wehub-resource-sync
41 lines
1.5 KiB
C++
41 lines
1.5 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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==============================================================================*/
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#include <array>
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#include "tensorflow/compiler/tf2xla/mlir_xla_op_kernel.h"
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#include "tensorflow/compiler/tf2xla/xla_helpers.h"
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#include "tensorflow/compiler/tf2xla/xla_op_kernel.h"
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#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
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#include "xla/hlo/builder/lib/matrix.h"
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#include "xla/hlo/builder/xla_builder.h"
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#include "tensorflow/core/framework/op_kernel.h"
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#include "tensorflow/core/framework/types.pb.h"
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namespace tensorflow {
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namespace {
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constexpr std::array<DataType, 9> kEinsumTypes = {
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{DT_INT32, DT_INT64, DT_UINT64, DT_HALF, DT_BFLOAT16, DT_FLOAT, DT_DOUBLE,
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DT_COMPLEX64, DT_COMPLEX128}};
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REGISTER_XLA_OP(Name("XlaEinsum").TypeConstraint("T", kEinsumTypes),
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MlirXlaOpKernel);
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REGISTER_XLA_OP(Name("Einsum").TypeConstraint("T", kEinsumTypes),
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MlirXlaOpKernel);
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} // namespace
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} // namespace tensorflow
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