blob: e5bc88b875f14d79ffe2d5fbedcf4b673735439a [file] [log] [blame]
# Copyright (C) 2020 Arm Limited or its affiliates. All rights reserved.
#
# SPDX-License-Identifier: Apache-2.0
#
# 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
#
# 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.
# Description:
# Numerical utilities for various types of rounding etc.
import math
import numpy as np
def round_up(a, b):
return ((a + b - 1) // b) * b
def round_up_divide(a, b):
return (a + b - 1) // b
def round_up_to_int(v):
return int(math.ceil(v))
def round_down_to_power_of_two(v):
assert v > 0
while v & (v - 1):
v &= v - 1
return v
def round_up_to_power_of_two(v):
return round_down_to_power_of_two(2 * v - 1)
def round_down_log2(v):
return int(math.floor(np.log2(v)))
def round_up_log2(v):
return int(math.ceil(np.log2(v)))
def round_to_int(v):
return np.rint(v).astype(np.int64)
# Performs rounding away from zero.
# n.b. This is identical to C++11 std::round()
def round_away_zero(f):
r = -0.5 if (f < 0) else 0.5
return np.trunc(f + r)
def quantise_float32(f, scale=1.0, zero_point=0):
return zero_point + int(round_away_zero(np.float32(f) / np.float32(scale)))
def clamp_tanh(x):
if x <= -4:
y = -1.0
elif x >= 4:
y = 1.0
else:
y = math.tanh(x)
return y
def clamp_sigmoid(x):
if x <= -8:
y = 0.0
elif x >= 8:
y = 1.0
else:
y = 1 / (1 + math.exp(-x))
return y