def angle(cls, v1, v2, degrees=False):
if Tensor.match_shapes(v1, v2):
if degrees:
return LIB().v_angle(v1.pointer, v2.pointer, 1)
return LIB().v_angle(v1.pointer, v2.pointer, 0)
else:
raise ValueError("Vectors must have matching lengths")
def uniform(cls, low=0.0, high=1.0, shape=None):
pointer = None
if shape:
rank = len(shape)
c_data = rank * c_uint
pointer = LIB().uniform(rank, (c_data)(*shape), low, high)
else:
# TODO - change to scalar (now it's a vector)
pointer = LIB().uniform(1, (1 * c_uint)(1), low, high)
return cls(pointer=pointer)
def matmul(cls, a, b):
if a.shape[0] != b.shape[1]:
raise ValueError(
"The number of columns in the first matrix must be equal to the number of rows in the second matrix"
)
pointer = LIB().matmul(a.pointer, b.pointer)
return cls(pointer=pointer)
def add(cls, t1, t2):
if Tensor.match_shapes(t1, t2):
pointer = LIB().add(t1.pointer, t2.pointer)
return cls(pointer=pointer)
else:
raise ValueError("Tensors must have matching shapes")
def copy(self):
pointer = LIB().copy(self.pointer)
return Tensor(pointer=pointer)
def set(self, data):
data = _flatten(data)
c_data = c_double * len(data)
LIB().set(c_void_p(self.pointer), (c_data)(*data))
def from_shape(self, shape):
self.shape = shape
self.rank = len(shape)
self.pointer = LIB().init(self.rank, (c_int * self.rank)(*shape))
def det(self):
return LIB().det(self.pointer)
def sub(cls, v1, v2):
if Tensor.match_shapes(v1, v2):
pointer = LIB().v_sub(v1.pointer, v2.pointer)
return cls(pointer=pointer)
else:
raise ValueError("Vectors must have matching lengths")
def rotate(self, angle):
LIB().v_rotate(self.pointer, angle)
def random(cls, *shape):
rank = 1 if isinstance(shape, int) else len(shape)
c_data = c_int * rank
pointer = LIB().random(rank, (c_data)(*shape))
return cls(pointer=pointer)
def zeros(cls, *shape):
rank = 1 if isinstance(shape, int) else len(shape)
c_data = c_uint * rank
pointer = LIB().zeros(rank, (c_data)(*shape))
return cls(pointer=pointer)
def identity(cls, shape):
rank = len(shape)
c_data = c_int * rank
pointer = LIB().identity(rank, (c_data)(*shape))
return cls(pointer=pointer)
def transpose(self):
new_shape = LIB().T(self.pointer)
self.shape = [new_shape[i] for i in range(len(self.shape))]
return self
def mul(cls, t, scalar):
if isinstance(scalar, (int, float)):
pointer = LIB().mul(t.pointer, scalar)
return cls(pointer=pointer)
else:
raise TypeError(f"Can't multiply tensor with type {type(scalar)}")
def norm(self):
return LIB().v_norm(self.pointer)
def prod(cls, t):
return LIB().prod(t.pointer)
def dot(cls, v1, v2):
if Tensor.match_shapes(v1, v2):
return LIB().v_dot(v1.pointer, v2.pointer)
else:
raise ValueError("Vectors must have matching lengths")
def sqrt(cls, t):
return LIB().sqrt(t.pointer)
def __del__(self):
try:
LIB().destory(self.pointer)
except AttributeError:
return
def trace(self):
return LIB().trace(self.pointer)