"//tensorflow/core:framework",
        "//tensorflow/core/platform:errors",
    ],
)

cc_library(
    name = "resource_variable_ops",
    srcs = [
        "resource_variable_ops.cc",
    ],
    hdrs = [
        "resource_variable_ops.h",
    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        "//tensorflow/c/eager:abstract_context",

  bool HasTensor(const string& name) const;
  const string DebugString() const;

  // Returns a map from variable names to their shapes.  Slices of a partitioned
  // tensor are combined into a single entry.
  const TensorSliceReader::VarToShapeMap& GetVariableToShapeMap() const;

  // Returns a map from variable names to their data types.  Slices of a
  // partitioned tensor are combined into a single entry.

                          remote_device) != device_names.end());
  }

  // Create a variable using `ctx_0`.
  // Read the variable using `ctx_1`. This read should succeed.
  // 1. Create a variable on `remote_device`, using `ctx_0`.
  TFE_TensorHandle* handle_0 =
      CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var2");

  // 2. Wait for `var2` to be created and initialized on the worker.

# check This script checks for such errors early
if ! grep "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX" .bazelrc; then
  cat <<EOF
ERROR: RBE was enabled via the 'rbe' env in the 'TFCI' variable.
       TFCI: $TFCI
       TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX is "$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX".
       But in .bazelrc, there is no "rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX".

        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/types:optional",
        "@com_google_absl//absl/types:variant",
    ],
)

cc_library(
    name = "parallel_device_lib",
    srcs = [":lib_sources"],
    hdrs = [":lib_headers"],
    visibility = ["//tensorflow:internal"],
    deps = [
        "//tensorflow/c:c_api",

  }

  // Create a variable using `ctx_0`.
  // Replace worker1 using a new worker, and update the contexts.
  // Read the variable using `ctx_1`. This read should succeed.
  //
  // 1. Create a variable on `remote_device`, using `ctx_0`.
  TFE_TensorHandle* handle_0 =
      CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var");

paths point to attributes or sub-modules within a module's namespace, but they
don't correspond to an actual file or directory on the filesystem. The list of
such paths is stored in the packages_for_skip variable and will be skipped
during the test.

##### How to Build

```
bazel build //:test_import_api_packages
```

##### How to Run

```
bazel test //:test_import_api_packages --test_output=all

*   `tf.Variable`:

    *   Added `CompositeTensor` as a baseclass to `ResourceVariable`. This
        allows `tf.Variable`s to be nested in `tf.experimental.ExtensionType`s.
    *   Added a new constructor argument `experimental_enable_variable_lifting`
        to `tf.Variable`, defaulting to True. When it's `False`, the variable

'''
 Repository rule to set some environment variables.
 Can be set via build parameter "--repo_env=<VARIABLE_NAME>=<value>"
 e.g "--repo_env=REQUIREMENTS_FILE_NAME=requirements.in"

 List of variables:
 REQUIREMENTS_FILE_NAME
'''

def _updater_config_repository_impl(repository_ctx):
    repository_ctx.file("BUILD", "")
    requirements_file_name = repository_ctx.os.environ.get("REQUIREMENTS_FILE_NAME", "requirements.in")
    repository_ctx.file(

// MakeCleanup(f) returns an RAII cleanup object that calls 'f' in its
// destructor. The easiest way to use MakeCleanup is with a lambda argument,
// capturing the return value in an 'auto' local variable. Most users will not
// need more sophisticated syntax than that.
//
// Example:
//   void func() {
//     FILE* fp = fopen("data.txt", "r");
//     if (fp == nullptr) return;