<typ.UInt64> (Mod32u <typ.UInt32> (Trunc64to32 <typ.UInt32> (Rsh64Ux64 <typ.UInt64> x (Const64 <typ.UInt64> [32]))) (Const32 <typ.UInt32> [int32(c)]))) (Const64 <typ.UInt64> [int64((1<<32)/c)]))) (ZeroExt32to64 (Div32u <typ.UInt32> (Add32 <typ.UInt32> (Mod32u <typ.UInt32> (Trunc64to32 <typ.UInt32> x) (Const32 <typ.UInt32> [int32(c)])) (Mul32 <typ.UInt32> (Mod32u <typ.UInt32> (Trunc64to32 <typ.UInt32> (Rsh64Ux64 <typ.UInt64> x (Const64 <typ.UInt64> [32]))) (Const32 <typ.UInt32> [int32(c)])) (Const32...

	// cond: d != 0
	// result: (MOVDconst [int64(uint32(int32(c)/int32(d)))])
	for {
		if v_0.Op != OpARM64MOVDconst {
			break
		}
		c := auxIntToInt64(v_0.AuxInt)
		if v_1.Op != OpARM64MOVDconst {
			break
		}
		d := auxIntToInt64(v_1.AuxInt)
		if !(d != 0) {
			break
		}
		v.reset(OpARM64MOVDconst)
		v.AuxInt = int64ToAuxInt(int64(uint32(int32(c) / int32(d))))
		return true
	}

	// cond: x<y && uint32(x)>uint32(y)
	// result: (FlagLT_UGT)
	for {
		y := auxIntToInt32(v.AuxInt)
		if v_0.Op != OpAMD64MOVLconst {
			break
		}
		x := auxIntToInt32(v_0.AuxInt)
		if !(x < y && uint32(x) > uint32(y)) {
			break
		}
		v.reset(OpAMD64FlagLT_UGT)
		return true
	}
	// match: (CMPLconst (MOVLconst [x]) [y])
	// cond: x>y && uint32(x)<uint32(y)
	// result: (FlagGT_ULT)

		{"(*Pointer).Load", Method, 19},
		{"(*Pointer).Store", Method, 19},
		{"(*Pointer).Swap", Method, 19},
		{"(*Uint32).Add", Method, 19},
		{"(*Uint32).CompareAndSwap", Method, 19},
		{"(*Uint32).Load", Method, 19},
		{"(*Uint32).Store", Method, 19},
		{"(*Uint32).Swap", Method, 19},
		{"(*Uint64).Add", Method, 19},
		{"(*Uint64).CompareAndSwap", Method, 19},
		{"(*Uint64).Load", Method, 19},

`[a b c d a b c d]`.

>>> a = tf.constant([[1,2,3],[4,5,6]], tf.int32)
>>> b = tf.constant([1,2], tf.int32)
>>> tf.tile(a, b)
<tf.Tensor: shape=(2, 6), dtype=int32, numpy=
array([[1, 2, 3, 1, 2, 3],
       [4, 5, 6, 4, 5, 6]], dtype=int32)>
>>> c = tf.constant([2,1], tf.int32)
>>> tf.tile(a, c)
<tf.Tensor: shape=(4, 3), dtype=int32, numpy=
array([[1, 2, 3],
       [4, 5, 6],
       [1, 2, 3],

        tf.TensorSpec([], dtypes.int32) ]) def _remote_multiply(a, b): return
        tf.math.multiply(a, b)

        server.register("multiply", _remote_multiply) ```

    *   Example usage to create client: `python client =
        tf.distribute.experimental.rpc.Client.create("grpc", address) a =
        tf.constant(2, dtype=tf.int32) b = tf.constant(3, dtype=tf.int32)

                                  format: int32
                                  type: integer
                                http2MaxRequests:
                                  description: Maximum number of active requests to
                                    a destination.
                                  format: int32
                                  type: integer

                                  format: int32
                                  type: integer
                                http2MaxRequests:
                                  description: Maximum number of active requests to
                                    a destination.
                                  format: int32
                                  type: integer

                                  format: int32
                                  type: integer
                                http2MaxRequests:
                                  description: Maximum number of active requests to
                                    a destination.
                                  format: int32
                                  type: integer

            "format": "int32",
            "type": "integer"
          },
          "revisionHistoryLimit": {
            "description": "The number of old history to retain to allow rollback. This is a pointer to distinguish between explicit zero and not specified. Defaults to 10.",
            "format": "int32",
            "type": "integer"
          },
          "selector": {