for (int i = 0; i < outputs.size(); i++) {
      if (!null_indices.contains(i)) {
        outputs[i] = fn_outputs[i - skipped_indices];
      } else {
        skipped_indices += 1;
      }
    }
    TF_RETURN_IF_ERROR(ctx->RemoveFunction(fn_name));
    return absl::OkStatus();
  } else {
    return model(ctx, inputs, outputs);
  }
}

Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx) {

      }
      read = gcs_file->file_block_cache->Read(path, offset, n, buffer, status);
    } else {
      read = LoadBufferFromGCS(path, offset, n, buffer, gcs_file, status);
    }
    if (TF_GetCode(status) != TF_OK) return -1;
    if (read < n)
      TF_SetStatus(status, TF_OUT_OF_RANGE, "Read less bytes than requested");
    else
      TF_SetStatus(status, TF_OK, "");
    return read;
  };

  auto dtype = input->DataType();
  if (DataTypeIsFloating(BaseType(dtype)) ||
      DataTypeIsInteger(BaseType(dtype))) {
    return tensorflow::ops::Identity(ctx, input, output, name);
  } else if (!DataTypeIsComplex(BaseType(dtype)) &&
             BaseType(dtype) != DT_VARIANT) {
    return errors::InvalidArgument(
        "Expected numeric or variant tensor, got dtype ", dtype);
  }

# public read-only cache.
# The cache configs are different for MacOS and Linux
if [[ $(uname -s) == "Darwin" ]]; then
  TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_macos_cache_push"
else
  TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_cache_push"

if [[ $TFCI_PYCPP_SWAP_TO_BUILD_ENABLE == 1 ]]; then
   tfrun bazel build $TFCI_BAZEL_COMMON_ARGS --profile "$TFCI_OUTPUT_DIR/profile.json.gz" --config="${TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX}_pycpp_test"
else
   tfrun bazel test $TFCI_BAZEL_COMMON_ARGS --profile "$TFCI_OUTPUT_DIR/profile.json.gz" --config="${TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX}_pycpp_test"
fi

        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f
          docker image prune -af
      - name: Clean repository

    const FullTypeDef* ft;
    mutex_lock l(graph_->mu);
    graph_->graph.NodeType(output_.oper->node.name(), &ft);
    if (ft == nullptr) {
      return FullTypeDef();
    } else {
      return *ft;
    }
  }

  TF_Output output_;

  // For LLVM style RTTI.
  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:

    ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  } else {
    // Handles are on task0 (local), and task2, but op is on task1.
    matmul = MatMulOp(ctx, h0_task0, h1_task2);
  }
  if (remote) {
    TFE_OpSetDevice(matmul, task1_name, status);
    ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  } else if (!async) {
    // Set the local device to CPU to easily validate mirroring

    bool clear_existing_contexts) {
#if defined(IS_MOBILE_PLATFORM)
  status->status = tensorflow::errors::Unimplemented(
      "TFE_ContextSetServerDef not supported on mobile");
#else   // !defined(IS_MOBILE_PLATFORM)
  tensorflow::ServerDef server_def;
  if (!server_def.ParseFromArray(proto, proto_len)) {
    status->status = tensorflow::errors::InvalidArgument(

  if (av_tensor == nullptr) {
    TF_ASSIGN_OR_RETURN(
        *tensor, MakeTensorFromPjRtBuffer(tensor->dtype(), tensor->shape(),
                                          std::move(buffer)));
  } else {
    av_tensor->SetBuffer(std::move(buffer));
  }
  return absl::OkStatus();
}

absl::StatusOr<xla::PjRtCApiClient*> GetPjRtCApiClient(
    const DeviceType& device_type) {