)

config_setting(
    name = "with_xla_support",
    define_values = {"with_xla_support": "true"},
    visibility = ["//visibility:public"],
)

# By default, XLA GPU is compiled into tensorflow when building with
# --config=cuda even when `with_xla_support` is false. The config setting
# here allows us to override the behavior if needed.
config_setting(
    name = "no_xla_deps_in_cuda",

   * exists, a CAS is tried.  Retries proceed by "double hashing",
   * using a secondary hash (Marsaglia XorShift) to try to find a
   * free slot.
   *
   * The table size is capped because, when there are more threads
   * than CPUs, supposing that each thread were bound to a CPU,
   * there would exist a perfect hash function mapping threads to
   * slots that eliminates collisions. When we reach capacity, we

}

// DirectioAlignSize - DirectIO alignment needs to be 4K. Defined here as
// directio.AlignSize is defined as 0 in MacOS causing divide by 0 error.
const DirectioAlignSize = 4096

// CopyAligned - copies from reader to writer using the aligned input
// buffer, it is expected that input buffer is page aligned to
// 4K page boundaries. Without passing aligned buffer may cause
// this function to return error.
//

* Criar uma cópia do modelo armazenado, atualizando seus atributos com as atualizações parciais recebidas (usando o parâmetro `update`).
* Converter o modelo copiado em algo que possa ser armazenado no seu banco de dados (por exemplo, usando o `jsonable_encoder`).

import static com.google.common.truth.Truth.assertThat;
import static java.lang.System.arraycopy;
import static java.util.Arrays.asList;
import static java.util.Collections.emptyList;
import static java.util.Collections.nCopies;
import static java.util.Collections.singletonList;

import com.google.common.annotations.GwtCompatible;
import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;

import static com.google.common.truth.Truth.assertThat;
import static java.lang.System.arraycopy;
import static java.util.Arrays.asList;
import static java.util.Collections.emptyList;
import static java.util.Collections.nCopies;
import static java.util.Collections.singletonList;

import com.google.common.annotations.GwtCompatible;
import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;

        assertTrue(result.getFatals().get(2).contains("parent.version"));
    }

    @Test
    void testHardCodedSystemPath() throws Exception {
        SimpleProblemCollector result = validateRaw("hard-coded-system-path.xml");

        assertViolations(result, 0, 0, 3);

        assertContains(
                result.getWarnings().get(0),

build:dbg --per_file_copt=+tensorflow/core/kernels.*@-g0
# for now, disable arm_neon. see: https://github.com/tensorflow/tensorflow/issues/33360
build:dbg --cxxopt -DTF_LITE_DISABLE_X86_NEON
# AWS SDK must be compiled in release mode. see: https://github.com/tensorflow/tensorflow/issues/37498
build:dbg --copt -DDEBUG_BUILD

# Config to build TF TPU
build:tpu --define=with_tpu_support=true

mc: Health data saved to dc-11-health_20200321053323.json.gz
```

The gzipped output contains debugging information for your system

## Decoding Metadata

Metadata is stored in `xl.meta` files for erasure coded objects. Each disk in the set containing the object has this file. The file format is a binary format and therefore requires tools to view values.

### Installing xl-meta

      checkNotNull(value);
      checkArgument(!range.isEmpty(), "Range must not be empty, but was %s", range);
      entries.add(immutableEntry(range, value));
      return this;
    }

    /** Copies all associations from the specified range map into this builder. */
    @CanIgnoreReturnValue
    public Builder<K, V> putAll(RangeMap<K, ? extends V> rangeMap) {