var tokens int           // number of tokens to request

	if hdr > 0 { // available tokens go towards header first
		if hdr < b { // all of header can be accommodated
			r.opts.HeaderSize = 0
			need = int(math.Min(float64(b-hdr), float64(need))) // use remaining tokens towards payload
			tokens = need + hdr

		} else { // part of header can be accommodated
			r.opts.HeaderSize -= b - 1

 * <a href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingSortedSet} forward <i>indiscriminately</i> to
 * the methods of the delegate. For example, overriding {@link #add} alone <i>will not</i> change
 * the behavior of {@link #addAll}, which can lead to unexpected behavior. In this case, you should

 * href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingMapEntry} forward <i>indiscriminately</i> to
 * the methods of the delegate. For example, overriding {@link #getValue} alone <i>will not</i>
 * change the behavior of {@link #equals}, which can lead to unexpected behavior. In this case, you

   * this implementation.
   *
   * @since 7.0
   */
  protected boolean standardEquals(@CheckForNull Object object) {
    return Sets.equalsImpl(this, object);
  }

  /**
   * A sensible definition of {@link #hashCode} in terms of {@link #iterator}. If you override
   * {@link #iterator}, you may wish to override {@link #equals} to forward to this implementation.
   *

      ASSERT_NEAR(manuals[j], danalytical[j], abs_error);
    }
  }

  TF_DeleteTensor(analytical_tensor);
  delete[] danalytical;
}

Model BuildGradModel(Model forward, GradientRegistry registry) {
  return [forward_model = std::move(forward),
          grad_registry = std::move(registry)](
             AbstractContext* ctx,
             absl::Span<AbstractTensorHandle* const> inputs,

 * the <a href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingSortedMultiset} forward
 * <b>indiscriminately</b> to the methods of the delegate. For example, overriding {@link
 * #add(Object, int)} alone <b>will not</b> change the behavior of {@link #add(Object)}, which can

 * more methods to modify the behavior of the backing queue as desired per the <a
 * href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingQueue} forward <b>indiscriminately</b> to the
 * methods of the delegate. For example, overriding {@link #add} alone <b>will not</b> change the
 * behavior of {@link #offer} which can lead to unexpected behavior. In this case, you should

#include "tensorflow/c/eager/unified_api_testutil.h"

namespace tensorflow {
namespace gradients {

/* Returns numerical grad inside `dtheta_approx` given `forward` model and
 * parameter specified by `input_index`.
 *
 * I.e. if y = <output of the forward model> and w = inputs[input_index],
 * this will calculate dy/dw numerically.
 *
 * `use_function` indicates whether to use graph mode(true) or eager(false).
 *

 * <a href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingSortedMap} forward <i>indiscriminately</i> to
 * the methods of the delegate. For example, overriding {@link #put} alone <i>will not</i> change
 * the behavior of {@link #putAll}, which can lead to unexpected behavior. In this case, you should

    t.reset(x_raw);
  }

  AbstractOperationPtr check_numerics_op(ctx->CreateOperation());
  ForwardOperation forward_op;
  Status s = Reset(check_numerics_op.get(), "CheckNumerics",
                   /*raw_device_name=*/nullptr, &forward_op);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  if (isa<TracingOperation>(check_numerics_op.get())) {