def setup(self):
a = np.arange(4)
vec = self.declare_input('a', val=a)
self.register_output(
'einsum_summ1_sparse_derivs',
ot.einsum(vec, subscripts='i->', partial_format='sparse'))
def setup(self):
a = np.arange(4)
vec = self.declare_input('a', val=a)
# Outer Product of 2 vectors
self.register_output('einsum_outer1',
ot.einsum(vec, vec, subscripts='i,j->ij'))
def setup(self):
shape2 = (5, 4)
b = np.arange(20).reshape(shape2)
mat = self.declare_input('b', val=b)
# Transpose of a matrix
self.register_output('einsum_reorder1',
ot.einsum(mat, subscripts='ij->ji'))
def setup(self):
a = np.arange(4)
vec = self.declare_input('a', val=a)
# Summation of all the entries of a vector
self.register_output('einsum_summ1', ot.einsum(
vec,
subscripts='i->',
))
def setup(self):
a = np.arange(4)
vec = self.declare_input('a', val=a)
# Special operation: sum all the entries of the first and second
# vector to a single scalar
self.register_output('einsum_special2',
ot.einsum(vec, vec, subscripts='i,j->'))
def setup(self):
a = np.arange(4)
vec = self.declare_input('a', val=a)
# Special operation: summation of all the entries of first
# vector and scalar multiply the second vector with the computed
# sum
self.register_output('einsum_special1',
ot.einsum(vec, vec, subscripts='i,j->j'))
def setup(self):
# Shape of Tensor
shape3 = (2, 4, 3)
c = np.arange(24).reshape(shape3)
# Declaring tensor
tens = self.declare_input('c', val=c)
# Transpose of a tensor
self.register_output('einsum_reorder2',
ot.einsum(tens, subscripts='ijk->kji'))
def setup(self):
shape2 = (5, 4)
b = np.arange(20).reshape(shape2)
mat = self.declare_input('b', val=b)
self.register_output(
'einsum_reorder1_sparse_derivs',
ot.einsum(
mat,
subscripts='ij->ji',
partial_format='sparse',
))
def setup(self):
# Shape of Tensor
shape3 = (2, 4, 3)
c = np.arange(24).reshape(shape3)
# Declaring tensor
tens = self.declare_input('c', val=c)
# Summation of all the entries of a tensor
self.register_output('einsum_summ2',
ot.einsum(
tens,
subscripts='ijk->',
))
def setup(self):
# Shape of Tensor
shape3 = (2, 4, 3)
c = np.arange(24).reshape(shape3)
# Declaring tensor
tens = self.declare_input('c', val=c)
self.register_output(
'einsum_summ2_sparse_derivs',
ot.einsum(
tens,
subscripts='ijk->',
partial_format='sparse',
))
def setup(self):
a = np.arange(4)
vec = self.declare_input('a', val=a)
# Shape of Tensor
shape3 = (2, 4, 3)
c = np.arange(24).reshape(shape3)
# Declaring tensor
tens = self.declare_input('c', val=c)
# Outer Product of a tensor and a vector
self.register_output('einsum_outer2',
ot.einsum(
tens,
vec,
subscripts='hij,k->hijk',
))
def setup(self):
a = np.arange(4)
vec = self.declare_input('a', val=a)
# Shape of Tensor
shape3 = (2, 4, 3)
c = np.arange(24).reshape(shape3)
# Declaring tensor
tens = self.declare_input('c', val=c)
self.register_output(
'einsum_outer2_sparse_derivs',
ot.einsum(tens,
vec,
subscripts='hij,k->hijk',
partial_format='sparse'))
