def _compute_type(self):
assert len(self.shape) == 2
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(self.shape[0], self.shape[1])
self._type = tblockmatrix(self.child.typ.element_type,
tensor_shape,
is_row_vector,
self.block_size)
def _compute_type(self):
assert len(self.shape) == 2
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(
self.shape[0], self.shape[1])
self._type = tblockmatrix(self.child.typ.element_type, tensor_shape,
is_row_vector, self.block_size,
self.dims_partitioned)
def _compute_type(self):
assert len(self.shape) == 2
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(
self.shape[0], self.shape[1])
self._type = tblockmatrix(hl.tfloat64, tensor_shape, is_row_vector,
self.block_size)
def _compute_type(self):
shape = [self.child.typ.shape[i] for i in self.out_index_expr]
is_row_vector = self.out_index_expr == [1]
self._type = tblockmatrix(self.child.typ.element_type,
shape,
is_row_vector,
self.child.typ.block_size)
def _compute_type(self):
assert len(self.slices) == 2
matrix_shape = [1 + (s.stop - s.start - 1) // s.step for s in self.slices]
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(matrix_shape[0], matrix_shape[1])
self._type = tblockmatrix(self.child.typ.element_type,
tensor_shape,
is_row_vector,
self.child.typ.block_size)
def _compute_type(self):
shape = [self.child.typ.shape[i] for i in self.out_index_expr]
is_row_vector = self.out_index_expr == [1]
self._type = tblockmatrix(self.child.typ.element_type,
shape,
is_row_vector,
self.child.typ.block_size)
def _compute_type(self):
child_type = self.child.typ
if isinstance(child_type, tarray):
element_type = child_type._element_type
else:
element_type = child_type
self._type = tblockmatrix(element_type, self.shape, self.block_size,
self.dims_partitioned)
def _compute_type(self):
l_rows, l_cols = tensor_shape_to_matrix_shape(self.left)
r_rows, r_cols = tensor_shape_to_matrix_shape(self.right)
assert l_cols == r_rows
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(
l_rows, r_cols)
self._type = tblockmatrix(self.left.typ.element_type, tensor_shape,
is_row_vector, self.left.typ.block_size)
def _compute_type(self):
child_type = self.child.typ
if isinstance(child_type, tarray):
element_type = child_type._element_type
else:
element_type = child_type
assert len(self.shape) == 2
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(self.shape[0], self.shape[1])
self._type = tblockmatrix(element_type, tensor_shape, is_row_vector, self.block_size)
def _compute_type(self):
child_type = self.child.typ
if isinstance(child_type, tarray):
element_type = child_type._element_type
else:
element_type = child_type
assert len(self.shape) == 2
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(self.shape[0], self.shape[1])
self._type = tblockmatrix(element_type, tensor_shape, is_row_vector, self.block_size)
def _compute_type(self):
assert len(self.indices_to_keep) == 2
shape = [len(idxs) if len(idxs) != 0 else self.child.typ.shape[i] for i, idxs in
enumerate(self.indices_to_keep)]
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(shape[0], shape[1])
self._type = tblockmatrix(self.child.typ.element_type,
tensor_shape,
is_row_vector,
self.child.typ.block_size)
def _compute_type(self):
assert len(self.indices_to_keep) == 2
shape = [len(idxs) if len(idxs) != 0 else self.child.typ.shape[i] for i, idxs in
enumerate(self.indices_to_keep)]
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(shape[0], shape[1])
self._type = tblockmatrix(self.child.typ.element_type,
tensor_shape,
is_row_vector,
self.child.typ.block_size)
def _compute_type(self):
l_rows, l_cols = tensor_shape_to_matrix_shape(self.left)
r_rows, r_cols = tensor_shape_to_matrix_shape(self.right)
assert l_cols == r_rows
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(l_rows, r_cols)
self._type = tblockmatrix(self.left.typ.element_type,
tensor_shape,
is_row_vector,
self.left.typ.block_size)
def _compute_type(self):
child_matrix_shape = tensor_shape_to_matrix_shape(self.child)
if self.out_index_expr == [0, 1]:
is_row_vector = False
shape = []
elif self.out_index_expr == [0]:
is_row_vector = True
shape = [child_matrix_shape[1]]
elif self.out_index_expr == [1]:
is_row_vector = False
shape = [child_matrix_shape[0]]
else:
raise ValueError("Invalid out_index_expr")
self._type = tblockmatrix(self.child.typ.element_type, shape,
is_row_vector, self.child.typ.block_size)
def _compute_type(self):
assert len(self.indices_to_keep) == 2
child_tensor_shape = self.child.typ.shape
child_ndim = len(child_tensor_shape)
if child_ndim == 1:
if self.child.typ.is_row_vector:
child_matrix_shape = [1, child_tensor_shape[0]]
else:
child_matrix_shape = [child_tensor_shape[0], 1]
else:
child_matrix_shape = child_tensor_shape
matrix_shape = [len(idxs) if len(idxs) != 0 else child_matrix_shape[i] for i, idxs in
enumerate(self.indices_to_keep)]
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(matrix_shape[0], matrix_shape[1])
self._type = tblockmatrix(self.child.typ.element_type,
tensor_shape,
is_row_vector,
self.child.typ.block_size)
def _compute_type(self):
self._type = tblockmatrix(self.child.typ.element_type, self.shape,
self.block_size, self.dims_partitioned)
def _compute_type(self):
assert len(self.shape) == 2
tensor_shape, is_row_vector = _matrix_shape_to_tensor_shape(self.shape[0], self.shape[1])
self._type = tblockmatrix(hl.tfloat64, tensor_shape, is_row_vector, self.block_size)
