// CHECK-LABEL: fused_conv2d
func.func @fused_conv2d(%input: tensor<1x300x300x40xi8>,
                        %filter: tensor<3x3x40x40xi8>,
                        %bias: tensor<40xf32>,
                        %act: tensor<0xi8>) -> tensor<1x300x300x40xi8> {

  // CHECK:       %[[v0:.*]] = mhlo.constant dense<1.000000e+00> : tensor<f32>
  // CHECK-NEXT:  %[[v1:.*]] = mhlo.constant dense<2.000000e+00> : tensor<f32>

// CHECK: %[[maxpool:.*]] = "tf.MaxPool"(%[[conv_quant]]) <{data_format = "NHWC", ksize = [1, 2, 2, 1], padding = "VALID", strides = [1, 1, 1, 1]}> : (tensor<*xi8>) -> tensor<*xi8>
// CHECK: %[[dequantize:.*]] = "tf.PartitionedCall"(%[[maxpool]]
// CHECK-SAME: f = @dequantize_i8
// CHECK: return %[[dequantize]]

    %26 = "tf.Cast"(%25) {Truncate = false} : (tensor<2xi64>) -> tensor<2xf32>
    %27 = "tf.Equal"(%14, %26) {incompatible_shape_error = true} : (tensor<2xf32>, tensor<2xf32>) -> tensor<2xi1>
    %28 = "tf.Cast"(%27) {Truncate = false} : (tensor<2xi1>) -> tensor<2xf32>
    %29 = "tf.Sum"(%28, %6) {keep_dims = false} : (tensor<2xf32>, tensor<1xi32>) -> tensor<f32>
    %30 = "tf.CrossReplicaSum"(%29, %3) : (tensor<f32>, tensor<1x2xi32>) -> tensor<f32>

    %cst_7 = "tfl.pseudo_qconst"() {qtype = tensor<20x!quant.uniform<i8:f32, 0.006:-34>>, value = dense<1> : tensor<20xi8>} : () -> tensor<20x!quant.uniform<i8:f32, 0.006:-34>>
    %cst_11 = "tfl.pseudo_qconst"() {qtype = tensor<20x28x!quant.uniform<i8:f32, 0.006:-34>>, value = dense<1> : tensor<20x28xi8>} : () -> tensor<20x28x!quant.uniform<i8:f32, 0.006:-34>>

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