# limitations under the License.
# ==============================================================================

name: PyLint
on:
  pull_request:
    paths:
      - '**.py'

permissions:
  contents: read

jobs:
  build:
    name: PyLint
    runs-on: ubuntu-latest
    steps:
    - name: Checkout code
      uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0

void TF_SetTracingImplementation(const char* name, TF_Status* s) {
  tsl::Set_TF_Status_from_Status(s, SetDefaultTracingEngine(name));
}

// Creates a new TensorFlow function, it is an execution context attached to a
// given tracing context.
TF_ExecutionContext* TF_CreateFunction(const char* fn_name, TF_Status* s) {
  return wrap(CreateTracingExecutionContext(fn_name, s));
}

# ==============================================================================

name: ARM CI Extended C++

on:
  push:
    tags:
      - v2.**
  schedule:
    - cron: '0 2 * * *'

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: ARM CD

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

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:

#include "tensorflow/c/experimental/gradients/nn_grad.h"

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/immediate_execution_context.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"
#include "tensorflow/c/experimental/ops/array_ops.h"
#include "tensorflow/c/experimental/ops/math_ops.h"
#include "tensorflow/c/experimental/ops/nn_ops.h"

  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_Context* context = TFE_NewContext(opts, status.get());
  TFE_DeleteContextOptions(opts);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  bool arrived = false;
  bool executed = false;
  const char* name = "/job:localhost/replica:0/task:0/device:CUSTOM:0";
  RegisterLoggingDevice(context, name, /*strict_scope_placement=*/true,

// Enables only graph collection in RunMetadata on the functions executed from
// this context.
TF_CAPI_EXPORT extern void TFE_ContextEnableGraphCollection(TFE_Context* ctx);

// Disables only graph collection in RunMetadata on the functions executed from
// this context.
TF_CAPI_EXPORT extern void TFE_ContextDisableGraphCollection(TFE_Context* ctx);

// TODO(fishx): Move these monitoring APIs into a separate file.

// Creates a new TensorFlow function. A Function is an execution context, and as
// such it can trace operations through TF_ExecuteOperation. After completing
// tracing, a function can be obtained by TF_FinalizeFunction.
TF_ExecutionContext* TF_CreateFunction(const char* fn_name, TF_Status* status);

// Creates a context for eager execution of operations.
TF_ExecutionContext* TF_NewEagerExecutionContext(TFE_ContextOptions*,

#include "tensorflow/core/platform/logging.h"

namespace tensorflow {

namespace {

// Managing context for the DLManagedTensor, will manage the lifetime of
// DLManagedTensor. When calling DLManagedTensor::deleter, it will notify the
// original framework of destruction, and this context will be deleted also.
struct TfDlManagedTensorCtx {
  TensorReference reference;
  std::vector<int64_t> shape;

name: Set nightly branch to master HEAD

permissions: {}

jobs:
  master-to-nightly:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    runs-on: ubuntu-latest
    permissions:
      contents: write
    steps:
    - uses: zofrex/mirror-branch@a8809f0b42f9dfe9b2c5c2162a46327c23d15266 # v1.0.3
      name: Set nightly branch to master HEAD
      with: