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55 lines
2.0 KiB
55 lines
2.0 KiB
# Copyright 2019 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""operator dsl function: equal"""
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import _akg.tvm
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import _akg.topi
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from _akg.utils.dsl_create import produce_shapes
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from _akg.utils import validation_check as vc_util
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@vc_util.check_input_type(_akg.tvm.tensor.Tensor, _akg.tvm.tensor.Tensor)
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def equal(input1, input2):
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"""
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check whether input1 equals to input2.
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Args:
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input1 (tvm.tensor.Tensor): Tensor.
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input2 (tvm.tensor.Tensor): Tensor.
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Returns:
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tvm.tensor.Tensor. If input1 equal to input2 return True, else return False.
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"""
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shape1 = [x.value for x in input1.shape]
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shape2 = [x.value for x in input2.shape]
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vc_util.check_shape(shape1)
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vc_util.check_shape(shape2)
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shape1, shape2, shape = produce_shapes(shape1, shape2)
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vc_util.elemwise_dtype_check(input1.dtype, input2.dtype)
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dtype = input1.dtype
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# get equal compute
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t_value = _akg.tvm.compute(shape, lambda *indice: _akg.tvm.const(1, dtype), "T")
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f_value = _akg.tvm.compute(shape, lambda *indice: _akg.tvm.const(0, dtype), "F")
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input1_bro = _akg.topi.broadcast_to(input1, shape)
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input2_bro = _akg.topi.broadcast_to(input2, shape)
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c_out = _akg.tvm.compute(shape, lambda *indice: _akg.tvm.expr.Select(input1_bro[indice] == input2_bro[indice],
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t_value[indice], f_value[indice]), name="C")
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res = _akg.tvm.compute(shape, lambda *indice: c_out(*indice).astype("bool"), name="res")
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return res
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