load(
    "//tensorflow:tensorflow.bzl",
    "tf_cc_test",
)
load("//tensorflow:tensorflow.default.bzl", "filegroup")
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

# Currently pybind extension shared objects must use only C API headers since

# Variables containing version strings extracted from the canonical sources:
# tensorflow/core/public/version.h and tools/pip_package/setup.py.
#
# These variables aren't available by default. Scripts must source this file
# explicitly, *after* checking if update_version.py needs to be run for a
# nightly job. update_version.py affects TF_VER_SUFFIX, TF_VER_PYTHON, and
# TF_VER_FULL.

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Builds and returns a `TracingContext` using the default tracing impl.
AbstractContext* BuildFunction(const char* fn_name);

// Creates parameters (placeholders) in the tracing `ctx` using the shape and
// dtype of `inputs`.
Status CreateParamsForInputs(AbstractContext* ctx,

  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteGraph(graph);
  TF_DeleteStatus(s);
}

// If `device` is non-empty, run Min op on that device.
// Otherwise run it on the default device (CPU).
void RunMinTest(const string& device, bool use_XLA) {
  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Make a placeholder operation.

  // appended later), but should include any information specific to this custom
  // device which would be useful for debugging.
  //
  // Optional. If null, defaults to resolving the TFE_TensorHandle into a
  // TF_Tensor and summarizing that.
  TF_Buffer* (*summarize)(void* data, TF_Status* status) = nullptr;
} TFE_CustomDeviceTensorHandle;

        `tf.keras.utils.is_interactive_logging_enabled()` to check if
        interactive logging is enabled.
    *   Changed default value for the `verbose` argument of `Model.evaluate()`
        and `Model.predict()` to `"auto"`, which defaults to `verbose=1` for
        most cases and defaults to `verbose=2` when used with
        `ParameterServerStrategy` or with interactive logging disabled.

    if (current_grad == accumulated_gradients_.end()) {
      if (IsDtypeTrainable(input_tensors[target_index].GetDType())) {
        // ForwardAccumulator defaults to zeros for unwatched Tensors, unlike
        // GradientTape which uses ones.
        Gradient* zero = input_tensors[target_index].ZerosLike();
        new_zeros.push_back(zero);
        in_grads.push_back(zero);

load("@rules_python//python/pip_install:repositories.bzl", "pip_install_dependencies")

default_python_version = "3.10"

load(
    "//:updater_config_repository.bzl",
    "updater_config_repository",  # @unused
)

updater_config_repository(name = "updater_config_repository")

python_register_multi_toolchains(
    name = "python",
    default_version = default_python_version,
    ignore_root_user_error = True,
    python_versions = [

}

static TracingContext* CreateTracingExecutionContext(const char* fn_name,
                                                     TF_Status* s) {
  if (default_factory) {
    return default_factory(fn_name, s);
  }
  tsl::Set_TF_Status_from_Status(
      s, errors::FailedPrecondition("default_factory is nullptr"));
  return nullptr;
}

}  // end namespace tracing
}  // end namespace tensorflow

RUN /setup.python.sh python3.10 devel.requirements.txt
RUN /setup.python.sh python3.11 devel.requirements.txt
RUN /setup.python.sh python3.12 devel.requirements.txt
# "python3" commands by default run under 3.10