xref: /llvm-project/mlir/lib/Dialect/Tosa/Utils/QuantUtils.cpp (revision 0763f12213dc931a4c6926324e4e5d825237405c)
1 //===- QuantUtils.cpp -----------------------------------------------------===//
2 //
3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4 // See https://llvm.org/LICENSE.txt for license information.
5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6 //
7 //===----------------------------------------------------------------------===//
8 //
9 // This file contains TOSA numerical support functions and quantization
10 // attribute builders.
11 //
12 //===----------------------------------------------------------------------===//
13 
14 #include "mlir/Dialect/Tosa/Utils/QuantUtils.h"
15 
16 using namespace mlir;
17 using namespace mlir::tosa;
18 
19 /// From a scale value, generates multiplier and shift values where
20 /// mantissa is in [-1.0,-0.5] or [0.5, 1.0] such that
21 /// multiplier = mantissa*2^shift for 16-bit scaling.
22 static void computeMultiplierAndShiftTosaScale16(double scale,
23                                                  int32_t &multiplier,
24                                                  int32_t &shift) {
25 
26   const double mantissa = std::frexp(scale, &shift);
27   auto shiftedM = std::round(mantissa * (int64_t(1) << 15));
28 
29   // Can't be greater than 1.0.
30   assert(shiftedM <= (int64_t(1) << 15) &&
31          "Shifted mantissa exceeds 16 signed bits");
32 
33   if (shiftedM == (int64_t(1) << 15)) {
34     shiftedM /= 2;
35     shift++;
36   }
37 
38   // TOSA expects right shift to be positive and embed (1 << 15) into right
39   // shift bits.
40   shift = (-shift) + 15;
41 
42   assert(shiftedM <= std::numeric_limits<int32_t>::max() &&
43          "Shifted mantissa exceeds 32-bit signed output type");
44 
45   multiplier = static_cast<int32_t>(shiftedM);
46 
47   // Shifting tops out at 63 bits. Right shift to make 63 bits the max.
48   if (shift > 63) {
49     // Shifting the multiplier by more than 32-bits is unnecessary.
50     multiplier = multiplier >> std::min<int32_t>(32, shift - 63);
51     shift = 63;
52   }
53 }
54 
55 /// From a scale value, generates multiplier and shift values where
56 /// mantissa is in [-1.0,-0.5] or [0.5, 1.0] such that
57 /// multiplier = mantissa*2^shift for 32-bit scaling.
58 static void computeMultiplierAndShiftTosaScale32(double scale,
59                                                  int32_t &multiplier,
60                                                  int32_t &shift) {
61 
62   const double mantissa = std::frexp(scale, &shift);
63   auto shiftedM = std::round(mantissa * (int64_t(1) << 31));
64 
65   // Can't be greater than 1.0.
66   assert(shiftedM <= (int64_t(1) << 31) &&
67          "Shifted mantissa exceeds 32 signed bits");
68   if (shiftedM == (int64_t(1) << 31)) {
69     shiftedM /= 2;
70     shift++;
71   }
72 
73   // TOSA expects right shift to be positive, and embed (1 << 31) into right
74   // shift bits.
75   shift = (-shift) + 31;
76 
77   assert(shiftedM <= std::numeric_limits<int32_t>::max() &&
78          "Shifted mantissa exceeds 32-bit signed output type");
79 
80   multiplier = static_cast<int32_t>(shiftedM);
81 
82   // Shifting tops out at 63 bits. Right shift to make 63 bits the max.
83   if (shift > 63) {
84     // Shifting the multiplier by more than 32-bits is unnecessary.
85     multiplier = multiplier >> std::min<int32_t>(32, shift - 63);
86     shift = 63;
87   }
88 }
89 
90 /// Generates a quantized multiplier/shift from double.
91 void mlir::tosa::computeMultiplierAndShift(double scale, int32_t &multiplier,
92                                            int32_t &shift, int32_t scaleWidth) {
93 
94   switch (scaleWidth) {
95   case 16:
96     computeMultiplierAndShiftTosaScale16(scale, multiplier, shift);
97     return;
98   case 32:
99     computeMultiplierAndShiftTosaScale32(scale, multiplier, shift);
100     return;
101   default:
102     assert(0 && "Unsupported Tosa quantized_scale regime specified!");
103   }
104 }
105 
106 #define GET_UQTYPE(input_type)                                                 \
107   ((input_type).getElementType().dyn_cast<quant::UniformQuantizedType>())
108 #define GET_QTYPE(input_type)                                                  \
109   ((input_type).getElementType().dyn_cast<quant::QuantizedType>())
110 
111 /// Method to build ConvOpQuantizationAttr, called from
112 /// ConvOpQuantInfoBuilder/TransConvOpQuantInfoBuilder:
113 /// input_zp: input zeropoint
114 /// weight_zp: weight zeropoint.
115 ConvOpQuantizationAttr
116 mlir::tosa::buildConvOpQuantizationAttr(OpBuilder &builder, Value input,
117                                         Value weight) {
118 
119   auto inputType = input.getType().dyn_cast<ShapedType>();
120   auto weightType = weight.getType().dyn_cast<ShapedType>();
121 
122   if (!inputType || !weightType)
123     return nullptr;
124 
125   auto inputQType = GET_UQTYPE(inputType);
126   auto weightPerTensorQType = GET_UQTYPE(weightType);
127   auto weightPerAxisQType = weightType.getElementType()
128                                 .dyn_cast<quant::UniformQuantizedPerAxisType>();
129 
130   // Weights must be either per-tensor quantized or per-axis quantized.
131   assert(!((bool)weightPerTensorQType && (bool)weightPerAxisQType) &&
132          "Weights must be either per-tensor or per-axis quantized");
133 
134   // Either all quantized or all not quantized.
135   assert(!((bool)inputQType ^
136            ((bool)weightPerTensorQType || (bool)weightPerAxisQType)) &&
137          "Inputs and weights must be all quantized or all not quantized");
138 
139   if (inputQType) {
140 
141     int64_t inputZp = inputQType.getZeroPoint();
142     int64_t weightZp = 0;
143 
144     if (weightPerTensorQType) {
145       weightZp = weightPerTensorQType.getZeroPoint();
146     } else if (weightPerAxisQType) {
147       weightZp = weightPerAxisQType.getZeroPoints().front();
148     }
149 
150     auto quantAttr = tosa::ConvOpQuantizationAttr::get(
151         builder.getI32IntegerAttr(inputZp), builder.getI32IntegerAttr(weightZp),
152         builder.getContext());
153 
154     return quantAttr;
155   }
156 
157   return nullptr;
158 }
159 
160 /// Builds MatMulOpQuantizationAttr, called from
161 /// MatMulOpQuantInfoBuilder:
162 /// aZp: input a zeropoint
163 /// bZp: input b zeropoint.
164 MatMulOpQuantizationAttr
165 mlir::tosa::buildMatMulOpQuantizationAttr(OpBuilder &builder, Value a,
166                                           Value b) {
167 
168   auto aType = a.getType().dyn_cast<ShapedType>();
169   auto bType = b.getType().dyn_cast<ShapedType>();
170 
171   if (!aType || !bType)
172     return nullptr;
173 
174   auto aQType = GET_UQTYPE(aType);
175   auto bQType = GET_UQTYPE(bType);
176 
177   // A and B are either all quantized or all not quantized.
178   assert(!((bool)aQType ^ (bool)bQType) &&
179          "Matmul operands must be all quantized or all not quantized");
180 
181   if (aQType) {
182 
183     int64_t aZp = aQType.getZeroPoint();
184     int64_t bZp = bQType.getZeroPoint();
185 
186     auto quantAttr = tosa::MatMulOpQuantizationAttr::get(
187         builder.getI32IntegerAttr(aZp), builder.getI32IntegerAttr(bZp),
188         builder.getContext());
189 
190     return quantAttr;
191   }
192 
193   return nullptr;
194 }
195 
196 /// Builds UnaryOpQuantizationAttr
197 /// UnaryOpQuantInfoBuilder:
198 /// inputZp: input zeropoint
199 /// outputZp: output zeropoint.
200 UnaryOpQuantizationAttr
201 mlir::tosa::buildUnaryOpQuantizationAttr(OpBuilder &builder, Value input,
202                                          Type outputRawType) {
203 
204   auto inputType = input.getType().dyn_cast<ShapedType>();
205   auto outputType = outputRawType.dyn_cast<ShapedType>();
206 
207   if (!inputType || !outputType)
208     return nullptr;
209 
210   auto inputQType = GET_UQTYPE(inputType);
211   auto outputQType = GET_UQTYPE(outputType);
212 
213   // Either all quantized or all not quantized.
214   assert(!((bool)inputQType ^ (bool)outputQType) &&
215          "Unary inputs/outputs must be all quantized or all not quantized");
216 
217   if (inputQType) {
218 
219     int64_t inputZp = inputQType.getZeroPoint();
220     int64_t outputZp = outputQType.getZeroPoint();
221 
222     auto quantAttr = tosa::UnaryOpQuantizationAttr::get(
223         builder.getI32IntegerAttr(inputZp), builder.getI32IntegerAttr(outputZp),
224         builder.getContext());
225 
226     return quantAttr;
227   }
228 
229   return nullptr;
230 }
231 
232 /// Builds PadOpQuantizationAttr, called from PadOpQuantInfoBuilder:
233 /// inputZp: input zeropoint.
234 PadOpQuantizationAttr mlir::tosa::buildPadOpQuantizationAttr(OpBuilder &builder,
235                                                              Value input) {
236 
237   auto inputType = input.getType().dyn_cast<ShapedType>();
238 
239   if (!inputType)
240     return nullptr;
241 
242   auto inputQType = GET_UQTYPE(inputType);
243 
244   if (inputQType) {
245 
246     int64_t inputZp = inputQType.getZeroPoint();
247 
248     auto quantAttr = tosa::PadOpQuantizationAttr::get(
249         builder.getI32IntegerAttr(inputZp), builder.getContext());
250 
251     return quantAttr;
252   }
253 
254   return nullptr;
255 }
256 
257 /// Builds output type for a quantized ConvOp with the right bitwidth.
258 /// This is called by the builder when dealing with quantized content.
259 Type mlir::tosa::buildConvOpResultTypeInfo(OpBuilder &builder, Type outputType,
260                                            Value input, Value weight) {
261 
262   auto inputType = input.getType().dyn_cast<ShapedType>();
263   auto weightType = weight.getType().dyn_cast<ShapedType>();
264 
265   assert(inputType && weightType &&
266          "Could not extract input or weight tensors from Conv op");
267 
268   auto inputQType = GET_QTYPE(inputType);
269   auto weightQType = GET_QTYPE(weightType);
270 
271   assert(inputQType && weightQType &&
272          "Could not extract input or weight tensor types from Conv op");
273 
274   unsigned inputBits = inputQType.getStorageTypeIntegralWidth();
275   unsigned weightBits = weightQType.getStorageTypeIntegralWidth();
276 
277   auto outputShapedType = outputType.dyn_cast<ShapedType>();
278   assert(outputShapedType &&
279          "Could not extract output shape type from Conv op");
280 
281   IntegerType accElementType;
282   if (inputBits == 16 && weightBits == 8)
283     accElementType = builder.getIntegerType(48);
284   else
285     accElementType = builder.getI32Type();
286   auto accType = outputShapedType.clone(accElementType);
287   return accType;
288 }
289 
290 /// Builds Tosa quantization attributes from min/max values.
291 Type mlir::tosa::buildQTypeFromMinMax(OpBuilder builder, Type inputDType,
292                                       Attribute minAttr, Attribute maxAttr,
293                                       IntegerAttr quantBits, int filterQuantDim,
294                                       bool isSigned, BoolAttr narrowRange) {
295 
296   quant::QuantizedType retType;
297 
298   auto convfunc =
299       quant::ExpressedToQuantizedConverter::forInputType(inputDType);
300 
301   auto minElems = minAttr.dyn_cast<DenseFPElementsAttr>();
302   auto maxElems = maxAttr.dyn_cast<DenseFPElementsAttr>();
303 
304   SmallVector<double, 2> min, max;
305 
306   // At least one is per-axis quantized elementsattr.
307   if (minElems || maxElems) {
308     // Must have the same number of elements.
309     if (minElems.getNumElements() != maxElems.getNumElements())
310       return {};
311     min.reserve(minElems.getNumElements());
312     max.reserve(maxElems.getNumElements());
313     for (auto i : minElems)
314       min.push_back(FloatAttr::getValueAsDouble(i));
315     for (auto i : maxElems)
316       max.push_back(FloatAttr::getValueAsDouble(i));
317   } else { // Just a single FP value.
318     auto minVal = minAttr.dyn_cast<FloatAttr>();
319     if (minVal)
320       min.push_back(minVal.getValueAsDouble());
321     else
322       return {};
323     auto maxVal = maxAttr.dyn_cast<FloatAttr>();
324     if (maxVal)
325       max.push_back(maxVal.getValueAsDouble());
326     else
327       return {};
328   }
329 
330   if (min.size() == max.size()) {
331     if (min.size() == 1) { // Per-tensor quantization with one min/max pair.
332       retType = quant::fakeQuantAttrsToType(
333           builder.getUnknownLoc(), quantBits.getInt(), min[0], max[0],
334           narrowRange.getValue(), convfunc.expressedType, isSigned);
335     } else if (min.size() > 1) { // Per-axis quant on filterQuantDim.
336       auto shape = inputDType.dyn_cast<ShapedType>();
337       if (!shape)
338         return {};
339       if ((filterQuantDim) >= 0 && (shape.getRank() > filterQuantDim)) {
340         retType = quant::fakeQuantAttrsToType(
341             builder.getUnknownLoc(), quantBits.getInt(), filterQuantDim, min[0],
342             max[0], narrowRange.getValue(), convfunc.expressedType, isSigned);
343       }
344     } else {
345       return {};
346     }
347   } else {
348     return {};
349   }
350 
351   if (!retType)
352     return {};
353 
354   return convfunc.convert(retType);
355 }
356 
357 /// Builds Tosa quantization attributes from min/max values.
358 TypeAttr
359 mlir::tosa::buildQTypeAttrFromMinMax(OpBuilder builder, Type inputDtype,
360                                      Attribute minAttr, Attribute maxAttr,
361                                      IntegerAttr quantBits, int filterQuantDim,
362                                      bool isSigned, BoolAttr narrowRange) {
363 
364   return TypeAttr::get(buildQTypeFromMinMax(builder, inputDtype, minAttr,
365                                             maxAttr, quantBits, filterQuantDim,
366                                             isSigned, narrowRange));
367 }
368