// CHECK: %[[dq0:.*]] = "quantfork.dcast"(%[[q0]])
// CHECK-SAME: quant.uniform<i8:f32, 0.010039215461880554:-1>
// CHECK: %[[maxpool:.*]] = "tf.MaxPool"(%[[dq0]])
// CHECK: %[[q1:.*]] = "quantfork.qcast"(%[[maxpool]])
// CHECK-SAME: quant.uniform<i8:f32, 0.010039215461880554:-1>
// CHECK: %[[dq1:.*]] = "quantfork.dcast"(%[[q1]])
// CHECK-SAME: quant.uniform<i8:f32, 0.010039215461880554:-1>
// CHECK: %[[reshape:.*]] = "tf.Reshape"(%[[dq1]]

	// func(p1 int6, p2 s, p3 int64)
	//   (r1 s, r2 int8, r3 int32) {
	i8 := types.Types[types.TINT8]
	i16 := types.Types[types.TINT16]
	i32 := types.Types[types.TINT32]
	i64 := types.Types[types.TINT64]
	s := mkstruct(i8, i8, mkstruct(), i8, i16)
	ft := mkFuncType(nil, []*types.Type{i8, s, i64},
		[]*types.Type{s, i8, i32})

	exp := makeExpectedDump(`
        IN 0: R{ I0 } spilloffset: 0 typ: int8

// CHECK-DAG: %[[input_0:.*]] = "tfl.dequantize"({{.*}}) : (tensor<1x1x5x!quant.uniform<i8:f32, 0.010588235481112611:-15>>) -> tensor<1x1x5xf32>
// CHECK-DAG: %[[input_1:.*]] = "tfl.dequantize"({{.*}}) : (tensor<2x5x!quant.uniform<i8<-127:127>:f32, 0.011122002376346137>>) -> tensor<2x5xf32>
// CHECK-DAG: %[[input_2:.*]] = "tfl.dequantize"({{.*}}) : (tensor<2x5x!quant.uniform<i8<-127:127>:f32, 0.018341723389512912>>) -> tensor<2x5xf32>

/// Examples:
/// 1. realValue is a primitive value attribute:
/// (realValue: FloatAttr, quantizedElementType: UniformQuantizedType[i8:f32])
///   -> (IntegerAttr, outConvertedType: i8)
/// 2. realValue is an elements attribute:
/// (realValue: DenseElementsAttr[tensor<2x2xf32>],
///  quantizedElementType: UniformQuantizedType[i8:f32])
///   -> (DenseElementsAttr[tensor<2x2xi8>], outConvertedType: tensor<2x2xi8>)
Attribute quantizeAttr(Attribute realValue,

// CHECK-DAG: %[[CONST:.*]] = arith.constant dense<0.000000e+00> : tensor<2x1024xf32>
// CHECK: %0 = "quantfork.qcast"(%[[CONST]]) : (tensor<2x1024xf32>) -> tensor<2x1024x!quant.uniform<i8<-127:127>:f32, 3.9370078740157481E-9>>
// CHECK: %1 = "quantfork.dcast"(%0) : (tensor<2x1024x!quant.uniform<i8<-127:127>:f32, 3.9370078740157481E-9>>) -> tensor<2x1024xf32>

    %1 = "quantfork.dcast"(%0) : (tensor<2x2x3x2x!quant.uniform<i8<-127:127>:f32:3, {4.000000e-03,5.000000e-03}>>) -> tensor<*xf32>
    %2 = "quantfork.qcast"(%arg0) : (tensor<1x2x2x3xf32>) -> tensor<1x2x2x3x!quant.uniform<i8:f32, 8.000000e-03>>
    %3 = "quantfork.dcast"(%2) : (tensor<1x2x2x3x!quant.uniform<i8:f32, 8.000000e-03>>) -> tensor<*xf32>

  %0 = stablehlo.convolution(%arg0, %arg1) dim_numbers = [b, f, 0, 1]x[o, i, 0, 1]->[b, f, 0, 1], window = {pad = [[1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x4x3x3x!quant.uniform<i8:f32, 1.000000e+0:-100>>, tensor<2x4x3x3x!quant.uniform<i8:f32:0,...

@testLstmIntermediates(%arg0: tensor<1x528x!quant.uniform<i8:f32, 0.037248000502586365:-19>>, %arg1: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.059801999479532242>>, %arg2: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.031925998628139496>>, %arg3: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.056272000074386597>>, %arg4: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.063763998448848724>>, %arg5: tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.013358999975025654>>, %arg6: tenso...

// CHECK: %[[Q_WEIGHT_PER_TENSOR:.*]] = "quantfork.qcast"(%[[WEIGHT_CONST]]) {{.*}} (tensor<2x3x3x2xf32>) -> tensor<2x3x3x2x!quant.uniform<i8:f32, {{.*}}>>
// CHECK: %[[DQ_WEIGHT:.*]] = "quantfork.dcast"(%[[Q_WEIGHT_PER_TENSOR]])

// CHECK: %[[Q_ACTIVATION:.*]] = "quantfork.qcast"(%[[ARG_0]])
// CHECK-SAME: -> tensor<1x3x2x3x!quant.uniform<i8:f32, 0.018920717052384919:-128>>
// CHECK: %[[DQ_ACTIVATION:.*]] = "quantfork.dcast"(%[[Q_ACTIVATION]])

	use(p1k[i])
	use(p100k[i])

	use(s[ui])
	use(a1[ui])
	use(a1k[ui])
	use(a100k[ui])
	use(p1[ui])
	use(p1k[ui])
	use(p100k[ui])

	use(s[i8])
	use(a1[i8])
	use(a1k[i8])
	use(a100k[i8])
	use(p1[i8])
	use(p1k[i8])
	use(p100k[i8])

	// Unsigned 8-bit numbers don't need checks for len >= 2⁸.
	use(s[ui8])
	use(a1[ui8])
	use(a1k[ui8])   // ERROR "index bounds check elided"