return ops::MatMul(ctx, inputs[0], inputs[1], &outputs[0],
                     /*transpose_a=*/false,
                     /*transpose_b=*/false, "MatMul");
}

absl::Status MulModel(AbstractContext* ctx,
                      absl::Span<AbstractTensorHandle* const> inputs,
                      absl::Span<AbstractTensorHandle*> outputs) {
  return ops::Mul(ctx, inputs[0], inputs[1], &outputs[0], "Mul");
}

	}
}

// Borrowed from mutex_test.go
func HammerMutex(m *DRWMutex, loops int, cdone chan bool) {
	for range loops {
		m.Lock(id, source)
		m.Unlock(context.Background())
	}
	cdone <- true
}

// Borrowed from mutex_test.go
func TestMutex(t *testing.T) {
	loops := 200
	if testing.Short() {
		loops = 5
	}
	c := make(chan bool)
	m := NewDRWMutex(ds, "test")
	for range 10 {

// on it must match the list of operations in ops.
type testFile struct {
	ops fileOps
	pos int64
}

func (f *testFile) Read(b []byte) (int, error) {
	if len(b) == 0 {
		return 0, nil
	}
	if len(f.ops) == 0 {
		return 0, io.EOF
	}
	s, ok := f.ops[0].(string)
	if !ok {
		return 0, errors.New("unexpected Read operation")
	}

	n := copy(b, s)
	if len(s) > n {
		f.ops[0] = s[n:]
	} else {
		f.ops = f.ops[1:]

				consistent = false
				continue
			}
			ver := vers[0]
			if len(tops) == 0 {
				consistent = true
				topSig = ver.header
			} else {
				consistent = consistent && ver.header == topSig
			}
			tops = append(tops, vers[0])
		}

		// Check if done...
		if len(tops) < quorum {
			// We couldn't gather enough for quorum
			break
		}

          + "that allows parallel edges, call allowsParallelEdges(true) on the Builder.";
  static final String SELF_LOOPS_NOT_ALLOWED =
      "Cannot add self-loop edge on node %s, as self-loops are not allowed. To construct a graph "
          + "that allows self-loops, call allowsSelfLoops(true) on the Builder.";
  static final String NOT_AVAILABLE_ON_UNDIRECTED =
      "Cannot call source()/target() on a EndpointPair from an undirected graph. Consider calling "

  /**
   * Returns the count of {@code node}'s incident edges, counting self-loops twice (equivalently,
   * the number of times an edge touches {@code node}).
   *
   * <p>For directed graphs, this is equal to {@code inDegree(node) + outDegree(node)}.
   *
   * <p>For undirected graphs, this is equal to {@code incidentEdges(node).size()} + (number of
   * self-loops incident to {@code node}).
   *

  /**
   * Returns the count of {@code node}'s incident edges, counting self-loops twice (equivalently,
   * the number of times an edge touches {@code node}).
   *
   * <p>For directed graphs, this is equal to {@code inDegree(node) + outDegree(node)}.
   *
   * <p>For undirected graphs, this is equal to {@code incidentEdges(node).size()} + (number of
   * self-loops incident to {@code node}).
   *

This directory contains templates that work around gradle-ospackage-plugin
trying to be helpful and adding templates for your os packaging scripts. We
have relatively nice scripts already so we just override the templates to be

    TF_RETURN_IF_ERROR(
        ops::Sub(ctx, fPlus.get(), fMinus.get(), f_outputs, "sub_top"));
    AbstractTensorHandlePtr fDiff(f_outputs[0]);

    // Calculate using the difference quotient definition:
    // (f(theta + eps) - f(theta - eps)) / (2 * eps).
    TF_RETURN_IF_ERROR(
        ops::Div(ctx, fDiff.get(), two_eps.get(), f_outputs, "diff_quotient"));

	v := &g[T]{
		db:  db,
		ops: make([]op, 0, 5),
	}

	if len(opts) > 0 {
		v.ops = append(v.ops, func(db *DB) *DB {
			return db.Clauses(opts...)
		})
	}

	v.createG = &createG[T]{
		chainG: chainG[T]{
			execG: execG[T]{g: v},
		},
	}
	return v
}

type g[T any] struct {
	*createG[T]
	db  *DB
	ops []op
}