//tensorflow/core/tfrt
//tensorflow/python/kernel_tests/signal
//tensorflow/examples
//tensorflow/tools/android
//tensorflow/python/eager/benchmarks
EOF

  # grep patterns for files and targets which don't need to be in the pip
  # package, ever.
  cat > $BATS_TEST_TMPDIR/ignore_these_deps <<EOF
benchmark
_test$
_test.py$
_test_cpu$
_test_cpu.py$
_test_gpu$
_test_gpu.py$
_test_lib$

        assertTrue(queryFieldConfig.searchFieldSet.contains("field3"));
    }

    /**
     * Test performance improvement of Set-based lookup over array-based lookup.
     * This is a micro-benchmark to demonstrate the O(1) vs O(n) improvement.
     */
    @Test
    public void test_lookupPerformance_SetFasterThanArray() {
        // Create a large array of fields
        int fieldCount = 1000;

			return cfg, err
		}
		if inlineBlock > 128*humanize.KiByte {
			configLogOnceIf(context.Background(), fmt.Errorf("inline block value bigger than recommended max of 128KiB -> %s, performance may degrade for PUT please benchmark the changes", inlineBlockStr), inlineBlockStr)
		}
		cfg.inlineBlock = int64(inlineBlock)
	} else {
		cfg.inlineBlock = 128 * humanize.KiByte
	}

	cfg.initialized = true

	return cfg, nil
}

// provide any API to calculate the profiler file path in the
// disk since the name of this latter is randomly generated.
type profilerWrapper struct {
	// Profile recorded at start of benchmark.
	records map[string][]byte
	stopFn  func() ([]byte, error)
	ext     string
}

// record will record the profile and store it as the base.

]

# List of files to configure when building Bazel on Apple platforms.
APPLE_BAZEL_FILES = [
    'tensorflow/lite/ios/BUILD', 'tensorflow/lite/objc/BUILD',
    'tensorflow/lite/swift/BUILD',
    'tensorflow/lite/tools/benchmark/experimental/ios/BUILD'
]

# List of files to move when building for iOS.
IOS_FILES = [
    'tensorflow/lite/objc/TensorFlowLiteObjC.podspec',
    'tensorflow/lite/swift/TensorFlowLiteSwift.podspec',
]

	return obj
}

// BenchmarkListObjects - Run ListObject Repeatedly and benchmark.
func BenchmarkListObjects(b *testing.B) {
	// Make a temporary directory to use as the obj.
	directory := b.TempDir()

	// Create the obj.
	obj := initFSObjectsB(directory, b)

	bucket := "ls-benchmark-bucket"
	// Create a bucket.
	err := obj.MakeBucket(b.Context(), bucket, MakeBucketOptions{})

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.google.common.base;

import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import org.jspecify.annotations.NullUnmarked;

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.google.common.base;

import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import org.jspecify.annotations.NullUnmarked;

			t.Errorf("test %d, unexpected error: %v", i, err)
		}
		if (formats == FormatUnknown) && (err == nil) {
			t.Errorf("test %d, got nil-error, want non-nil error", i)
		}
	}
}

func Benchmark(b *testing.B) {
	type file struct {
		hdr  *Header
		body []byte
	}

	vectors := []struct {
		label string
		files []file
	}{{
		"USTAR",
		[]file{{

   * world. Figure out what sort of space-time tradeoff we're actually going to get here with the
   * *Map variants. This class is particularly hard to benchmark, because the benefit is not only in
   * less allocation, but also having the GC do less work to scan the heap because of fewer
   * references, which is particularly hard to quantify.
   */