python3 tensorflow/tools/ci_build/update_version.py --nightly
fi

# This generates a pure python wheel of the format "*-py3-none-any.whl"
bazel run --HERMETIC_PYTHON_VERSION=3.13 //tensorflow/tools/pip_package:setup_py_binary -- bdist_wheel --dist-dir "$TFCI_OUTPUT_DIR"

# Get the name of the pure python wheel that was built. This should
# resolve to either
# 1. tensorflow-a.b.c-py3-none-any.whl  or, for nightly builds,

/// info

Notice how `Offer` has a list of `Item`s, which in turn have an optional list of `Image`s

///

## Bodies of pure lists { #bodies-of-pure-lists }

If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models:

```Python

	{"3>>(1<<63)", "negative right shift count"},
	{"(1<<63)>>2", "right shift of value with high bit set"},
	{"(1<<62)>>2", ""},
	{`'\x80'`, "illegal UTF-8 encoding for character constant"},
	{"(23*4", "missing closing paren"},
	{")23*4", "unexpected ) evaluating expression"},
	{"18446744073709551616", "value out of range"},
}

func TestBadExpr(t *testing.T) {
	for i, test := range badExprTests {
		err := runBadTest(i, test, t)

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import jcifs.smb1.util.Hexdump;

/**
 * Unit test for {@link Trans2QueryFSInformation}. The class contains mostly
 * trivial wire-format helpers and a custom {@code toString()} implementation.
 * All tests are pure unit tests – no network or file system access is
 * required.
 */
class Trans2QueryFSInformationTest {

    /** Small helper to create a byte buffer larger than the maximum expected

    // Warning to maintainers: this implementation is highly optimized.
    int utf16Length = sequence.length();
    int utf8Length = utf16Length;
    int i = 0;

    // This loop optimizes for pure ASCII.
    while (i < utf16Length && sequence.charAt(i) < 0x80) {
      i++;
    }

    // This loop optimizes for chars less than 0x800.
    for (; i < utf16Length; i++) {
      char c = sequence.charAt(i);