ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Check unused input mappings
  int num_unused_input_mappings;
  const char** src_names;
  int* src_indexes;
  TF_ImportGraphDefResultsMissingUnusedInputMappings(
      results, &num_unused_input_mappings, &src_names, &src_indexes);
  ASSERT_EQ(1, num_unused_input_mappings);
  EXPECT_EQ(string("fake"), string(src_names[0]));
  EXPECT_EQ(0, src_indexes[0]);

          echo "success."
        }
        # See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/toolchains/remote_config/configs.bzl
        # This is a mapping of name_container_map keys under sigbuild_tf_configs
        # to tag names on gcr.io/tensorflow-sigs/build.
        # TF 2.9
        map sigbuild-r2.9 2.9-python3.9
        map sigbuild-r2.9-python3.8 2.9-python3.8

// inspect values. This would let people e.g. copy over most attributes and then
// modify some based on their values.

// A reference to an op's name -> attribute mapping
typedef struct TFE_OpAttrs TFE_OpAttrs;

// Fetch a reference to `op`'s attributes. The returned reference is only valid
// while `op` is alive.
TF_CAPI_EXPORT extern const TFE_OpAttrs* TFE_OpGetAttrs(const TFE_Op* op);

          temp_file_name.c_str());
  TF_SetStatus(status, TF_OK, "");
}

// TODO(vnvo2409): We could download into a local temporary file and use
// memory-mapping.
void NewReadOnlyMemoryRegionFromFile(const TF_Filesystem* filesystem,
                                     const char* path,
                                     TF_ReadOnlyMemoryRegion* region,

  *opers = results->return_nodes.data();
}

void TF_ImportGraphDefResultsMissingUnusedInputMappings(
    TF_ImportGraphDefResults* results, int* num_missing_unused_input_mappings,
    const char*** src_names, int** src_indexes) {
  *num_missing_unused_input_mappings = results->missing_unused_key_names.size();
  *src_names = results->missing_unused_key_names.data();
  *src_indexes = results->missing_unused_key_indexes.data();
}

operator in the script should be in the "math" category, and it will be
generated in the output file `c/experimental/ops/math_ops.cc`.

Running this script should be a no-op, generating identical code other than

// Fetches any input mappings requested via
// TF_ImportGraphDefOptionsAddInputMapping() that didn't appear in the GraphDef
// and weren't used as input to any node in the imported graph def. The number
// of fetched mappings is returned in `num_missing_unused_input_mappings`. The
// array of each mapping's source node name is returned in `src_names`, and the
// array of each mapping's source index is returned in `src_indexes`.
//

*   `tf.print`:
    *   Bug fix in `tf.print()` with `OrderedDict` where if an `OrderedDict`
        didn't have the keys sorted, the keys and values were not being printed
        in accordance with their correct mapping.
*   `tf.train.Checkpoint`:
    *   Now accepts a `root` argument in the initialization, which generates a
        checkpoint with a root object. This allows users to create a

# Map --platforms=darwin_x86_64 to --cpu=darwin and vice-versa to make selects()
# and transistions that use these flags work.
build:cross_compile_macos_x86 --platform_mappings=tensorflow/tools/toolchains/cross_compile/config/platform_mappings

# RBE cross-compile configs for Darwin x86
build:rbe_cross_compile_macos_x86 --config=cross_compile_macos_x86 --remote_download_minimal

  // Temporarily push or pop transient state for this accumulator.
  //
  // Allows an accumulator which is currently processing an operation to
  // temporarily reset its state. Without pushing and popping, accumulators
  // ignore operations executed as a direct result of their own jvp
  // computations.
  void PushState() { call_state_.emplace(nullptr, false); }
  void PopState() { call_state_.pop(); }

 private: