# Copyright 2019 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """operator dsl function: sqrt""" import akg.tvm import akg.topi from akg.utils import validation_check as vc_util from akg.utils import kernel_exec as utils def sqrt(data): """ Computes square root of x element-wise. \f[ y = \\sqrt x = x^{\\frac{1}{2}} \f] Note: In order to prevent loss of precision, the function uses exponential constant changes: \f[ y = [e^{lnx}]^{\\frac{1}{2}} \f] Args: data (tvm.tensor.Tensor): Tensor of type float16, float32. Returns: tvm.tensor.Tensor, has same type and shape as data. """ check_list = ["float16", "float32"] dtype = data.dtype if not dtype in check_list: raise RuntimeError("Sqrt cce only support %s while dtype is %s" % (",".join(check_list), dtype)) vc_util.check_shape(data.shape) if not utils.product_is_mini(): return akg.topi.sqrt(data) is_needed_conv = (dtype == 'float32') data = data.astype('float16') if is_needed_conv else data power_num = akg.tvm.const(0.5, dtype=('float16' if is_needed_conv else dtype)) shape = data.shape vlog_t = akg.tvm.compute(shape, lambda *indice: akg.tvm.log(data(*indice)), name="vlog_t") vmuls_t = akg.tvm.compute(shape, lambda *indice: vlog_t(*indice) * power_num, name="vmuls_t") res = akg.tvm.compute(shape, lambda *indice: akg.tvm.exp(vmuls_t(*indice)), name="res") res = res.astype('float32') if is_needed_conv else res return res