# 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. import numpy as np from tensorio import compare_tensor from akg.utils import kernel_exec as utils from akg.ops.math import abs from base import get_rtol_atol def abs_run(shape, dtype, attrs): # Result_Numpy input_shape = [shape] input_dtype = [dtype] op_attrs = [shape, dtype] if 'tuning' in attrs.keys(): t = attrs.get("tuning", False) kernel_name = attrs.get("kernel_name", False) mod = utils.op_build_test(abs.abs_value, input_shape, input_dtype, kernel_name=kernel_name, attrs=attrs, tuning=t) if t: exp_output, inputs, output = gen_date(dtype, shape) return mod, exp_output, (inputs, output) else: return mod else: # result_tvm mod = utils.op_build_test(abs.abs_value, input_shape, input_dtype, kernel_name='abs', attrs=attrs) exp_output, inputs, output = gen_date(dtype, shape) acu_output = utils.mod_launch(mod, (inputs, output), expect=exp_output) # compare result rtol, atol = get_rtol_atol("abs", dtype) TestCase_Result = compare_tensor(acu_output, exp_output, rtol=rtol, atol=atol, equal_nan=True) return inputs, acu_output, exp_output, TestCase_Result def gen_date(dtype, shape): inputs = np.random.uniform(-1, 0, size=shape).astype(dtype) exp_output = np.abs(inputs) # inputs and output to hold the data output = np.full(shape, np.nan, dtype) return exp_output, inputs, output