# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

name: ARM CD

on:
  push:
    tags:
      - v2.**
    branches:
      - r2.**
  schedule:
    - cron: '0 8 * * *'

permissions:
  contents: read

jobs:
  build:

    TF_ImportGraphDefOptions* opts, TF_Operation* oper) {
  opts->opts.control_dependencies.push_back(oper->node.name());
}

void TF_ImportGraphDefOptionsAddReturnOutput(TF_ImportGraphDefOptions* opts,
                                             const char* oper_name, int index) {
  opts->tensor_id_data.push_back(oper_name);
  const string& oper_name_str = opts->tensor_id_data.back();

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

name: ARM CI Extended

on:
  push:
    tags:
      - v2.**
  schedule:
    - cron: '0 4 * * *'

permissions:
  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks

        lengths_vector.reserve(s_size);
        for (int i = 0; i < s_size; ++i) {
          const string& v = default_value.list().s(i);
          values_vector.push_back(v.data());
          lengths_vector.push_back(v.size());
        }
        TFE_OpSetAttrStringList(op, attr_name, values_vector.data(),
                                lengths_vector.data(), s_size);
      }

      // Int

    }
    auto* t = dyn_cast<GraphTensor>(outputs[0]);
    if (!t) {
      return tensorflow::errors::InvalidArgument(
          "Unable to cast input to GraphTensor");
    }
    inputs_.push_back(t->output_);
    *output = tensorflow::down_cast<TracingTensorHandle*>(outputs[0]);
    return absl::OkStatus();
  }

  Status Finalize(OutputList* outputs, AbstractFunction** f) override {

          absl::Span<tensorflow::ImmediateExecutionTensorHandle*>(
              tensorflow::unwrap(handles), *num_handles),
          &result);
      return tensorflow::wrap(result);
    }
    tensor_handles.push_back(
        tensorflow::TensorHandleFromInterface(unwrapped_handle));
  }
  tensorflow::EagerContext* context =
      tensorflow::ContextFromInterface(tensorflow::unwrap(ctx));

    *   Support for TensorRT is otherwise unaffected as long as TensorRT is
        already installed on the system.
*   Using .post1 instead of a full minor release allowed us to push this release
    out quickly. However, please note the following caveat:
    *   For users wishing to pin their Python dependency in a requirements file
        or other situation, under Python's version specification rules,

        // GradientTape which uses ones.
        Gradient* zero = input_tensors[target_index].ZerosLike();
        new_zeros.push_back(zero);
        in_grads.push_back(zero);
      } else {
        in_grads.push_back(nullptr);
      }
    } else {
      in_grads.push_back(current_grad->second);
    }
  }

  // Avoid infinite recursion. Whichever forward function we run, it'll end up

    TF_Function* func = TF_FunctionImportFunctionDef(
        binary_proto_buf.data(), binary_proto_buf.size(), status);
    if (!status->status.ok()) return {};
    ret.push_back(UniqueFuncPtr(func, TF_DeleteFunction));
  }
  return ret;
}

TF_Tensor* TF_DequeueNamedTensor(TF_Session* session, int tensor_id,
                                 TF_Status* status) {
  assert(session);

# to build TensorFlow. Look at ci/official/envs to find which types of jobs
# push to the cache.  For macOS, use --config=tf_public_macos_cache
build:tf_public_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/january2024" --remote_upload_local_results=false
# Cache pushes are limited to TF's CI system.
build:tf_public_cache_push --config=tf_public_cache --remote_upload_local_results=true --google_default_credentials