import java.io.StringWriter;
import java.util.Random;

/** Benchmark for {@code BaseEncoding} performance. */
public class BaseEncodingBenchmark {
  private static final int INPUTS_COUNT = 0x1000;
  private static final int INPUTS_MASK = 0xFFF;

  enum EncodingOption {
    BASE64(BaseEncoding.base64()),
    BASE64_URL(BaseEncoding.base64Url()),
    BASE32(BaseEncoding.base32()),
    BASE32_HEX(BaseEncoding.base32Hex()),

name: Notify Translations

on:
  pull_request_target:
    types:
      - labeled
      - closed
  workflow_dispatch:
    inputs:
      number:
        description: PR number
        required: true
      debug_enabled:
        description: 'Run the build with tmate debugging enabled (https://github.com/marketplace/actions/debugging-with-tmate)'
        required: false
        default: 'false'

jobs:
  notify-translations:

void CSession::Run(TF_Status* s) {
  if (inputs_.size() != input_values_.size()) {
    ADD_FAILURE() << "Call SetInputs() before Run()";
    return;
  }
  ResetOutputValues();
  output_values_.resize(outputs_.size(), nullptr);

  const TF_Output* inputs_ptr = inputs_.empty() ? nullptr : &inputs_[0];
  TF_Tensor* const* input_values_ptr =
      input_values_.empty() ? nullptr : &input_values_[0];

  // watched inputs.
  void Watch(const AbstractTensorHandle*);
  // Records an operation with given inputs and outputs
  // on the tape and marks all its outputs as watched if at
  // least one input of the op is watched and has a trainable dtype.
  // op_name is optional and is used for debugging only.
  void RecordOperation(absl::Span<AbstractTensorHandle* const> inputs,

void Tape::RecordOperation(absl::Span<AbstractTensorHandle* const> inputs,
                           absl::Span<AbstractTensorHandle* const> outputs,
                           GradientFunction* gradient_function,
                           const string& op_name) {
  std::vector<int64_t> input_ids(inputs.size());
  std::vector<tensorflow::DataType> input_dtypes(inputs.size());
  for (int i = 0; i < inputs.size(); i++) {
    input_ids[i] = ToId(inputs[i]);

            TaskInputs inputs = task.getInputs();
            inputs.files(extension.getCssFiles())
                .withPropertyName("manual")
                .withPathSensitivity(PathSensitivity.RELATIVE);
            inputs.dir("src/main/resources")
                .withPropertyName("resources")
                .withPathSensitivity(PathSensitivity.RELATIVE);
            inputs.dir(extension.getUserManual().getSnippets())

      Iterable<? extends T>... inputs) {
    return concatNoDefensiveCopy(Arrays.copyOf(inputs, inputs.length));
  }

  /**
   * Returns a fluent iterable that combines several iterables. The returned iterable has an
   * iterator that traverses the elements of each iterable in {@code inputs}. The input iterators
   * are not polled until necessary.
   *

                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    for (int i = 0; i < grad_outputs.size(); i++) {
      auto grad_input = grad_outputs[i];
      // TODO(srbs): Should we add a copy contructor to AbstractTensorHandle
      // that takes care of this similar to `Tensor`?
      if (grad_input) {
        grad_input->Ref();
      }
      grad_inputs[i] = grad_input;
    }
    return absl::OkStatus();
  }

      for (ClosingFuture<?> input : inputs) {
        input.becomeSubsumedInto(closeables);
      }
    }

    /**
     * Returns a new {@code ClosingFuture} pipeline step derived from the inputs by applying a
     * combining function to their values. The function can use a {@link DeferredCloser} to capture
     * objects to be closed when the pipeline is done.
     *

package etcd

import (
	"reflect"
	"testing"
)

// TestParseEndpoints - tests parseEndpoints function with valid and invalid inputs.
func TestParseEndpoints(t *testing.T) {
	testCases := []struct {
		s         string
		endpoints []string
		secure    bool
		success   bool
	}{
		// Invalid inputs
		{"https://localhost:2379,http://localhost:2380", nil, false, false},
		{",,,", nil, false, false},
		{"", nil, false, false},