66 lines
2.4 KiB
C++
66 lines
2.4 KiB
C++
/* Copyright 2018 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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#ifndef TENSORFLOW_COMPILER_TF2XLA_KERNELS_IF_OP_H_
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#define TENSORFLOW_COMPILER_TF2XLA_KERNELS_IF_OP_H_
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#include "tensorflow/compiler/tf2xla/xla_op_kernel.h"
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#include "tensorflow/core/framework/attr_value.pb.h"
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namespace tensorflow {
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// This TensorFlow op provides a functional conditional primitive.
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//
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// The outputs of the then/else branches must agree on the number, types, and
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// shapes of the Tensors carried around the two bodies.
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//
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// Computations in then/else bodies may read from and write to resource
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// variables.
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// Resource variables may be passed as arguments to the then/else function's
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// bodies. The XlaCompiler converts resource variable arguments
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// into parameters to the XLA computation and moves them to the end of the
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// parameter list, and by using the `return_updated_values_for_all_variables`
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// we ensure that all variables that appear in the input also appear at the
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// end of the then/else bodies output. This ensures the then/else bodies output
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// signatures match.
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//
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// It is the user's responsibility to ensure that each non-variable _Arg matches
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// the corresponding _Retval.
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class XlaIfOp : public XlaOpKernel {
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public:
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explicit XlaIfOp(OpKernelConstruction* ctx);
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void Compile(XlaOpKernelContext* ctx) override;
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private:
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TF_DISALLOW_COPY_AND_ASSIGN(XlaIfOp);
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NameAttrList then_branch_;
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NameAttrList else_branch_;
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DataType cond_type_;
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DataTypeVector input_types_;
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DataTypeVector output_types_;
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bool has_token_input_output_;
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std::vector<string> token_input_nodes_;
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// Whether to propagate compile time consts into the cond branches.
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// This is not supported by default now since it may cause HBM memory
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// overheads.
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bool propagate_compile_time_consts_ = false;
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};
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} // namespace tensorflow
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#endif // TENSORFLOW_COMPILER_TF2XLA_KERNELS_IF_OP_H_
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