// license that can be found in the LICENSE file.

// constant conversions

package const1

import "math"

const(
	mi = ^int(0)
	mu = ^uint(0)
	mp = ^uintptr(0)

	logSizeofInt     = uint(mi>>8&1 + mi>>16&1 + mi>>32&1)
	logSizeofUint    = uint(mu>>8&1 + mu>>16&1 + mu>>32&1)
	logSizeofUintptr = uint(mp>>8&1 + mp>>16&1 + mp>>32&1)
)

const (
	minInt8 = -1<<(8<<iota - 1)
	minInt16
	minInt32
	minInt64

	f(Bool)             // ERROR "convert|wrong type|cannot|incompatible"
}

const ptr = nil // ERROR "const.*nil|not constant"
const _ = string([]byte(nil)) // ERROR "is not a? ?constant"
const _ = uintptr(unsafe.Pointer((*int)(nil))) // ERROR "is not a? ?constant"
const _ = unsafe.Pointer((*int)(nil)) // ERROR "cannot be nil|invalid constant type|is not a constant|not constant"

// CHECK: name: "const2"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_HALF
// CHECK: half_val: 15360
// CHECK: half_val: 16384
// CHECK: name: "const3"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_BFLOAT16
// CHECK: half_val: 16964
// CHECK: half_val: 17485
// CHECK: name: "const4"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_BFLOAT16

func.func @main() -> tensor<2x3xi32> {
  %graph = tf_executor.graph {
    %0:2 = tf_executor.island wraps "tf.Const"() {value = dense<5> : tensor<2x3xi32>} : () -> tensor<2x3xi32> loc("Const0")
    %1:2 = tf_executor.island wraps "tf.Const"() {value = dense<4.2> : tensor<4x5xf32>} : () -> tensor<4x5xf32> loc("Const1")

// CHECK: name: "const2"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_HALF
// CHECK: half_val: 15360
// CHECK-NEXT: half_val: 16384
    %2:2 = tf_executor.island wraps "tf.Const"() {device = "", dtype = bf16, value = dense<[4.900000e+01, 8.200000e+02]> : tensor<2xbf16>} : () -> tensor<bf16> loc("const3")
// CHECK: name: "const3"
// CHECK-NEXT: op: "Const"
// CHECK: dtype: DT_BFLOAT16
// CHECK: half_val: 16964

        shape {
          dim {
            size: 2
          }
        }
      }
    }
  }
}
node {
  name: "RaggedToTensor"
  op: "RaggedTensorToTensor"
  input: ["Const0", "_Arg", "Const1", "Const2"]
  attr {
    key: "T"
    value {
      type: DT_STRING
    }
  }
  attr {
    key: "row_partition_types"
    value {
      list {
        s: ["ROW_SPLITS"]
      }

          }
        }
        int_val: 0
      }
    }
  }
  experimental_debug_info {
  }
}
node {
  name: "tf.Const1"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_INT32
        tensor_shape {
        }
        int_val: 0
      }
    }
  }
  experimental_debug_info {

					Valu("const1", OpConst32, intType, 1, nil),
					Valu("const2", OpConst32, intType, 2, nil),
					Valu("addr", OpAddr, boolType.PtrTo(), 0, nil, "sb"),
					Valu("cond", OpLoad, boolType, 0, nil, "addr", "start"),
					If("cond", "b2", "b3")),
				Bloc("b2",
					Goto("b3")),
				Bloc("b3",
					Valu("phi", OpPhi, intType, 0, nil, "const1", "const2"),

  // CHECK-NEXT:       buffer: 2,
  // CHECK-NEXT:       name: "Const1",
  // CHECK-NEXT:       quantization: {
  // CHECK-EMPTY:
  // CHECK-NEXT:       },
  // CHECK-NEXT:       has_rank: true
  // CHECK-NEXT:     }, {
  // CHECK-NEXT:       shape: [ 4 ],
  // CHECK-NEXT:       type: BOOL,
  // CHECK-NEXT:       buffer: 3,
  // CHECK-NEXT:       name: "Const2",
  // CHECK-NEXT:       quantization: {
  // CHECK-EMPTY:

// ChaCha8 is ChaCha with 8 rounds.
// See https://cr.yp.to/chacha/chacha-20080128.pdf.
//
// ChaCha8 operates on a 4x4 matrix of uint32 values, initially set to:
//
//	const1 const2 const3 const4
//	seed   seed   seed   seed
//	seed   seed   seed   seed
//	counter64     0      0
//
// We use the same constants as ChaCha20 does, a random seed,
// and a counter. Running ChaCha8 on this input produces