// -----

// CHECK-LABEL: func @sign
// CHECK-SAME: [[ARG:%arg.*]]: tensor<1x2x3x4xf32>
func.func @sign(%arg0: tensor<1x2x3x4xf32>) -> tensor<1x2x3x4xf32> {
  // CHECK: [[SIGN:%.*]] = mhlo.sign [[ARG]]
  // CHECK: return [[SIGN]] : tensor<1x2x3x4xf32>
  %0 = "tf.Sign"(%arg0) : (tensor<1x2x3x4xf32>) -> (tensor<1x2x3x4xf32>)
  func.return %0 : tensor<1x2x3x4xf32>
}

// -----

// CHECK-LABEL: func @sign_dynamic

//
// ```
// %0 = stablehlo.constant dense<3>
// %1 = stablehlo.constant dense<4>
// %2 = stablehlo.constant dense<2>
// %3 = stablehlo.convolution(%%arg0, %%arg1) :
//          (tensor<?x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<?x3x4x2xf32>
// %4 = stablehlo.get_dimension_size %3, dim = 0 :
//          (tensor<?x3x4x2xf32>) -> tensor<i32>
// %5 = stablehlo.reshape %4 :
//          (tensor<i32>) -> tensor<1xi32>

func.func @FakeQuantWithMinMaxVarsPerChannel(tensor<1x2x3x8xf32>, tensor<8xf32>, tensor<8xf32>) -> tensor<1x2x3x8xf32> {
^bb0(%arg0: tensor<1x2x3x8xf32>, %arg1: tensor<8xf32>, %arg2: tensor<8xf32>):
  %0 = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %arg1, %arg2) : (tensor<1x2x3x8xf32>, tensor<8xf32>, tensor<8xf32>) -> tensor<1x2x3x8xf32>
  func.return %0 : tensor<1x2x3x8xf32>
}

// -----

      rhs_contracting_dimensions = [2]
    >,
    precision_config = [#stablehlo<precision DEFAULT>, #stablehlo<precision DEFAULT>]
  } : (tensor<1x2x3x4xf32>, tensor<1x2x4x5xf32>) -> tensor<1x2x3x5xf32>
  return %0 : tensor<1x2x3x5xf32>
}
// Do nothing for float operands
// CHECK: stablehlo.dot_general
// CHECK-NOT: tfl.batch_matmul

// -----

  //
  // For example,
  //
  //   %shape  = tf.Shape(%arg)                   // %arg: tensor<?x2x3x1xf32>
  //   %height = tf.StridedSlice(%shape, 1, 2, 1)
  //
  // In this case %height can be replaced with a constant 2.
  //
  // Or,
  //
  //   %shape  = tf.Shape(%arg)                   // %arg: tensor<?x2x3x1xf32>
  //   %spatial_shape = tf.StridedSlice(%shape, 1, 3, 1)
  //