}
	return buffer.Bytes()
}

// truncatePodHostnameIfNeeded truncates the pod hostname if it's longer than 63 chars.
func truncatePodHostnameIfNeeded(podName, hostname string) (string, error) {
	// Cap hostname at 63 chars (specification is 64bytes which is 63 chars and the null terminating char).
	const hostnameMaxLen = 63
	if len(hostname) <= hostnameMaxLen {
		return hostname, nil
	}

  }

  std::vector<std::optional<std::vector<int>>> shapes;
  TF_RETURN_IF_ERROR(::tensorflow::ParseNodeShapes(input_shapes, shapes));

  for (const auto& shape : shapes) {
    if (!shape) {
      return absl::AbortedError("Missing input argument shapes");
    }
    parsed_shapes.push_back(SmallVector<int64_t>(shape->begin(), shape->end()));
  }
  return parsed_shapes;
}

		}
	}
	lockInit(&pp.timers.mu, lockRankTimers)

	// This P may get timers when it starts running. Set the mask here
	// since the P may not go through pidleget (notably P 0 on startup).
	timerpMask.set(id)
	// Similarly, we may not go through pidleget before this P starts
	// running if it is P 0 on startup.
	idlepMask.clear(id)
}

			}
			err = a.Actor.Act(b, ctx, a)
			span.Done()
		}
		if a.json != nil {
			a.json.TimeDone = time.Now()
		}

		// The actions run in parallel but all the updates to the
		// shared work state are serialized through b.exec.
		b.exec.Lock()
		defer b.exec.Unlock()

		if err != nil {
			if b.AllowErrors && a.Package != nil {
				if a.Package.Error == nil {

  let options = [
    Option<"max_iterations_", "max-iterations", "int64_t", /*default=*/"10",
           "Maximum shape inference iterations">,
    Option<"input_arg_shapes_", "input-arg-shapes", "std::string", /*default=*/"",
           "Input tensor shapes. Shapes for different tensors are separated by ':', and dimension sizes for the same tensor are separated by ','">,
  ];
}

element. For example, if you have a single image of shape `[height, width,
channels]`, you can make it a batch of 1 image with `expand_dims(image, 0)`,
which will make the shape `[1, height, width, channels]`.

Other examples:

```
# 't' is a tensor of shape [2]
shape(expand_dims(t, 0)) ==> [1, 2]
shape(expand_dims(t, 1)) ==> [2, 1]
shape(expand_dims(t, -1)) ==> [2, 1]

    # Checks that each variable's name and shape match.
    self.assertEqual(len(variable_node_defs), len(var_name_and_shapes))
    for var_name, shape in var_name_and_shapes:
      self.assertIn(var_name, variable_node_defs)
      self.assertEqual(
          shape,
          tensor_shape.TensorShape(
              variable_node_defs[var_name].attr['shape'].shape
          ),
      )

  %0 = "tfl.shape"(%arg1) : (tensor<8x7x6x5x?x3x2x1xf32>) -> tensor<8xi64>
  %1 = "tfl.shape"(%arg2) : (tensor<?x3x2x1xf32>) -> tensor<4xi64>
  %2 = "tfl.broadcast_args"(%0, %1) : (tensor<8xi64>, tensor<4xi64>) -> tensor<8xi64>
  %3 = "tfl.shape"(%arg0) : (tensor<8x7x6x5x?x3x2x1xi1>) -> tensor<8xi64>

//		flags has a similar effect.
//	-ldflags '[pattern=]arg list'
//		arguments to pass on each go tool link invocation.
//	-linkshared
//		build code that will be linked against shared libraries previously
//		created with -buildmode=shared.
//	-mod mode
//		module download mode to use: readonly, vendor, or mod.
//		By default, if a vendor directory is present and the go version in go.mod

			continue
		}

		var rst sym.SymKind
		if rs != 0 {
			rst = ldr.SymType(rs)
		}

		if rs != 0 && (rst == sym.Sxxx || rst == sym.SXREF) {
			// When putting the runtime but not main into a shared library
			// these symbols are undefined and that's OK.
			if target.IsShared() || target.IsPlugin() {
				if ldr.SymName(rs) == "main.main" || (!target.IsPlugin() && ldr.SymName(rs) == "main..inittask") {