// CHECK: "tfl.slice"

// -----

func.func @fullyConnectedToConv(%arg0: tensor<384x384xf32>, %arg1: tensor<512x384xf32>, %arg2: tensor<512xf32>) -> tensor<384x512xf32> {
  %0 = "tfl.fully_connected"(%arg0, %arg1, %arg2) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<384x384xf32>, tensor<512x384xf32>, tensor<512xf32>) -> tensor<384x512xf32>
  func.return %0: tensor<384x512xf32>
}

  func.return %1 : tensor<5x2x3x4xf32>
}

// CHECK: %cst = arith.constant dense<1.000000e+00> : tensor<5x2x3x4xf32>
// CHECK: %0 = "tfl.transpose"(%arg0, %arg1) : (tensor<2x3x4x5xf32>, tensor<4xi32>) -> tensor<5x2x3x4xf32>
// CHECK: %1 = tfl.add %0, %cst {fused_activation_function = "NONE"} : tensor<5x2x3x4xf32>
// CHECK: return %1 : tensor<5x2x3x4xf32>

// -----

// CHECK-LABEL: doubleTposeInput

BASIC>, proj_clip = 2.000000e+00 : f32}> {asymmetric_quantize_inputs = false} : (tensor<1x384xf32>, tensor<1x96xf32>, tensor<384x480xf32>, tensor<384xf32>, tensor<1x96xf32>) -> (tensor<1x96xf32>, tensor<1x96xf32>, tensor<1x480xf32>, tensor<1x384xf32>)

  %0:4 = "tfl.basic_lstm"(%arg0, %arg1, %arg2, %arg3, %arg4) {fused_activation_function = "RELU", cell_clip = 1.0 : f32, proj_clip = 2.0 : f32} : (tensor<1x384xf32>, tensor<1x96xf32>, tensor<384x480xf32>, tensor<384xf32>, tensor<1x96xf32>) -> (tensor<1x96xf32>,...

// CHECK-LABEL: testBasicLstm
func.func @testBasicLstm(%arg0: tensor<1x384xf32>, %arg1: tensor<1x96xf32>, %arg2: tensor<384x480xf32>, %arg3: tensor<384xf32>, %arg4: tensor<1x96xf32>) -> (tensor<1x96xf32>, tensor<1x96xf32>) {