etcd_request_duration_seconds_bucket{operation="foo",type="bar",le="1"} 1
etcd_request_duration_seconds_bucket{operation="foo",type="bar",le="1.25"} 1
etcd_request_duration_seconds_bucket{operation="foo",type="bar",le="1.5"} 1
etcd_request_duration_seconds_bucket{operation="foo",type="bar",le="2"} 1
etcd_request_duration_seconds_bucket{operation="foo",type="bar",le="3"} 1

      apiserver_watch_cache_read_wait_seconds_bucket{resource="pods",le="1"} 1
      apiserver_watch_cache_read_wait_seconds_bucket{resource="pods",le="1.25"} 1
      apiserver_watch_cache_read_wait_seconds_bucket{resource="pods",le="1.5"} 1
      apiserver_watch_cache_read_wait_seconds_bucket{resource="pods",le="2"} 1
      apiserver_watch_cache_read_wait_seconds_bucket{resource="pods",le="3"} 1

  %1 = "quantfork.dcast"(%0) : (tensor<*x!quant.uniform<i8:f32, 5.000000e-02:-10>>) -> tensor<*xf32>
  %2 = "tf.MaxPool"(%1) {data_format = "NHWC", device = "", explicit_paddings = [], ksize = [1, 2, 2, 1], padding = "VALID", strides = [1, 2, 2, 1]} : (tensor<*xf32>) -> tensor<*xf32>
  %3 = "quantfork.qcast"(%2) {volatile} : (tensor<*xf32>) -> tensor<*x!quant.uniform<i8:f32, 5.000000e-02:-10>>

        '[1.0,1.3]'             | '1.2'                       | true         | '1.3' // should probably choose 1.2 instead
        '1.2'                   | '[1.0,1.3]'                 | false        | '1.2'
        '[1.0,1.2]'             | '[1.0, 1.3]'                | true         | '1.2'
        '[1.0,1.3]'             | '[1.0,1.2]'                 | true         | '1.3' // should probably choose 1.2 instead
    }

func.func @conv2d_backprop_input_with_add(%arg0: tensor<4xi32>, %arg1: tensor<3x3x1x32xf32>, %arg2: tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32> {
  %0 = "tf.Conv2DBackpropInput"(%arg0, %arg1, %arg2) {strides = [1, 2, 2, 1], padding="SAME", dilations=[1, 1, 1, 1]}: (tensor<4xi32>, tensor<3x3x1x32xf32>, tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32>
  %1 = "tf.Const"() {value = dense<1.000000e+00> : tensor<1xf32>} : () -> tensor<1xf32>

// Check that the body is not modified.
// CHECK: %[[REDUCE_WINDOW:.+]] = "stablehlo.reduce_window"(%[[ARG]], %[[INIT_VALUE_CONST]])
// CHECK: <{base_dilations = array<i64: 1, 2, 2, 1>, window_dilations = array<i64: 1, 2, 2, 1>, window_dimensions = array<i64: 1, 2, 2, 1>, window_strides = array<i64: 1, 2, 2, 1>}>
// CHECK: ^bb0(%[[REDUCE_ARG_0:.+]]: tensor<f32>, %[[REDUCE_ARG_1:.+]]: tensor<f32>):
// CHECK: %[[MAX:.+]] = stablehlo.maximum %[[REDUCE_ARG_0]], %[[REDUCE_ARG_1]]

            def details = args[0]
            Collection<ComponentResolutionState> candidates = details.candidates
            assert candidates*.version == ['1.2', '1.1']
            details.select(candidates.find { it.version == '1.2' })
        }
        1 * conflictResolver.select(!null) >> { args ->
            def details = args[0]
            Collection<ComponentResolutionState> candidates = details.candidates

    %conv = "tf.Conv2D"(%arg0, %arg1) {attr_map = "0:strides,1:use_cudnn_on_gpu,2:padding,3:explicit_paddings,4:dilations", data_format = "NHWC", device = "", dilations = [1, 2, 2, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x2x2x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32>
    return %conv : tensor<*xf32>
  }

kubelet_image_pull_duration_seconds_bucket{image_size_in_bytes="0-10MB",le="30"} 1
kubelet_image_pull_duration_seconds_bucket{image_size_in_bytes="0-10MB",le="60"} 1
kubelet_image_pull_duration_seconds_bucket{image_size_in_bytes="0-10MB",le="120"} 1
kubelet_image_pull_duration_seconds_bucket{image_size_in_bytes="0-10MB",le="180"} 1
kubelet_image_pull_duration_seconds_bucket{image_size_in_bytes="0-10MB",le="240"} 1

    %conv = "tf.Conv2D"(%arg0, %arg1) {attr_map = "0:strides,1:use_cudnn_on_gpu,2:padding,3:explicit_paddings,4:dilations", data_format = "NHWC", device = "", dilations = [1, 2, 2, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x2x2x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32>
    return %conv : tensor<*xf32>
  }