%outputs_18, %control_19 = tf_executor.island wraps "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %outputs_16, %outputs_14) {device = "", narrow_range = true, num_bits = 8 : i64} : (tensor<*xf32>, tensor<186xf32>, tensor<186xf32>) -> tensor<*xf32>
    tf_executor.fetch %outputs_18 : tensor<*xf32>
  }
  func.return %0 : tensor<*xf32>

// CHECK: tf_executor.island wraps "tf.FakeQuantWithMinMaxVarsPerChannel"

// WRAPPED-NEXT: tf_executor.graph {

// RUN: tf-opt %s -tfl-raise-custom-ops="test-raise-tf-targets=tf.FakeQuantWithMinMaxVarsPerChannel,tf.FakeQuantWithMinMaxVars" -tfl-prepare-tf | FileCheck --dump-input=always %s
// RUN: tf-opt %s -tfl-raise-custom-ops="test-raise-tf-targets=tf.FakeQuantWithMinMaxVarsPerChannel,tf.FakeQuantWithMinMaxVars" -tfl-prepare-tf=use-fake-quant-num-bits=true | FileCheck --check-prefix LOBIT --dump-input=always %s

// RUN: tf-opt %s -tfl-raise-custom-ops="test-raise-tf-targets=tf.FakeQuantWithMinMaxVarsPerChannel,tf.FakeQuantWithMinMaxVars" -tfl-prepare-tf | FileCheck --dump-input=always %s
// RUN: tf-opt %s -tfl-raise-custom-ops="test-raise-tf-targets=tf.FakeQuantWithMinMaxVarsPerChannel,tf.FakeQuantWithMinMaxVars" -tfl-prepare-tf=use-fake-quant-num-bits=true | FileCheck --check-prefix LOBIT --dump-input=always %s

  %arg2 = arith.constant dense<[255.0, 254.0, 256.0]> : tensor<3xf32>
  %0 = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %arg1, %arg2) {num_bits = 5, narrow_range = false} : (tensor<8x3xf32>, tensor<3xf32>, tensor<3xf32>) -> tensor<8x3xf32>
  func.return %0 : tensor<8x3xf32>

// CHECK:  %[[fq:.*]] = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %cst, %cst_0)

  %arg2 = arith.constant dense<[15.0, 14.0, 16.0]> : tensor<3xf32>
  %0 = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %arg1, %arg2) {num_bits = 3, narrow_range = false} : (tensor<8x3xf32>, tensor<3xf32>, tensor<3xf32>) -> tensor<8x3xf32>
  func.return %0 : tensor<8x3xf32>

// CHECK:  %[[fq:.*]] = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %cst, %cst_0)

      list {
        s: "loc:@BoxPredictor_4/ClassPredictor/weights_quant/max"
      }
    }
  }
}
node {
  name: "BoxPredictor_4/ClassPredictor/weights_quant/FakeQuantWithMinMaxVarsPerChannel"
  op: "FakeQuantWithMinMaxVarsPerChannel"
  input: "BoxPredictor_4/ClassPredictor/weights/read"
  input: "BoxPredictor_4/ClassPredictor/weights_quant/min/read"
  input: "BoxPredictor_4/ClassPredictor/weights_quant/max/read"

      }
    }
  }
}
node {
  name: "BoxPredictor_4/ClassPredictor/weights_quant/FakeQuantWithMinMaxVarsPerChannel"
  op: "FakeQuantWithMinMaxVarsPerChannel"
  input: "BoxPredictor_4/ClassPredictor/weights/read"
  input: "BoxPredictor_4/ClassPredictor/weights_quant/min"
  input: "BoxPredictor_4/ClassPredictor/weights_quant/max"
  attr {

      }
    }
  }
}
node {
  name: "BoxPredictor_4/ClassPredictor/weights_quant/FakeQuantWithMinMaxVarsPerChannel"
  op: "FakeQuantWithMinMaxVarsPerChannel"
  input: "BoxPredictor_4/ClassPredictor/weights/read"
  input: "BoxPredictor_4/ClassPredictor/weights_quant/min"
  input: "BoxPredictor_4/ClassPredictor/weights_quant/max"
  attr {

      list {
        s: "loc:@BoxPredictor_4/ClassPredictor/weights_quant/max"
      }
    }
  }
}
node {
  name: "BoxPredictor_4/ClassPredictor/weights_quant/FakeQuantWithMinMaxVarsPerChannel"
  op: "FakeQuantWithMinMaxVarsPerChannel"
  input: "BoxPredictor_4/ClassPredictor/weights/read"
  input: "BoxPredictor_4/ClassPredictor/weights_quant/min/read"
  input: "BoxPredictor_4/ClassPredictor/weights_quant/max/read"

}

// -----

// Test valid tf.FakeQuantWithMinMaxVarsPerChannel
// CHECK-LABEL: func @FakeQuantWithMinMaxVarsPerChannel
func.func @FakeQuantWithMinMaxVarsPerChannel(tensor<1x2x3x8xf32>, tensor<8xf32>, tensor<8xf32>) -> tensor<1x2x3x8xf32> {
^bb0(%arg0: tensor<1x2x3x8xf32>, %arg1: tensor<8xf32>, %arg2: tensor<8xf32>):