// doesn't need to be transposed, then just tiling is enough and there is no
  // need to call another einsum. For example, tiling is sufficient for
  // "abcd->ac". But for equations like "aabbcd->ac" (generalized traces) or
  // "abc->ca" (transpose), we'd need another einsum operation after tiling.
  if (!has_repeated_labels &&
      input_subs_without_reduced_labels == output_subs) {

// we skip to "start+t.Size_" and begin again from there. This process is
// repeated until we hit "start+s.elemsize".
// This tiling algorithm supports array data, since the type always refers to
// the element type of the array. Single objects are considered the same as
// single-element arrays.
// The tiling algorithm may scan data past the end of the compiler-recognized
// object, but any unused data within the allocation slot (i.e. within s.elemsize)

  // Enables tracking of the "live" JitRt queries to, on a crash, identify the
  // "query of death". See TfJitRtQueryOfDeathLogger.
  bool log_query_of_death;

  // Enable vectorization, which requires tiling and peeling on different ops.
  bool vectorize;

  // Enables crash reproducer for JitRt MLIR pass manager.
  bool enable_crash_reproducer;
};

// Return a pointer to the DumpGraphFlags struct;

//
// See also https://golang.org/design/25530-sumdb#checksum-database
// and https://research.swtch.com/tlog#tiling_a_log.
type Tile struct {
	H int   // height of tile (1 ≤ H ≤ 30)
	L int   // level in tiling (-1 ≤ L ≤ 63)
	N int64 // number within level (0 ≤ N, unbounded)
	W int   // width of tile (1 ≤ W ≤ 2**H; 2**H is complete tile)
}

// TileForIndex returns the tile of fixed height h ≥ 1

  let description = [{
    Constructs a tensor by tiling a given tensor.

   This operation creates a new tensor by replicating input
   multiples times. The output tensor's i'th dimension has
   input.dims(i) * multiples[i] elements, and the values of input
   are replicated multiples[i] times along the 'i'th dimension.
   For example, tiling [a b c d] by [2] produces [a b c d a b c d].
  }];

      slowFactorials[i] = RANDOM_SOURCE.nextInt(factorialBound);
      binomials[i] = RANDOM_SOURCE.nextInt(factorials[i] + 1);
    }
  }

  /** Previous version of BigIntegerMath.factorial, kept for timing purposes. */
  private static BigInteger oldSlowFactorial(int n) {
    if (n <= 20) {
      return BigInteger.valueOf(LongMath.factorial(n));
    } else {
      int k = 20;

# Erasure code sizing guide

## Toy Setups

Capacity constrained environments, MinIO will work but not recommended for production.

| servers | drives (per node) | stripe_size | parity chosen (default) | tolerance for reads (servers) | tolerance for writes (servers) |
|--------:|------------------:|------------:|------------------------:|------------------------------:|-------------------------------:|

Martin Taillefer <******@****.***> 1568244741 -0700

// run

// Copyright 2009 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// Test simulating a Turing machine, sort of.

package main

// brainfuck

var p, pc int
var a [30000]byte

const prog = "++++++++++[>+++++++>++++++++++>+++>+<<<<-]>++.>+.+++++++..+++.>++.<<+++++++++++++++.>.+++.------.--------.>+.>.!"

func scan(dir int) {

package base

import (
	"fmt"
	"io"
	"strings"
	"time"
)

var Timer Timings

// Timings collects the execution times of labeled phases
// which are added through a sequence of Start/Stop calls.
// Events may be associated with each phase via AddEvent.
type Timings struct {
	list   []timestamp
	events map[int][]*event // lazily allocated
}

type timestamp struct {