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- # 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.
-
- """
- sqrt run define
- """
-
- import numpy as np
- import akg
- import akg.lang.cce
- import akg.tvm
- from akg.utils import kernel_exec as utils
- from tests.common.test_op import range as tvm_range
- from tests.common.tensorio import compare_tensor
-
-
- def range_run(start, limit, delta, dtype, attrs):
- t_range = tvm_range.range_value(start, limit, delta, dtype)
- # Create module
- sch = akg.tvm.create_schedule(t_range.op)
- kernel_name = "range"
- with akg.build_config(add_lower_pass=utils.debug_mode(0), dump_pass_ir=True):
- mod = akg.build(sch, [t_range], "cce", name=kernel_name, attrs=attrs, polyhedral=True)
- print(mod.imported_modules[0].get_source())
- # Generate data for testing the op
- expect = np.asarray(list(range(start, limit, delta)))
-
- output = np.full((max(0, (limit - start) / delta),), np.nan, dtype)
- output = utils.mod_launch(mod, (output, ), expect=expect)
-
- return tuple(), output, expect, compare_tensor(output, expect, rtol=5e-03, equal_nan=True)
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