Remove the constraint that min / max should stride zero

Since we apply nudging for the zero point to make sure the nudged zerop points
can be in the range of [qmin, qmax], the constraint that rmin / rmax should
stride zero isn't necessary.

This also matches the documentation of tensorflow's FakeQuantWithMinMaxArgs op,
where min and max don't need to stride zero:
https://www.tensorflow.org/api_docs/python/tf/quantization/fake_quant_with_min_max_args

PiperOrigin-RevId: 268296285

mlir/lib/Dialect/QuantOps/Utils/FakeQuantSupport.cpp

@@ -54,8 +54,17 @@ bool getDefaultStorageParams(unsigned numBits, bool narrowRange, bool isSigned,
   return false;
 }
 
-void getScaleAndZeroPoint(int64_t qmin, int64_t qmax, double rmin, double rmax,
-                          double &scale, int64_t &nudgedZeroPoint) {
+// This is a specific implementation of nudging:
+// If 0.0 < rmin < rmax or rmin < rmax < 0.0, the range will be shifted
+// to include 0.0, but the range width size (rmax-rmin) isn't changed. The zero
+// point is derived from the shifted range, and the scale isn't changed. As
+// a consequence some values, which are supposeed in the original [rmin, rmax]
+// range will be outside the shifted range and be clamped during quantization.
+// TODO(fengliuai): we should nudge the scale as well, but that requires the
+// fake quant op used in the training to use the nudged scale as well.
+void getNudgedScaleAndZeroPoint(int64_t qmin, int64_t qmax, double rmin,
+                                double rmax, double &scale,
+                                int64_t &nudgedZeroPoint) {
   // Determine the scale.
   const double qminDouble = qmin;
   const double qmaxDouble = qmax;
@@ -100,14 +109,6 @@ UniformQuantizedType fakeQuantAttrsToType(Location loc, unsigned numBits,
                                           double rmin, double rmax,
                                           bool narrowRange, Type expressedType,
                                           bool isSigned) {
-  // Range must straddle zero.
-  // TODO(b/140641593): remove this constraint.
-  if (rmin > 0.0 || rmax < 0.0) {
-    return (emitError(loc, "FakeQuant range must straddle zero: [")
-                << rmin << "," << rmax << "]",
-            nullptr);
-  }
-
   MLIRContext *ctx = expressedType.getContext();
   unsigned flags = isSigned ? QuantizationFlags::Signed : 0;
   Type storageType;
@@ -129,7 +130,7 @@ UniformQuantizedType fakeQuantAttrsToType(Location loc, unsigned numBits,
 
   double scale;
   int64_t nudgedZeroPoint;
-  getScaleAndZeroPoint(qmin, qmax, rmin, rmax, scale, nudgedZeroPoint);
+  getNudgedScaleAndZeroPoint(qmin, qmax, rmin, rmax, scale, nudgedZeroPoint);
 
   return UniformQuantizedType::getChecked(flags, storageType, expressedType,
                                           scale, nudgedZeroPoint, qmin, qmax,
@@ -172,7 +173,7 @@ fakeQuantAttrsToType(Location loc, unsigned numBits, int32_t quantizedDimension,
 
     double scale;
     int64_t nudgedZeroPoint;
-    getScaleAndZeroPoint(qmin, qmax, rmin, rmax, scale, nudgedZeroPoint);
+    getNudgedScaleAndZeroPoint(qmin, qmax, rmin, rmax, scale, nudgedZeroPoint);
     scales.push_back(scale);
     zeroPoints.push_back(nudgedZeroPoint);
   }

mlir/test/Dialect/QuantOps/convert-fakequant-invalid.mlir

@@ -1,27 +1,5 @@
 // RUN: mlir-opt %s -split-input-file -verify-diagnostics -quant-convert-simulated-quantization
 
-// -----
-// Verify that a mismatched range errors.
-func @fakeQuantArgs(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
-^bb0(%arg0: tensor<8x4x3xf32>):
-  // expected-error@+1 {{FakeQuant range must straddle zero: [1.100000e+00,1.500000e+00]}}
-  %0 = "quant.const_fake_quant"(%arg0) {
-    min = 1.1 : f32, max = 1.5 : f32, num_bits = 8
-  } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
-  return %0 : tensor<8x4x3xf32>
-}
-
-// -----
-// Verify that a valid range errors.
-func @fakeQuantArgs(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
-^bb0(%arg0: tensor<8x4x3xf32>):
-  // expected-error@+1 {{FakeQuant range must straddle zero: [1.100000e+00,1.000000e+00}}
-  %0 = "quant.const_fake_quant"(%arg0) {
-    min = 1.1 : f32, max = 1.0 : f32, num_bits = 8
-  } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
-  return %0 : tensor<8x4x3xf32>
-}
-
 // -----
 // Unsupported quantizable type (i1 is currently not a supported element type).
 func @fakeQuantArgs(tensor<8x4x3xi1>) -> tensor<8x4x3xi1> {

mlir/test/Dialect/QuantOps/convert-fakequant.mlir

@@ -47,7 +47,7 @@ func @fakeQuantArgs_Quint8_0_1(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
 
 // -----
 // Verifies a quint8 asymmetric 0..1 range (with narrow_range = true).
-// CHECK_LABEL: fakeQuantArgs_Quint8_NarrowRange
+// CHECK-LABEL: fakeQuantArgs_Quint8_NarrowRange
 func @fakeQuantArgs_Quint8_NarrowRange(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
 ^bb0(%arg0: tensor<8x4x3xf32>):
   // CHECK: %0 = "quant.qcast"(%arg0) : (tensor<8x4x3xf32>)
@@ -62,7 +62,7 @@ func @fakeQuantArgs_Quint8_NarrowRange(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
 
 // -----
 // Verifies a quint8 symmetric range of -1..127/128.
-// CHECK_LABEL: fakeQuantArgs_Quint8_SymmetricRange
+// CHECK-LABEL: fakeQuantArgs_Quint8_SymmetricRange
 func @fakeQuantArgs_Quint8_SymmetricRange(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
 ^bb0(%arg0: tensor<8x4x3xf32>):
   // CHECK: %0 = "quant.qcast"(%arg0) : (tensor<8x4x3xf32>)
@@ -122,7 +122,7 @@ func @fakeQuantArgs_Qint8_0_1(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
 
 // -----
 // Verifies a qint8 asymmetric 0..1 range (with narrow_range = true).
-// CHECK_LABEL: fakeQuantArgs_Qint8_NarrowRange
+// CHECK-LABEL: fakeQuantArgs_Qint8_NarrowRange
 func @fakeQuantArgs_Qint8_NarrowRange(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
 ^bb0(%arg0: tensor<8x4x3xf32>):
   // CHECK: %0 = "quant.qcast"(%arg0) : (tensor<8x4x3xf32>)
@@ -137,7 +137,7 @@ func @fakeQuantArgs_Qint8_NarrowRange(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
 
 // -----
 // Verifies a qint8 symmetric range of -1..127/128.
-// CHECK_LABEL: fakeQuantArgs_Qint8_SymmetricRange
+// CHECK-LABEL: fakeQuantArgs_Qint8_SymmetricRange
 func @fakeQuantArgs_Qint8_SymmetricRange(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
 ^bb0(%arg0: tensor<8x4x3xf32>):
   // CHECK: %0 = "quant.qcast"(%arg0) : (tensor<8x4x3xf32>)
@@ -181,9 +181,41 @@ func @fakeQuantArgs_UnrankedTensor(tensor<f32>) -> tensor<f32> {
   return %0 : tensor<f32>
 }
 
+// -----
+// CHECK-LABEL: fakeQuantArgs_all_positive
+func @fakeQuantArgs_all_positive(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
+^bb0(%arg0: tensor<8x4x3xf32>):
+
+  // CHECK: %[[qc:.*]] = "quant.qcast"(%arg0) : (tensor<8x4x3xf32>)
+  // CHECK-SAME: -> tensor<8x4x3x!quant.uniform<i8:f32, 0.0039215686274509803:-128>>
+  // CHECK-NEXT: "quant.dcast"(%[[qc]]) : (tensor<8x4x3x!quant.uniform<i8:f32, 0.0039215686274509803:-128>>)
+  // CHECK-SAME: -> tensor<8x4x3xf32>
+
+  %0 = "quant.const_fake_quant"(%arg0) {
+    min = 0.5 : f32, max = 1.5 : f32, num_bits = 8, narrow_range = false, is_signed = true
+  } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
+  return %0 : tensor<8x4x3xf32>
+}
+
+// -----
+// CHECK-LABEL: fakeQuantArgs_all_negative
+func @fakeQuantArgs_all_negative(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
+^bb0(%arg0: tensor<8x4x3xf32>):
+
+  // CHECK: %[[qc:.*]] = "quant.qcast"(%arg0) : (tensor<8x4x3xf32>)
+  // CHECK-SAME: -> tensor<8x4x3x!quant.uniform<i8:f32, 0.0039215686274509803:127>>
+  // CHECK-NEXT: "quant.dcast"(%[[qc]]) : (tensor<8x4x3x!quant.uniform<i8:f32, 0.0039215686274509803:127>>)
+  // CHECK-SAME: -> tensor<8x4x3xf32>
+
+  %0 = "quant.const_fake_quant"(%arg0) {
+    min = -1.5 : f32, max = -0.5 : f32, num_bits = 8, narrow_range = false, is_signed = true
+  } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
+  return %0 : tensor<8x4x3xf32>
+}
+
 // -----
 // Verifies a qint8 per axis
-// CHECK_LABEL: fakeQuantPerAxis
+// CHECK-LABEL: fakeQuantPerAxis
 func @fakeQuantPerAxis(tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
 ^bb0(%arg0: tensor<8x4x3xf32>):