git diff --diff-filter ACMRT --name-only origin/master > $BATS_FILE_TMPDIR/changed_files
    fi
}

# Note: this is excluded on the full code base, since any submitted code must
# have passed Google's internal style guidelines.
@test "Check buildifier formatting on BUILD files" {
    echo "buildifier formatting is recommended. Here are the suggested fixes:"
    echo "============================="

  tests_failed = 'tests_failed'
  build_failed = 'build_failed'
  passed = 'passed'


def parse_args() -> argparse.Namespace:
  """Parses the commandline args."""
  parser = argparse.ArgumentParser(
      description='Extracts ResultStore links from a build log.\n'
                  'These can be then printed out, and/or output into a '
                  'JUnit-based XML file inside a specified directory.')

# JAX requirements, passed into container by defining the ARG 
# REQUIREMENTS_FILE=jax.requirements.txt


setuptools
wheel
cloudpickle
colorama>=0.4.4
matplotlib
pillow>=9.1.0
rich
absl-py
portpicker
six
opt-einsum
auditwheel
typing_extensions
importlib_metadata>=4.6
numpy==1.26.0;python_version=="3.12"
numpy==1.23.4;python_version=="3.11"
numpy==1.22.4;python_version<"3.11"
scipy==1.11.2;python_version=="3.12"

}

// For TFE_CustomDevice::copy_tensor_to_device in the parallel device
// registration.
//
// Since this function is used to satisfy the TFE_CustomDevice C API,
// device_info is passed in using a C-style generic. It must always be a
// ParallelDevice.
TFE_TensorHandle* CopyToParallelDevice(TFE_Context* context,
                                       TFE_TensorHandle* tensor,

}

// -------------------------  VariableInfo  ------------------------------------
struct TF_VariableInfo {
  TF_VariableInfo() = delete;
  // TF_VariableInfo is constructed here by TensorFlow, and will be passed to
  // plugin as a opaque pointer. Plugin will need to call C APIs below to
  // operate on TF_VariableInfo (such as allocate temp tensor for the `var` held
  // by the underlying tensorflow::VariableInfo.

                                  TF_Status* status) {
  tensorflow::AttrValue attr_value;
  if (!attr_value.ParseFromArray(proto, proto_len)) {
    status->status = InvalidArgument(
        "Unparseable AttrValue proto passed to "
        "TF_FunctionSetAttrValueProto");
    return;
  }

  auto fdef_or = func->record->mutable_fdef();
  if (!fdef_or.ok()) {
    status->status = fdef_or.status();
    return;
  }

//
// Conventions:
// * We use the prefix TF_ for everything in the API.
// * Objects are always passed around as pointers to opaque structs
//   and these structs are allocated/deallocated via the API.
// * TF_Status holds error information.  It is an object type
//   and therefore is passed around as a pointer to an opaque
//   struct as mentioned above.
// * Every call that has a TF_Status* argument clears it on success

    unsigned char enable);
TF_CAPI_EXPORT unsigned char TF_SetTfXlaCpuGlobalJit(unsigned char enable);

// Sets XLA's auto jit mode according to the specified string, which is parsed
// as if passed in XLA_FLAGS. This has global effect.
TF_CAPI_EXPORT void TF_SetXlaAutoJitMode(const char* mode);

// Returns whether the single GPU or general XLA auto jit optimizations are
// enabled through MarkForCompilationPassFlags.

  // a tensor with the result.
  virtual Gradient* AggregateGradients(
      gtl::ArraySlice<Gradient*> gradient_tensors) const = 0;

  // Calls the passed-in backward function.
  //
  // `unneeded_gradients` contains sorted list of input indices for which a
  // gradient is not required.
  virtual Status CallBackwardFunction(

// function. Otherwise return nullptr in result and error Status from the
// function.
//
// If `library_filename` has already been loaded, we return a cached handle.
// Device and Kernels/Ops are registered as globals when a library is loaded
// for the first time.
TF_Library* TF_LoadPluggableDeviceLibrary(const char* library_filename,