Move Quantization -> Dialect/QuantOps, FxpMathOps -> Dialect/FxpMathOps.

    Adding the additional layer of directory was discussed offline and matches the Target/ tree. The names match the defacto convention we seem to be following where the C++ namespace is ^(.+)Ops/$ matched against the directory name.

    This is in preparation for patching the Quantizer into this tree, which would have been confusing without moving the Quantization dialect to its more proper home. It is left to others to move other dialects if desired.

    Tested:
      ninja check-mlir

--

PiperOrigin-RevId: 248171982

3 files changed, 364 insertions, 0 deletions

diff --git a/mlir/lib/Dialect/QuantOps/Utils/FakeQuantSupport.cpp b/mlir/lib/Dialect/QuantOps/Utils/FakeQuantSupport.cpp
new file mode 100644
index 00000000000..5562e45bb4a
--- /dev/null
+++ b/mlir/lib/Dialect/QuantOps/Utils/FakeQuantSupport.cpp
@@ -0,0 +1,109 @@
+//===- FakeQuantSupport.cpp - Support utilities for FakeQuant ops ---------===//
+//
+// Copyright 2019 The MLIR Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// =============================================================================
+
+#include "mlir/Dialect/QuantOps/FakeQuantSupport.h"
+#include "mlir/Dialect/QuantOps/QuantTypes.h"
+
+using namespace mlir;
+using namespace mlir::quant;
+
+UniformQuantizedType mlir::quant::fakeQuantAttrsToType(Location loc,
+                                                       unsigned numBits,
+                                                       double rmin, double rmax,
+                                                       bool narrowRange,
+                                                       Type expressedType) {
+  MLIRContext *ctx = expressedType.getContext();
+  Type storageType;
+  unsigned flags;
+  int64_t qmin;
+  int64_t qmax;
+
+  // Hard-coded type mapping from TFLite.
+  if (numBits <= 8) {
+    storageType = IntegerType::get(8, ctx);
+    flags = 0;
+    qmin = 0;
+    qmax = 255;
+  } else if (numBits <= 16) {
+    storageType = IntegerType::get(16, ctx);
+    flags = QuantizationFlags::Signed;
+    qmin = -32768;
+    qmax = 32767;
+  } else {
+    ctx->emitError(loc, "unsupported FakeQuant number of bits: ") << numBits;
+    return nullptr;
+  }
+
+  // Handle narrowRange.
+  if (narrowRange) {
+    qmin += 1;
+  }
+
+  // Range must straddle zero.
+  if (rmin > 0.0 || rmax < 0.0) {
+    return (ctx->emitError(loc, "FakeQuant range must straddle zero: [")
+                << rmin << "," << rmax << "]",
+            nullptr);
+  }
+
+  // Special case where min/max is a point. Must be 0.
+  if (rmin == rmax) {
+    return UniformQuantizedType::getChecked(flags, storageType, expressedType,
+                                            0.0, 0, qmin, qmax, loc);
+  }
+
+  // Determine the scale.
+  const double qminDouble = qmin;
+  const double qmaxDouble = qmax;
+  const double scale = (rmax - rmin) / (qmaxDouble - qminDouble);
+
+  // Zero point computation.
+  // In float, solve the affine equation for any known pair
+  // (real value, corresponding quantized value), of which, two such pairs
+  // are known: (rmin, qmin), (rmax, qmax).
+  // The arithmetic error on the zero point computed from either pair will be
+  // roughly machine_epsilon * (sum of absolute values of terms).
+  // Use the variant that adds the smaller error.
+  const double zeroPointFromMin = qminDouble - rmin / scale;
+  const double zeroPointFromMinError =
+      std::abs(qminDouble) + std::abs(rmin / scale);
+  const double zeroPointFromMax = qmaxDouble - rmax / scale;
+  const double zeroPointFromMaxError =
+      std::abs(qmaxDouble) + std::abs(rmax / scale);
+
+  const double zeroPointDouble = (zeroPointFromMinError < zeroPointFromMaxError)
+                                     ? zeroPointFromMin
+                                     : zeroPointFromMax;
+
+  // Now nudge the zero point to be an integer.
+  int64_t nudgedZeroPoint = 0;
+  if (zeroPointDouble < qminDouble) {
+    nudgedZeroPoint = qmin;
+  } else if (zeroPointDouble > qmaxDouble) {
+    nudgedZeroPoint = qmax;
+  } else {
+    nudgedZeroPoint = round(zeroPointDouble);
+  }
+
+  // By construction, the nudged zero point should always be in range.
+  assert(nudgedZeroPoint >= qmin);
+  assert(nudgedZeroPoint <= qmax);
+
+  return UniformQuantizedType::getChecked(flags, storageType, expressedType,
+                                          scale, nudgedZeroPoint, qmin, qmax,
+                                          loc);
+}
diff --git a/mlir/lib/Dialect/QuantOps/Utils/QuantizeUtils.cpp b/mlir/lib/Dialect/QuantOps/Utils/QuantizeUtils.cpp
new file mode 100644
index 00000000000..3685a65f2d8
--- /dev/null
+++ b/mlir/lib/Dialect/QuantOps/Utils/QuantizeUtils.cpp
@@ -0,0 +1,182 @@
+//===- QuantizeUtils.cpp - Support utilities for quantization -------------===//
+//
+// Copyright 2019 The MLIR Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// =============================================================================
+
+#include "mlir/Dialect/QuantOps/QuantizeUtils.h"
+#include "mlir/Dialect/QuantOps/UniformSupport.h"
+#include "mlir/IR/Attributes.h"
+#include "mlir/IR/StandardTypes.h"
+
+namespace mlir {
+namespace quant {
+/// Converts a possible primitive, real expressed value attribute to a
+/// corresponding storage attribute (typically FloatAttr -> IntegerAttr).
+/// quantizedElementType is the QuantizedType that describes the expressed
+/// origValue.
+/// Returns a converter Attribute or nullptr if conversion is not possible.
+static Attribute convertPrimitiveValueAttr(
+    Attribute origRealValue, QuantizedType quantizedElementType,
+    const UniformQuantizedValueConverter &converter, Type &outConvertedType) {
+  if (origRealValue.isa<FloatAttr>()) {
+    FloatAttr floatAttr = origRealValue.cast<FloatAttr>();
+    outConvertedType = quantizedElementType.getStorageType();
+    return IntegerAttr::get(quantizedElementType.getStorageType(),
+                            converter.quantizeFloatToInt(floatAttr.getValue()));
+  }
+
+  return nullptr;
+}
+
+/// Converts a real expressed DenseFPElementsAttr to a corresponding
+/// DenseElementsAttr (typically DenseIntElementsAttr) containing quantized
+/// storage values assuming the given quantizedElementType and converter.
+static DenseElementsAttr
+convertDenseFPElementsAttr(DenseFPElementsAttr realFPElementsAttr,
+                           QuantizedType quantizedElementType,
+                           const UniformQuantizedValueConverter &converter) {
+  // Convert to corresponding quantized value attributes.
+  SmallVector<APInt, 8> quantValues;
+  quantValues.reserve(realFPElementsAttr.size());
+  for (APFloat realVal : realFPElementsAttr) {
+    quantValues.push_back(converter.quantizeFloatToInt(realVal));
+  }
+
+  // Cast from an expressed-type-based type to storage-type-based type,
+  // preserving the dense shape (i.e. tensor<4xf32> -> tensor<4xi8>).
+  VectorOrTensorType newDenseType =
+      quantizedElementType
+          .castExpressedToStorageType(realFPElementsAttr.getType())
+          .dyn_cast_or_null<VectorOrTensorType>();
+  if (!newDenseType) {
+    return nullptr;
+  }
+  return DenseIntElementsAttr::get(newDenseType, quantValues);
+}
+
+/// Converts a real expressed SplatElementsAttr to a corresponding
+/// SplatElementsAttr containing quantized storage values assuming the given
+/// quantizedElementType and converter.
+static SplatElementsAttr
+convertSplatElementsAttr(SplatElementsAttr realSplatAttr,
+                         QuantizedType quantizedElementType,
+                         const UniformQuantizedValueConverter &converter) {
+  // Since the splat just references a single primitive value, use the
+  // function for converting primitives.
+  // NOTE: When implementing per-channel, we will need to promote the
+  // splat to a dense and handle channels individually.
+  Type unusedPrimitiveType;
+  auto elementAttr =
+      convertPrimitiveValueAttr(realSplatAttr.getValue(), quantizedElementType,
+                                converter, unusedPrimitiveType);
+  if (!elementAttr) {
+    return nullptr;
+  }
+
+  // Cast from an expressed-type-based type to storage-type-based type,
+  // preserving the splat shape (i.e. tensor<4xf32> -> tensor<4xi8>).
+  VectorOrTensorType newSplatType =
+      quantizedElementType.castExpressedToStorageType(realSplatAttr.getType())
+          .dyn_cast_or_null<VectorOrTensorType>();
+  if (!newSplatType) {
+    return nullptr;
+  }
+  return SplatElementsAttr::get(newSplatType, elementAttr);
+}
+
+/// Converts a real expressed SplatElementsAttr to a corresponding
+/// SplatElementsAttr containing quantized storage values assuming the given
+/// quantizedElementType and converter.
+static SparseElementsAttr
+convertSparseElementsAttr(SparseElementsAttr realSparseAttr,
+                          QuantizedType quantizedElementType,
+                          const UniformQuantizedValueConverter &converter) {
+  DenseElementsAttr realDenseAttr = realSparseAttr.getValues();
+  if (!realDenseAttr.isa<DenseFPElementsAttr>()) {
+    return nullptr;
+  }
+  DenseElementsAttr quantDenseAttr =
+      convertDenseFPElementsAttr(realDenseAttr.cast<DenseFPElementsAttr>(),
+                                 quantizedElementType, converter);
+  if (!quantDenseAttr) {
+    return nullptr;
+  }
+
+  // Cast from an expressed-type-based type to storage-type-based type,
+  // preserving the sparse shape (i.e. tensor<4xf32> -> tensor<4xi8>).
+  VectorOrTensorType newSparseType =
+      quantizedElementType.castExpressedToStorageType(realSparseAttr.getType())
+          .dyn_cast_or_null<VectorOrTensorType>();
+  if (!newSparseType) {
+    return nullptr;
+  }
+  return SparseElementsAttr::get(newSparseType, realSparseAttr.getIndices(),
+                                 quantDenseAttr);
+}
+
+/// Converts a real expressed Attribute to a corresponding Attribute containing
+/// quantized storage values assuming the given uniform quantizedElementType and
+/// converter.
+Attribute quantizeAttrUniform(Attribute realValue,
+                              UniformQuantizedType quantizedElementType,
+                              const UniformQuantizedValueConverter &converter,
+                              Type &outConvertedType) {
+  // Fork to handle different variants of constants supported.
+  if (realValue.isa<SplatElementsAttr>()) {
+    // Splatted tensor or vector constant.
+    auto converted = convertSplatElementsAttr(
+        realValue.cast<SplatElementsAttr>(), quantizedElementType, converter);
+    outConvertedType = converted.getType();
+    return converted;
+  } else if (realValue.isa<DenseFPElementsAttr>()) {
+    // Dense tensor or vector constant.
+    auto converted = convertDenseFPElementsAttr(
+        realValue.cast<DenseFPElementsAttr>(), quantizedElementType, converter);
+    outConvertedType = converted.getType();
+    return converted;
+  } else if (realValue.isa<SparseElementsAttr>()) {
+    // Sparse tensor or vector constant.
+    auto converted = convertSparseElementsAttr(
+        realValue.cast<SparseElementsAttr>(), quantizedElementType, converter);
+    outConvertedType = converted.getType();
+    return converted;
+  } else {
+    // Nothing else matched: try to convert a primitive.
+    return convertPrimitiveValueAttr(realValue, quantizedElementType, converter,
+                                     outConvertedType);
+  }
+}
+
+/// Convert an attribute from a type based on
+/// quantizedElementType.getExpressedType() to one based on
+/// quantizedElementType.getStorageType().
+/// Returns nullptr if the conversion is not supported.
+/// On success, stores the converted type in outConvertedType.
+Attribute quantizeAttr(Attribute realValue, QuantizedType quantizedElementType,
+                       Type &outConvertedType) {
+  // Hard-coded to just support UniformQuantizedType. This will need to
+  // be generalized when there is more than one.
+  auto uniformQuantizedType =
+      quantizedElementType.dyn_cast<UniformQuantizedType>();
+  if (!uniformQuantizedType) {
+    return nullptr;
+  }
+  UniformQuantizedValueConverter converter(uniformQuantizedType);
+  return quantizeAttrUniform(realValue, uniformQuantizedType, converter,
+                             outConvertedType);
+}
+
+} // namespace quant
+} // namespace mlir
diff --git a/mlir/lib/Dialect/QuantOps/Utils/UniformSupport.cpp b/mlir/lib/Dialect/QuantOps/Utils/UniformSupport.cpp
new file mode 100644
index 00000000000..d791075f5db
--- /dev/null
+++ b/mlir/lib/Dialect/QuantOps/Utils/UniformSupport.cpp
@@ -0,0 +1,73 @@
+//===- UniformSupport.cpp - Support utilities for uniform quant -----------===//
+//
+// Copyright 2019 The MLIR Authors.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// =============================================================================
+
+#include "mlir/Dialect/QuantOps/UniformSupport.h"
+#include "mlir/IR/StandardTypes.h"
+
+using namespace mlir;
+using namespace mlir::quant;
+
+static bool isQuantizablePrimitiveType(Type inputType) {
+  return inputType.isa<FloatType>();
+}
+
+const ExpressedToUniformQuantizedConverter
+ExpressedToUniformQuantizedConverter::forInputType(Type inputType) {
+  switch (inputType.getKind()) {
+  default:
+    if (isQuantizablePrimitiveType(inputType)) {
+      // Supported primitive type (which just is the expressed type).
+      return ExpressedToUniformQuantizedConverter{inputType, inputType};
+    }
+    // Unsupported.
+    return ExpressedToUniformQuantizedConverter{inputType, nullptr};
+  case StandardTypes::RankedTensor:
+  case StandardTypes::UnrankedTensor:
+  case StandardTypes::Vector: {
+    Type elementType = inputType.cast<VectorOrTensorType>().getElementType();
+    if (!isQuantizablePrimitiveType(elementType)) {
+      // Unsupported.
+      return ExpressedToUniformQuantizedConverter{inputType, nullptr};
+    }
+    return ExpressedToUniformQuantizedConverter{
+        inputType, inputType.cast<VectorOrTensorType>().getElementType()};
+  }
+  }
+}
+
+Type ExpressedToUniformQuantizedConverter::convert(
+    UniformQuantizedType elementalType) const {
+  assert(expressedType && "convert() on unsupported conversion");
+
+  switch (inputType.getKind()) {
+  default:
+    if (isQuantizablePrimitiveType(elementalType)) {
+      // For primitives, just use the new elemental type.
+      return elementalType;
+    }
+    // Unsupported.
+    return nullptr;
+  case StandardTypes::RankedTensor:
+    return RankedTensorType::get(inputType.cast<RankedTensorType>().getShape(),
+                                 elementalType);
+  case StandardTypes::UnrankedTensor:
+    return UnrankedTensorType::get(elementalType);
+  case StandardTypes::Vector:
+    return VectorType::get(inputType.cast<VectorType>().getShape(),
+                           elementalType);
+  }
+}