// CHECK: %[[q:.*]] = "tfl.quantize"(%[[w]]) <{qtype = tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.003937007874015748:1>>}> {volatile} : (tensor<32x3x3x3xf32>) -> tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.003937007874015748:1>>
// CHECK: %[[dq:.*]] = "tfl.dequantize"(%[[q]]) : (tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 0.003937007874015748:1>>) -> tensor<32x3x3x3xf32>

// CHECK:         }

// -----

module {
func.func @constWeight(%arg0: tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32> {
  %0 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<16x3x3x3xf32>} : () -> tensor<16x3x3x3xf32>
  %1 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<16xf32>} : () -> tensor<16xf32>

// CHECK:  %0 = "tf.Transpose"(%arg1, %[[CONSTANT0]]) : (tensor<3x3x3x16xf32>, tensor<4xi32>) -> tensor<16x3x3x3xf32>
// CHECK:  %1 = "tfl.conv_2d"(%arg0, %0, %[[CONSTANT]]) <{dilation_h_factor = 2 : i32, dilation_w_factor = 3 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 4 : i32, stride_w = 5 : i32}> : (tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32>
// CHECK:  %2 = "tf.Conv2D"