// CHECK-PER-TENSOR: %[[CONST_0:.+]] = stablehlo.constant() <{value = dense<{{.*}}> : tensor<2x3x3x2xi8>}> : () -> tensor<2x3x3x2x!quant.uniform<i8<-127:127>:f32, {{.*}}>
// CHECK-PER-TENSOR: %[[UNIFORM_QUANTIZE_0:.+]] = stablehlo.uniform_quantize %[[ARG_0]] : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3x!quant.uniform<i8:f32, {{.*}}>>
// CHECK-PER-TENSOR: %[[CALL_0:.+]] = call @quantized_conv_fn(%[[UNIFORM_QUANTIZE_0]], %[[CONST_0]])

// parameterized type or function value.
func (check *Checker) rawExpr(T *target, x *operand, e ast.Expr, hint Type, allowGeneric bool) exprKind {
	if check.conf._Trace {
		check.trace(e.Pos(), "-- expr %s", e)
		check.indent++
		defer func() {
			check.indent--
			check.trace(e.Pos(), "=> %s", x)
		}()
	}

	kind := check.exprInternal(T, x, e, hint)

	if !allowGeneric {
		check.nonGeneric(T, x)
	}

// parameterized type or function value.
func (check *Checker) rawExpr(T *target, x *operand, e syntax.Expr, hint Type, allowGeneric bool) exprKind {
	if check.conf.Trace {
		check.trace(e.Pos(), "-- expr %s", e)
		check.indent++
		defer func() {
			check.indent--
			check.trace(e.Pos(), "=> %s", x)
		}()
	}

	kind := check.exprInternal(T, x, e, hint)

	if !allowGeneric {
		check.nonGeneric(T, x)
	}

  func.return
}

// CHECK: [[CONST:%.*]] = "tf.Const"
// CHECK: [[VAR:%.*]] = "tf.VarHandleOp"
// CHECK: "tf_device.cluster"() ({
// CHECK:   "tf.opA"() ({
// CHECK:     "tf.AssignAddVariableOp"([[VAR]], [[CONST]])
// CHECK:    })
// CHECK:    "tf.opB"()
// CHECK:    tf_device.return
// CHECK:  })
// CHECK-SAME: _replication_info = "foo"
// CHECK: "tf.AssignAddVariableOp"([[VAR]], [[CONST]])

// CHECK-SAME: effective_hidden_scale_intermediate = tensor<!quant.uniform<i8:f32, 0.0039215686274509803:-1>>
// CHECK-SAME: input_to_cell_intermediate = tensor<!quant.uniform<i16<-32767:32767>:f32, 1.2207403790398877E-4>>
// CHECK-SAME: input_to_forget_intermediate = tensor<!quant.uniform<i16<-32767:32767>:f32, 4.8829615161595508E-4>>
// CHECK-SAME: input_to_input_intermediate = tensor<!quant.uniform<i16<-32767:32767>:f32, 9.7659230323191015E-4>>

// CHECK: %[[XLA_CALL_MODULE:.*]] = "tf.XlaCallModule"(%arg0, %[[CONST]])
// CHECK: return %[[XLA_CALL_MODULE:.*]] : tensor<1x1x64xf32>
// CHECK: }

// CHECK-LABEL: private @composite_dot_general_fn_1
// CHECK: %[[DOT_GENERAL:.*]] = stablehlo.dot_general %arg0, %arg1
// CHECK: return %[[DOT_GENERAL:.*]] : tensor<1x1x64xf32>
// CHECK: }

// -----

// CHECK-LABEL: @dot_general_with_bias_same_shape_fn(

    // CHECK: [[GRAD_SQUARE:%.*]] = "tf.Square"([[GRAD]])
    // CHECK: [[V_DELTA:%.*]] = "tf.Mul"([[ONE_MINUS_BETA2]], [[GRAD_SQUARE]])
    // CHECK: [[NEW_V:%.*]] = "tf.AddV2"([[BETA2_OLD_V]], [[V_DELTA]])
    // CHECK: [[ALPHA_NEW_M:%.*]] = "tf.Mul"([[ALPHA]], [[NEW_M]])
    // CHECK: [[SQRT_NEW_V:%.*]] = "tf.Sqrt"([[NEW_V]])
    // CHECK: [[SQRT_NEW_V_EPSILON:%.*]] = "tf.AddV2"([[SQRT_NEW_V]], [[EPSILON]])

	if goos == "darwin" || ((goos == "linux" || goos == "windows") && goarch == "amd64") {
		t.registerTest("API release note check", &goTest{variant: "check", pkg: "cmd/relnote", testFlags: []string{"-check"}})
		t.registerTest("API check", &goTest{variant: "check", pkg: "cmd/api", timeout: 5 * time.Minute, testFlags: []string{"-check"}})
	}

	// Runtime CPU tests.
	if !t.compileOnly && t.hasParallelism() {
		for i := 1; i <= 4; i *= 2 {

  func.return %4: tensor<2x4xf32>

// CHECK-NEXT: %[[q:.*]] = "tfl.quantize"(%arg0)
// CHECK-NEXT: %[[dq:.*]] = "tfl.dequantize"(%[[q]])
// CHECK-NEXT: %[[q_0:.*]] = "tfl.quantize"(%arg1)
// CHECK-NEXT: %[[dq_0:.*]] = "tfl.dequantize"(%[[q_0]])
// CHECK-NEXT: %[[c:.*]] = "tfl.concatenation"(%[[dq]], %[[dq_0]])
// CHECK-NEXT: %[[q_1:.*]] = "tfl.quantize"(%[[c]])
// CHECK-NEXT: %[[dq_1:.*]] = "tfl.dequantize"(%[[q_1]])

  func.return %2 : tensor<2x1xf32>

// CHECK: %cst = arith.constant
// CHECK: %[[rs:.*]] = "tf.Reshape"
// CHECK-SAME: -> tensor<2x1xf32>
// CHECK: %[[q:.*]] = "tfl.quantize"(%[[rs]]) <{qtype = tensor<2x1x!quant.uniform<u8:f32, 1.000000e+00>>}>
// CHECK-SAME: -> tensor<2x1x!quant.uniform<u8:f32, 1.000000e+00>>
// CHECK: %[[dq:.*]] = "tfl.dequantize"(%[[q]])
// CHECK-SAME: -> tensor<2x1xf32>
// CHECK: return %[[dq]]
}