# MLIR:         %[[weight:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<186x1x1x256x!quant.uniform<i4<-7:7>:f32:0, {2.2825599397931779,
# MLIR:         %[[conv:.*]] = "tfl.conv_2d"(%[[ARG_0]], %[[weight]], %[[bias]]) <{dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32}

// Tests if reduce_window op following quantized function is quantized.

module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 1722 : i32}, tf_saved_model.semantics} {
  // CHECK-LABEL: main_00
  // CHECK-SAME: %[[ARG0:.*]]: tensor<2x3x1x1024xf32>

    %0 = "tfl.pack"(%arg0, %arg1) {axis = 0 : i32, tac.device = "CPU", values_count = 2 : i32} : (tensor<100xf32>, tensor<100xf32>) -> tensor<2x100xf32>
    func.return %0 : tensor<2x100xf32>
  }

    arithmetic operations.

    Example:

    ```mlir
    %1 = "tfr.constant"() { value: i32 } : () -> !tfr.attr
    %2 = "tfr.constant"() { value: [i32, f32] } : () -> !tfr.attr
    %3 = tfr.constant [i32, f32] -> !tfr.attr
    %4 = tfr.constant f32 -> !tfr.attr
    ```
  }];

  let arguments = (ins TFR_allowedConstValues:$value);

# MLIR:         %[[weight:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<186x1x1x256x!quant.uniform<i8<-127:127>:f32:0, {0.12581039038230116,
# MLIR:         %[[conv:.*]] = "tfl.conv_2d"(%[[ARG_0]], %[[weight]], %[[bias]]) <{dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32}

    %cst_0 = "tf.Const"() {device = "", value = dense<[[-0.211145893, -0.708605706], [-0.954062759, -0.614013135]]> : tensor<2x2xf32>} : () -> tensor<2x2xf32>
    %cst_1 = "tf.Const"() { value = dense<-1> : tensor<i32> } : () -> tensor<i32>

# MLIR:         %[[weight:.*]] = "tfl.pseudo_qconst"() <{qtype = tensor<186x1x1x256x!quant.uniform<i4<-7:7>:f32:0, {2.2825599397931779,
# MLIR:         %[[conv:.*]] = "tfl.conv_2d"(%[[ARG_0]], %[[weight]], %[[bias]]) <{dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32}

		//
		// 	(import "gojs" "add" (func (param i32)))
		wi.Params = []obj.WasmField{{Type: obj.WasmI32}}
	} else {
		// All other imported functions use the normal WASM ABI.
		// Example:
		//
		// 	//go:wasmimport a_module add
		// 	func importedAdd(a, b uint) uint
		//
		// will roughly become
		//
		// 	(import "a_module" "add" (func (param i32 i32) (result i32)))
		abiConfig := AbiForBodylessFuncStackMap(f)

    <BTrue>   true   </BTrue>
    <I>   266703   </I>
    <INeg>   -266703   </INeg>
    <I8>  112  </I8>
    <I8Neg>  -112  </I8Neg>
    <I16>  6703  </I16>
    <I16Neg>  -6703  </I16Neg>
    <I32>  266703  </I32>
    <I32Neg>  -266703  </I32Neg>
    <I64>  266703  </I64>
    <I64Neg>  -266703  </I64Neg>
    <UI>   266703   </UI>
    <UI8>  112  </UI8>
    <UI16>  6703  </UI16>
    <UI32>  266703  </UI32>

    %4 = stablehlo.constant dense<4.000000e-01> : tensor<1x1x1xf32>  // Input 2 inverse scale (1 / s2).
    %5 = stablehlo.constant dense<0> : tensor<1x1x1xi8>  // Input 2 zero point (z2).
    %6 = stablehlo.constant dense<0> : tensor<1x1x1xi32>  // Input 2 zero point (z2) (upcast & folded into i32).