f6bc68ba4c
This CL gives additional configuration to dynamic padder, which tells it what ops can have accept dynamic tensors. If an op requires dynamic tensor as input, and a static tensor is presented, a "SliceToDynamic" will be inserted. If an op requires static tensor as input and a dynamic tensor is presented, a "PadToStatic" op will be inserted. If an op requires static tensor and the tensor is already static, dynamic padder will rewrite the op to make it produce the same result as if the tensor is dynamic (this is what we already have today). PiperOrigin-RevId: 309326119 Change-Id: I5376674d6acf9905af1b7e09b127811b57517e97
92 lines
3.7 KiB
C++
92 lines
3.7 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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#ifndef TENSORFLOW_COMPILER_XLA_SERVICE_DYNAMIC_PADDER_H_
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#define TENSORFLOW_COMPILER_XLA_SERVICE_DYNAMIC_PADDER_H_
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#include "tensorflow/compiler/xla/service/dynamic_dimension_inference.h"
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#include "tensorflow/compiler/xla/service/hlo_pass_interface.h"
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namespace xla {
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// With bounded shapes, only part of the shape contains effective data and the
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// rest contains padded data, whose value can be anything depending on the
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// source of the data. When a bounded shape is directly consumed by an
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// instruction that collapses dimensions (reduce for example), the padding data
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// would affect result of the instruction.
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//
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// DynamicPadder uses DynamicDimensionInference to detect bounded shapes in a
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// hlo module, it then inserts certain instructions to reset the padding into an
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// identity value so that in doesn't affect the result of subsequent
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// instruction. For example, it'd reset the padding to 0 before a bounded shape
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// is consumed by a reduce-sum.
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//
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// Dynamic_padder removes dynamic shapes from the entry computation, and inserts
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// custom calls (with dynamic shapes), which are lowered by specialized
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// emitters: PadToStatic and SliceToDynamic.
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// Each instruction can have one of the three modes in supporting dynamic
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// lowering.
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enum OpDynamismSupport {
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// There is no support for dynamic lowering -- dynamic padder will make sure
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// the input to that op has static bound by rewriting the op (e.g, extra space
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// in reduce_sum will be padded with 0).
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kNoSupport = 0,
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// The op can take either dynamic input or static input.
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kOptional,
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// The op only has a dynamic lowering, dynamic padder will make sure the input
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// to this op is in dynamic form.
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kRequired,
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};
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class DynamicPadder : public HloModulePass {
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public:
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// Returns true if given instruction supports native dynamic lowering. If so,
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// dynamic padder will not attempt to pad it.
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using OpSupportsDynamismHandler =
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std::function<OpDynamismSupport(HloInstruction*)>;
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// If `slice_dynamic_output` is true, insert 'slice_to_dynamic' ops to all
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// outputs that are inferred to be dynamic.
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explicit DynamicPadder(
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bool slice_dynamic_output = true,
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DynamicDimensionInference::CustomCallInferenceHandler
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custom_call_handler = nullptr,
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OpSupportsDynamismHandler op_supports_dynamism_handler = nullptr)
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: slice_dynamic_output_(slice_dynamic_output),
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custom_call_handler_(custom_call_handler),
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op_supports_dynamism_handler_(op_supports_dynamism_handler) {}
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absl::string_view name() const override { return "dynamic_padder"; }
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StatusOr<bool> Run(HloModule* module) override;
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private:
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// Insert 'slice_to_dynamic' ops to all outputs that are inferred to be
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// dynamic.
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bool slice_dynamic_output_;
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// A handler for dynamic dimension inference of custom calls.
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DynamicDimensionInference::CustomCallInferenceHandler custom_call_handler_;
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// A handler to indicate if a given hlo instruction support native dynamism
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// lowering.
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OpSupportsDynamismHandler op_supports_dynamism_handler_;
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};
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} // namespace xla
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#endif // TENSORFLOW_COMPILER_XLA_SERVICE_DYNAMIC_PADDER_H_
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