} else if (typestr == "list(float)") {
            metadata.type = TF_ATTR_FLOAT;
          } else if (typestr == "list(bool)") {
            metadata.type = TF_ATTR_BOOL;
          } else if (typestr == "list(type)") {
            metadata.type = TF_ATTR_TYPE;
          } else if (typestr == "list(shape)") {
            metadata.type = TF_ATTR_SHAPE;
          } else if (typestr == "list(tensor)") {

_tf_api_dir = _os.path.dirname(_os.path.dirname(_API_MODULE.__file__))
_current_module = _sys.modules[__name__]

if not hasattr(_current_module, "__path__"):
  __path__ = [_tf_api_dir]
elif _tf_api_dir not in __path__:
  __path__.append(_tf_api_dir)

# Hook external TensorFlow modules.

# Load tensorflow-io-gcs-filesystem if enabled
if (_os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "true" or
    _os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "1"):

permissions:
  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: [self-hosted, linux, ARM64]
    strategy:
      fail-fast: false
      matrix:
        pyver: ['3.9', '3.10', '3.11', '3.12']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |

    // Calculate Grad
    std::string name = "relu_grad";
    TF_RETURN_IF_ERROR(ReluGrad(ctx, upstream_grad, activations,
                                &grad_inputs[0], name.c_str()));
    return absl::OkStatus();
  }
  ~ReluGradientFunction() override {
    for (auto output : forward_outputs_) {
      if (output) {
        output->Unref();
      }
    }
  }

 private:

permissions:
  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: [self-hosted, linux, ARM64]
    strategy:
      matrix:
        pyver: ['3.10']
    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then

 	    if (cp[cnt] != usrc[cnt])
 	      break;
 
-	  if (cnt < nhere - 1)
+	  if (cnt < nhere - 1 || cnt == len)
 	    {
 	      cp += 2 * nhere;
 	      continue;
 	    }
 
-	  if (cp[nhere - 1] > usrc[nhere -1])
+	  if (cp[nhere - 1] > usrc[nhere - 1])
 	    {
 	      cp += 2 * nhere;
 	      continue;
 	    }
 
-	  if (cp[2 * nhere - 1] < usrc[nhere -1])

  TracingContext* tracing_ctx = dyn_cast<TracingContext>(unwrap(func));
  if (!tracing_ctx) {
    tsl::Set_TF_Status_from_Status(
        s, tensorflow::errors::InvalidArgument(
               "TF_AddFunctionParameter must be called on a TracingContext."));
    return nullptr;
  }
  tensorflow::PartialTensorShape partial_shape;
  if (shape.num_dims != -1) {
    DCHECK(shape.dim_sizes != nullptr);

  if [[ -s $BATS_TEST_TMPDIR/actual_extra_licenses ]]; then
    echo "Please remove the following extra licenses from $LICENSES_TARGET:"
    cat $BATS_TEST_TMPDIR/actual_extra_licenses
  fi

  if [[ -s $BATS_TEST_TMPDIR/actual_missing_licenses ]]; then

                                                  TF_Status* status);

// Returns the device of the operation that produced `h`. If `h` was produced by
// a copy, returns the destination device of the copy. Note that the returned
// device name is not always the device holding the tensor handle's memory. If
// you want the latter, use TFE_TensorHandleBackingDeviceName. This function
// will block till the operation that produces `h` has completed.

  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.
"""
contrib = _LazyLoader("contrib", globals(), "tensorflow.contrib",
                      _CONTRIB_WARNING)
# The templated code that replaces the placeholder above sometimes
# sets the __all__ variable. If it does, we have to be sure to add
# "contrib".
if "__all__" in vars():
  vars()["__all__"].append("contrib")