// will block till the operation that produces `h` has completed.
TF_CAPI_EXPORT extern const char* TFE_TensorHandleDeviceName(
    TFE_TensorHandle* h, TF_Status* status);

// Returns the name of the device in whose memory `h` resides.
//
// This function will block till the operation that produces `h` has completed.
TF_CAPI_EXPORT extern const char* TFE_TensorHandleBackingDeviceName(

  EXPECT_EQ(out.size(), file_size - block_size);
}

TEST(RamFileBlockCacheTest, Inconsistent) {
  // Tests the detection of interrupted reads leading to partially filled blocks
  // where we expected complete blocks.
  const size_t block_size = 16;
  // This fetcher returns OK but only fills in one byte for any offset.
  auto fetcher = [block_size](const string& filename, size_t offset, size_t n,

  // in the cache, and our current block is not block size, this likely means
  // we have inconsistent state within the cache. Note: it's possible some
  // incomplete reads may still go undetected.
  if (block->data.size() < block_size_) {
    Key fmax = std::make_pair(key.first, std::numeric_limits<size_t>::max());
    auto fcmp = block_map_.upper_bound(fmax);

  TF_Operation* feed = Placeholder(graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_Output feed_out_0 = TF_Output{feed, 0};
  int num_dims;

  // Fetch the shape, it should be completely unknown.
  num_dims = TF_GraphGetTensorNumDims(graph, feed_out_0, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(-1, num_dims);

  // Set the shape to be unknown, expect no change.

build:cuda_clang --@local_config_cuda//:cuda_compiler=clang
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current

RESULT_STORE_LINK_RE = re.compile(
    r'^INFO: Streaming build results to: (https://[\w./\-]+)')
FAILED_BUILD_LINE = 'FAILED: Build did NOT complete successfully'
BUILD_STATUS_LINE = 'INFO: Build'
TESTS_FAILED_RE = re.compile(r'^INFO: Build completed, \d+ tests? FAILED')
BAZEL_COMMAND_RE = re.compile(
    r'(^| )(?P<command>bazel (.*? )?(?P<type>test|build) .+)')


class InvokeStatus:

  return output


def set_tf_cuda_compute_capabilities(environ_cp):
  """Set TF_CUDA_COMPUTE_CAPABILITIES."""
  while True:
    native_cuda_compute_capabilities = get_native_cuda_compute_capabilities(
        environ_cp)
    if not native_cuda_compute_capabilities:
      default_cuda_compute_capabilities = _DEFAULT_CUDA_COMPUTE_CAPABILITIES
    else:
      default_cuda_compute_capabilities = native_cuda_compute_capabilities

          days-before-issue-stale: 7
          days-before-issue-close: 7
          stale-issue-label: "stale"
          # reason for closed the issue default value is not_planned
          close-issue-reason: completed
          # List of labels to remove when issues/PRs unstale. 
          labels-to-remove-when-unstale: 'stat:awaiting response'
          only-labels: "stat:awaiting response"
          stale-issue-message: > 

# Move the updated file to the appropriate directory
mv "$REQUIREMENTS_LOCK_FILE" ../wheel_test/

TF_CAPI_EXPORT extern void TFE_ContextAsyncWait(TFE_Context* ctx,
                                                TF_Status* status);

// This function will block till the operation that produces `h` has
// completed. This is only valid on local TFE_TensorHandles. The pointer
// returned will be on the device in which the TFE_TensorHandle resides (so e.g.
// for a GPU tensor this will return a pointer to GPU memory). The pointer is