xref: /aosp_15_r20/external/tensorflow/tensorflow/compiler/tf2tensorrt/convert/ops/quantization_ops.h (revision b6fb3261f9314811a0f4371741dbb8839866f948)
1 /* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
2 
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6 
7     http://www.apache.org/licenses/LICENSE-2.0
8 
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15 #ifndef TENSORFLOW_COMPILER_TF2TENSORRT_CONVERT_OPS_QUANTIZATION_OPS_H_
16 #define TENSORFLOW_COMPILER_TF2TENSORRT_CONVERT_OPS_QUANTIZATION_OPS_H_
17 #if GOOGLE_CUDA && GOOGLE_TENSORRT
18 
19 #include "absl/strings/str_format.h"
20 #include "absl/strings/str_join.h"
21 #include "tensorflow/core/graph/graph.h"
22 #include "tensorflow/core/lib/core/status.h"
23 
24 namespace tensorflow {
25 namespace tensorrt {
26 namespace convert {
27 
28 constexpr std::array<const char*, 4> kQuantizationOpNames = {
29     "QuantizeAndDequantizeV2",
30     "QuantizeAndDequantizeV3",
31     "FakeQuantWithMinMaxVars",
32     "FakeQuantWithMinMaxArgs",
33 };
34 
35 // Operations with supported conversion to Q/DQ ops in TensorRT explicit
36 // precision mode.
37 constexpr std::array<const char*, 1> kExplicitQuantizationOpNames = {
38     "QuantizeAndDequantizeV2",
39 };
40 
41 // Contains two scaling factors for quantization and dequantization
42 // respectively. A shift factor is omitted as TensorRT only supports symmetric
43 // quantization.
44 template <typename T, size_t N>
45 struct QuantizationScales {
46   std::array<T, N> quantize_scale;
47   std::array<T, N> dequantize_scale;
48 };
49 
50 // In TensorRT 7 and 8, only uniform tensor scaling is supported for
51 // activations.
52 using UniformQuantizationScales = QuantizationScales<float, 1>;
53 
54 // Per-channel scaling is supported for weights in TensorRT version >= 8.0.
55 template <size_t ChannelDimSize>
56 using PerChannelQuantizationScales = QuantizationScales<float, ChannelDimSize>;
57 
58 template <typename T, size_t N>
59 std::ostream& operator<<(std::ostream& os,
60                          const QuantizationScales<T, N>& scales) {
61   os << absl::StrFormat("QuantizationScales[quantize={%s},dequantize={%s}]",
62                         absl::StrJoin(scales.quantize_scale, ","),
63                         absl::StrJoin(scales.dequantize_scale, ","));
64   return os;
65 }
66 
67 // Returns true if the Tensorflow node is a quantize and dequantize operation.
68 bool IsQuantizeAndDequantizeOp(const Node*);
69 
70 }  // namespace convert
71 }  // namespace tensorrt
72 }  // namespace tensorflow
73 
74 #endif  // GOOGLE_CUDA && GOOGLE_TENSORRT
75 
76 #endif  // TENSORFLOW_COMPILER_TF2TENSORRT_CONVERT_OPS_QUANTIZATION_OPS_H_
77