Shape(lh_length + rh_length - 1, 1)
def shape_from_args(self):
"""Always scalar.
"""
return u.Shape(1, 1)
def shape_from_args(self):
"""The sum of the argument dimensions - 1.
"""
rows = self.args[0].size[0] * self.args[1].size[0]
cols = self.args[0].size[1] * self.args[1].size[1]
return u.Shape(rows, cols)
def init_dcp_attr(self):
shape = u.Shape(self._rows, self._cols)
sign = u.Sign(self.sign_str)
self._dcp_attr = u.DCPAttr(sign, u.Curvature.CONSTANT, shape)
def shape_from_args(self):
"""A square matrix.
"""
rows, _ = self.args[0].size
return u.Shape(rows, rows)
def shape_from_args(self):
"""A column vector.
"""
rows, _ = self.args[0].size
return u.Shape(rows, 1)
def shape_from_args(self):
"""Returns the shape of the index expression.
"""
return u.Shape(*ku.size(self.key, self.args[0]._dcp_attr.shape))
def shape_from_args(self):
cols = sum(arg.size[1] for arg in self.args)
rows = self.args[0].size[0]
return u.Shape(rows, cols)
def init_dcp_attr(self):
"""Override.
"""
self._dcp_attr = utils.DCPAttr(utils.Sign.POSITIVE,
utils.Curvature.AFFINE,
utils.Shape(self._rows, self._cols))
def init_dcp_attr(self):
shape = u.Shape(*intf.size(self.value))
sign = intf.sign(self.value)
self._dcp_attr = u.DCPAttr(sign, u.Curvature.CONSTANT, shape)
def shape_from_args(self):
return u.Shape(1, 1)
def shape_from_args(self):
"""Resolves to a scalar.
"""
return u.Shape(1, 1)
def shape_from_args(self):
"""A vector.
"""
rows, cols = self.args[0].size
return u.Shape(rows * (cols - 1) // 2, 1)
def shape_from_args(self):
"""Returns the shape from the rows, cols arguments.
"""
return u.Shape(self.rows, self.cols)
def shape_from_args(self):
"""The sum of the argument dimensions - 1.
"""
return u.Shape(self.args[0].size[0] + self.args[1].size[0] - 1,
self.args[0].size[1] + self.args[1].size[1] - 1)
