```shell
$ python
```

```python
>>> import tensorflow as tf
>>> tf.add(1, 2).numpy()
3
>>> hello = tf.constant('Hello, TensorFlow!')
>>> hello.numpy()
b'Hello, TensorFlow!'
```

For more examples, see the
[TensorFlow tutorials](https://www.tensorflow.org/tutorials/).

## Contribution guidelines

**If you want to contribute to TensorFlow, be sure to review the

  }

  // Single line mode might have an extra space at the end, due to the internal
  // details of `Printer`.
  TrimTrailingWhitespaces(method_txtpb);

  return method_txtpb;
}

// Applies quantization spec to all matched lifted functions. At this point only
// denylisting (`NoQuantization`) will be applied if specs is nonempty.
// TODO: b/307620778 - Support more advanced selective quantization methods.

  auto func_op_quant_spec = GetStableHloOpQuantSpec;
  auto func_op_quant_scale_spec = GetStableHloQuantConstraints;

  for (auto func_op : module_op.getOps<func::FuncOp>()) {
    // The function might contain more stats ops than required, and it will
    // introduce requantize if the calibration stats have conflicts. This tries
    // to remove all the redundant stats ops.
    RemoveRedundantStatsOps(func_op, func_op_quant_spec,

#include "tensorflow/cc/saved_model/constants.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/framework/node_def.pb.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"
#include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"

namespace tensorflow {
namespace libexport {

      if (!llvm::isa<TFL::ConstOp, TFL::QConstOp, arith::ConstantOp>(op))
        return;

      // We only fold int32/int64 for Const and i32 for QConst if not specify
      // all constants flag. (Since they're more like "configs" or i32 biases.)
      // We will fold every const ops (and q_const ops) if we speicfy the
      // fold_all_constants_flag.
      if (!fold_all_constants_flag_) {
        if (!IsConstOrQConstInt(op)) return;

  cat > $BATS_TEST_TMPDIR/ignore_deps_for_these_packages <<EOF
//tensorflow/lite
//tensorflow/compiler/mlir/lite
//tensorflow/compiler/mlir/tfrt
//tensorflow/core/runtime_fallback
//tensorflow/core/tfrt
//tensorflow/python/kernel_tests/signal
//tensorflow/examples
//tensorflow/tools/android
//tensorflow/python/eager/benchmarks
EOF

#include "tensorflow/cc/experimental/libtf/value.h"
#include "tensorflow/cc/experimental/libtf/value_iostream.h"
#include "tensorflow/core/framework/op_def.pb.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/statusor.h"

namespace tf {
namespace libtf {

using tensorflow::AbstractContext;
using tensorflow::AbstractFunctionPtr;

# Dockerfile for more details:
# - gcr.io/tensorflow-sigs/build-arm64:jax-latest-multi-python
# - gcr.io/tensorflow-sigs/build-arm64:tf-latest-multi-python

set -exo pipefail

function is_continuous_or_release() {
  [[ "$KOKORO_JOB_TYPE" == "CONTINUOUS_INTEGRATION" ]] || [[ "$KOKORO_JOB_TYPE" == "RELEASE" ]]
}

# Move into the directory of the script
cd "$(dirname "$0")"

#include "absl/strings/str_cat.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/lib/hash/hash.h"
#include "tensorflow/core/lib/strings/strcat.h"

namespace tensorflow {

/// @defgroup core Core Tensorflow API

class Output;

/// @addtogroup core
/// @{

/// Represents a node in the computation graph.

# specifically. Use your best judgment to keep the scripts in this directory
# lean and easy to follow. When in doubt, remember that for CI scripts, "keep it
# simple" is MUCH more important than "don't repeat yourself."

# -e: abort script if one command fails
# -u: error if undefined variable used
# -x: log all commands
# -o pipefail: entire command fails if pipe fails. watch out for yes | ...