numpy_call_dict_mkl = {
# assign
"assign":
_assign_right_to_left,
# zero_operand ops
# unary ops
"neg":
lambda left: math_cpu.neg(left),
"abs":
lambda left: np.abs(left),
"sgn":
lambda left: np.sign(left),
"sqrt":
lambda left: math_cpu.sqrt(left),
"sqr":
lambda left: math_cpu.square(left),
"exp":
lambda left: math_cpu.exp(left),
"log":
lambda left: math_cpu.log(left),
"safelog":
lambda left: math_cpu.safelog(left),
"exp2":
lambda left: np.exp2(left),
"log2":
lambda left: np.log2(left),
"sig":
lambda left: 1. / (1. + np.exp(-left)),
"sig2":
lambda left: 1. / (1. + np.exp2(-left)),
"tanh":
def _assign_right_to_left(left, right):
math_cpu.blas_copy(left, right)
# how to overlaod numpy_call_dict?
numpy_call_dict_mkl = {
# assign
"assign": _assign_right_to_left,
# zero_operand ops
# unary ops
"neg": lambda left: math_cpu.neg(left),
"abs": lambda left: np.abs(left),
"sgn": lambda left: np.sign(left),
"sqrt": lambda left: math_cpu.sqrt(left),
"sqr": lambda left: math_cpu.square(left),
"exp": lambda left: math_cpu.exp(left),
"log": lambda left: math_cpu.log(left),
"safelog": lambda left: math_cpu.safelog(left),
"exp2": lambda left: np.exp2(left),
"log2": lambda left: np.log2(left),
"sig": lambda left: 1. / (1. + np.exp(-left)),
"sig2": lambda left: 1. / (1. + np.exp2(-left)),
"tanh": lambda left: np.tanh(left),
"tanh2": lambda left: (np.exp2(2. * left) - 1.) / (np.exp2(2. * left) + 1.),
"transpose": lambda left: np.transpose(left),
"rint": lambda left: np.rint(left),
# binary ops
"add": lambda left, right: math_cpu.add(left, right),
"sub": lambda left, right: math_cpu.sub(left, right),
"mul": lambda left, right: math_cpu.mul(left, right),