115 lines
4.2 KiB
C++
115 lines
4.2 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_LITE_TOOLS_OPTIMIZE_OPERATOR_PROPERTY_H_
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#define TENSORFLOW_LITE_TOOLS_OPTIMIZE_OPERATOR_PROPERTY_H_
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#include "tensorflow/lite/model.h"
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#include "tensorflow/lite/schema/schema_generated.h"
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namespace tflite {
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namespace optimize {
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namespace operator_property {
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// The scales of a certain tensor can be derived from the multiplications of all
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// the scales. For example, for bias in conv, derived_scale = {{0, 1}, {}, {}}
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// and for lstm gate bias, the derived scale is {{}, {0}, {2^-10}}
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struct DerivedScale {
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std::vector<int> input_tensors = {};
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std::vector<int> intermediate_tensors = {};
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// This is a list of extra factors that are not associated with any other
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// tensor.
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std::vector<float> factors = {};
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};
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struct TensorProperty {
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// per_axis also implies symmetric currently.
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bool per_axis = false;
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// TODO(jianlijianli): remove dimension index and read it from tensor instead.
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int per_axis_index = 0;
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bool symmetric = false;
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// Constraints.
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bool restriction = false;
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// scale/zero_point hardcoded.
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std::pair<float, int> restricted_value_int8 = {0.0f, 0};
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std::pair<float, int> restricted_value_int16 = {0.0f, 0};
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// Use derived scale.
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bool use_derived_scale = false;
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// The derived scale.
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DerivedScale derived_scale;
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// The number of bits for this tensor. It could be 8, 16, 32 or even not power
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// of two.
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int number_of_bits = 8;
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// Extend the range to power of two.
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bool extend_to_power_of_two = false;
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// State tensor.
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bool state_tensor = false;
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};
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struct OperatorProperty {
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// Is a quantized operations currently supported.
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bool quantizable = true;
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// Is a quantized operations currently supported for 16x8
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bool quantizable_int16 = true;
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// Op has arbitrary number of inputs, such as concat.
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bool arbitrary_inputs = false;
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// Op has arbitrary number of outputs, such as slice.
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bool arbitrary_outputs = false;
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// Input indexes -> input tensor property.
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// Must be topologically sorted since there are derived scales.
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std::vector<std::pair<int, TensorProperty>> inputs = {};
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// Output indexes -> output tensor property.
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std::vector<std::pair<int, TensorProperty>> outputs = {};
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// Bias indexes.
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// TODO(jianlijianli): remove this by putting biases into inputs as well since
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// we now can model "derived scale".
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std::vector<int> biases = {};
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// Intermediate indexes -> intermediate tensor property.
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std::vector<std::pair<int, TensorProperty>> intermediates = {};
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// Force output to reuse the same scale and zero point of input.
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bool restrict_same_input_output_scale = false;
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// Use same min of min and max of max for each group.
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// Incompatible with restrict_same_input_output_scale and restricted_value.
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// TODO(jianlijianli): make it compatible with other restrictions when there
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// is a use case.
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std::vector<std::vector<int>> restrict_scale = {};
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// Op version.
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int version = 1;
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// When we quantize activations into 16 bit and weights into 8 bit,
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// we want to quantize all inputs, including constant tensors,
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// for the operators like Add, Mul into 16-bit as well. The constant
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// inputs are quantized as weights and this variable indicates
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// that we want to do quantizations of these tensors as activations.
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bool quantize_input_as_activations = false;
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};
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OperatorProperty GetOperatorProperty(const ModelT* model, int subgraph_index,
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int op_index);
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} // namespace operator_property
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} // namespace optimize
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} // namespace tflite
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#endif // TENSORFLOW_LITE_TOOLS_OPTIMIZE_OPERATOR_PROPERTY_H_
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