// division can result in strange behavior.
//
//      floordiv = cast(floordiv(cast(left), cast(right))))
//
//   %left_cast = cast(%left)
//   %right_cast = cast(%right)
//   %div = div(%left, %left)
//   %floored = floor(%div)
//   %floored_cast = cast(%floored)
//
// Required to manually specify the intermediate types.

- [`KT-54443`](https://youtrack.jetbrains.com/issue/KT-54443) Smart cast to non-null after safe-call in require
- [`KT-25747`](https://youtrack.jetbrains.com/issue/KT-25747) DFA variables: propagate smart cast results from local variables
- [`KT-22997`](https://youtrack.jetbrains.com/issue/KT-22997) Smart-cast should merge is-check for non-nullable type and a null check to a nullable type

  %19 = "tf.StringLength"(%arg0) {device = "", unit = "BYTE"} : (tensor<1x!tf_type.string>) -> tensor<1xi32>
  %20 = "tf.ExpandDims"(%19, %7) {device = ""} : (tensor<1xi32>, tensor<i32>) -> tensor<1x1xi32>
  %21 = "tf.Cast"(%20) {Truncate = false, device = ""} : (tensor<1x1xi32>) -> tensor<1x1xi64>
  %22 = "tf.Reshape"(%21, %12) {device = ""} : (tensor<1x1xi64>, tensor<1xi64>) -> tensor<1xi64>

  // CHECK-SAME:   {broadcast_dimensions = dense<3> : tensor<1xi64>}
  // CHECK: %[[RESULT:.+]] = mhlo.add %arg0, %[[ARG1_BCAST]]
  // CHECK: %[[CAST:.+]] = tensor.cast %[[RESULT]] : tensor<?x?x?x?xi32> to tensor<?x?x?x512xi32>
  // CHECK: return %[[CAST]] : tensor<?x?x?x512xi32>
  %0 = "tf.BiasAdd"(%arg0, %arg1) {data_format = "NHWC"} : (tensor<?x?x?x?xi32>, tensor<512xi32>) -> tensor<?x?x?x512xi32>

  // CHECK: %[[CAST:.*]] = "tfl.cast
  // CHECK: return %[[CAST]]
}
func.func @squaredDifferenceReluRemoveRelu(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
  %0 = "tfl.squared_difference"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
  %1 = "tfl.relu"(%0) : (tensor<1xf32>) -> tensor<1xf32>
  func.return %1: tensor<1xf32>

// CHECK-LABEL: squaredDifferenceReluRemoveRelu

  func.return %0 : tensor<3xcomplex<f32>>
}

// CHECK-LABEL:   func @convert_i32_f32(
// CHECK-SAME:                          %[[VAL_0:.*]]: tensor<2xi32>) -> tensor<2xf32> {
// CHECK:           %[[VAL_1:.*]] = "tf.Cast"(%[[VAL_0]]) <{Truncate = false}> : (tensor<2xi32>) -> tensor<2xf32>
// CHECK:           return %[[VAL_1]] : tensor<2xf32>
// CHECK:         }
func.func @convert_i32_f32(%arg0: tensor<2xi32>) -> tensor<2xf32> {

- github.com/spf13/afero: [v1.2.2 → v1.6.0](https://github.com/spf13/afero/compare/v1.2.2...v1.6.0)
- github.com/spf13/cast: [v1.3.0 → v1.3.1](https://github.com/spf13/cast/compare/v1.3.0...v1.3.1)
- github.com/spf13/cobra: [v1.1.3 → v1.2.1](https://github.com/spf13/cobra/compare/v1.1.3...v1.2.1)

    - `apiserver_flowcontrol_demand_seats_high_watermark`: High watermark, over last adjustment period, of demand_seats
    - `apiserver_flowcontrol_demand_seats_average`: Time-weighted average, over last adjustment period, of demand_seats
    - `apiserver_flowcontrol_demand_seats_stdev`: Time-weighted standard deviation, over last adjustment period, of demand_seats
    - `apiserver_flowcontrol_demand_seats_smoothed`: Smoothed seat demands

- github.com/sean-/seed: [e2103e2](https://github.com/sean-/seed/tree/e2103e2)
- github.com/shurcooL/sanitized_anchor_name: [v1.0.0](https://github.com/shurcooL/sanitized_anchor_name/tree/v1.0.0)
- github.com/spf13/cast: [v1.3.1](https://github.com/spf13/cast/tree/v1.3.1)
- github.com/spf13/jwalterweatherman: [v1.1.0](https://github.com/spf13/jwalterweatherman/tree/v1.1.0)
- github.com/spf13/viper: [v1.8.1](https://github.com/spf13/viper/tree/v1.8.1)

		b.size += n
		b.expected -= int64(n)
	}
	return ntotal, nil
}

func (b *http2dataBuffer) lastChunkOrAlloc(want int64) []byte {
	if len(b.chunks) != 0 {
		last := b.chunks[len(b.chunks)-1]
		if b.w < len(last) {
			return last
		}
	}
	chunk := http2getDataBufferChunk(want)
	b.chunks = append(b.chunks, chunk)
	b.w = 0
	return chunk
}