// CHECK-SAME: %[[ARG:.+]]: tensor<1x3x3x4x!quant.uniform<i8:f32, 3.000000e+00:-100>>
// CHECK-DAG: %[[QCONST_0:.+]] = "tfl.pseudo_qconst"() <{qtype = tensor<2x3x3x4x!quant.uniform<i8<-127:127>:f32:0, {2.000000e+02,3.000000e+03}>>, value = dense<3> : tensor<2x3x3x4xi8>}> : () -> tensor<2x3x3x4x!quant.uniform<i8<-127:127>:f32:0, {2.000000e+02,3.000000e+03}>>

    %0 = stablehlo.convert %arg0 : (tensor<1x3x3x4xf32>) -> tensor<1x3x3x4xi8>
    return %0 : tensor<1x3x3x4xi8>
  }
// CHECK: @uniform_quantize_1
  func.func private @uniform_dequantize_0(%arg0: tensor<1x3x3x4xi8>, %arg1: tensor<1x1x1x1xf32>, %arg2: tensor<1x1x1x1xi8>) -> tensor<1x3x3x4xf32> {
    %0 = stablehlo.convert %arg0 : (tensor<1x3x3x4xi8>) -> tensor<1x3x3x4xf32>

  %1 = "tfl.pseudo_qconst"() {qtype = tensor<32x3x3x3x!quant.uniform<i8<-127:127>:f32, 0.021826678373682216:151>>, value = dense<-76> : tensor<32x3x3x3xi8>} : () -> tensor<32x3x3x3x!quant.uniform<i8<-127:127>:f32, 0.021826678373682216>>

// CHECK-NEXT:   %{{.*}} = "tfl.pseudo_qconst"() <{qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678{{[0-9]*}}:151>>, value = dense<-76> : tensor<32x3x3x3xi8>}> : () -> tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678{{[0-9]*}}:151>>

    return %0 : tensor<1x3x4x2xf32>
  }
}

// CHECK-LABEL: quantize_conv_per_tensor
// CHECK-SAME: %[[ARG0:.+]]: tensor<1x3x4x3xf32>
// CHECK: %[[CST:.+]] = stablehlo.constant() <{value = dense<127> : tensor<2x3x3x2xi8>}> : () -> tensor<2x3x3x2x!quant.uniform<i8<-127:127>:f32, 0.0023622048182750312>>

// CHECK: func.func private @quantize_conv_fn(%[[ARG_0:.+]]: tensor<1x3x4x3xf32>) -> tensor<1x3x4x2xf32> attributes {tf._original_func_name = "main_0"}
// CHECK: %[[CONST_0:.+]] = stablehlo.constant() <{value = dense<{{.*}}> : tensor<2x3x3x2xi8>}> : () -> tensor<2x3x3x2x!quant.uniform<i8<-127:127>:f32:3, {{.*}}>
// CHECK: %[[UNIFORM_QUANTIZE_0:.+]] = stablehlo.uniform_quantize %[[ARG_0]] : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3x!quant.uniform<i8:f32, {{.*}}>>

  %weight_zps = "tf.Const"() { value = dense<3> : tensor<i32> } : () -> tensor<i32>

  // CHECK: %[[CONST:.*]] = mhlo.constant()
  // CHECK-SAME{LITERAL} value = dense<127> : tensor<2x3x3x2xi8>
  // CHECK-SAME: tensor<2x3x3x2x!quant.uniform<i8:f32, 1.000000e+00:3>>
  // CHECK: mhlo.convolution(%arg0, %[[CONST]])
  // CHECK-SAME{LITERAL}: dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f]

  return %2 : tensor<?x2x2x1xi32>
}

// -----

// CHECK-LABEL: func @convolution_add_add_static
func.func @convolution_add_add_static(
    %lhs: tensor<2x3x2x1xi8>, %rhs: tensor<2x1x1x1xi8>,
    %zp_offset: tensor<2x2x2x1xi32>, %bias: tensor<1xi32>
  ) -> tensor<2x2x2x1xi32> {
  // CHECK-DAG: %[[conv:.*]] = mhlo.convolution

func.func @test_depthwise_conv2d_replace_float(%arg0: tensor<1x224x224x3xf32>) -> tensor<1x112x112x32xf32> {
  // CHECK-DAG: %[[VAL0:.+]] = "tfl.pseudo_qconst"() <{qtype = tensor<32x3x3x3x!quant.uniform<{{.+}}>>, value = dense<42> : tensor<32x3x3x3xi8>}>
  // CHECK-DAG: %[[VAL1:.+]] = "tfl.pseudo_qconst"() <{qtype = tensor<32x!quant.uniform<{{.+}}>>, value = dense<0> : tensor<32xi32>}>

  %1 = "tfl.pseudo_qconst"() {qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>, value = dense<-76> : tensor<32x3x3x3xi8>} : () -> tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.021826678373682216:151>>