-   type: dropdown id: source attributes: label: Source description: Tensorflow

	// Parse bucket encryption xml
	encConfig, err := validateBucketSSEConfig(io.LimitReader(r.Body, maxBucketSSEConfigSize))
	if err != nil {
		apiErr := APIError{
			Code:           "MalformedXML",
			Description:    fmt.Sprintf("%s (%s)", errorCodes[ErrMalformedXML].Description, err),
			HTTPStatusCode: errorCodes[ErrMalformedXML].HTTPStatusCode,
		}
		writeErrorResponse(ctx, w, apiErr, r.URL)
		return
	}

            }
        }

        int pad = lastLength - buffer.length();
        lastLength = buffer.length();
        pad(buffer, pad);
        buffer.append('\r');
        out.print(buffer);
        out.flush();
        buffer.setLength(0);
    }

    private void pad(StringBuilder buffer, int spaces) {
        String block = "                                        ";

		return "rune constant"
	case scanner.String:
		return "string constant"
	case scanner.RawString:
		return "raw string constant"
	case scanner.Comment:
		return "comment"
	default:
		return fmt.Sprintf("%q", rune(t))
	}
}

// NewLexer returns a lexer for the named file and the given link context.
func NewLexer(name string) TokenReader {
	input := NewInput(name)
	fd, err := os.Open(name)
	if err != nil {

else
  "$python" -m pip install *.whl $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS
fi
if [[ "$TFCI_WHL_IMPORT_TEST_ENABLE" == "1" ]]; then
  "$python" -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)'
  "$python" -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)'
fi
# Import tf nightly wheel built with numpy2 from PyPI in numpy1 env for testing.

// Intended to be used in unit tests.
func (b BatchJobYamlErr) message() string {
	return b.msg
}

// Error implements Error interface
func (b BatchJobYamlErr) Error() string {
	return fmt.Sprintf("%s\n Hint: error near line: %d, col: %d", b.msg, b.line, b.col)
}

// BatchJobKV is a key-value data type which supports wildcard matching
type BatchJobKV struct {
	line, col int
	Key       string `yaml:"key" json:"key"`

	}
	return err
}

func (c *CustomSerializer) Value(ctx context.Context, field *schema.Field, dst reflect.Value, fieldValue interface{}) (interface{}, error) {
	return fmt.Sprintf("%s%s", c.prefix, fieldValue), nil
}

func TestSerializer(t *testing.T) {
	schema.RegisterSerializer("custom", NewCustomSerializer("hello"))
	DB.Migrator().DropTable(adaptorSerializerModel(&SerializerStruct{}))

from unittest.mock import patch

from docs_src.python_types.tutorial006_py39 import process_items


def test_process_items():
    with patch("builtins.print") as mock_print:
        process_items(["item_a", "item_b", "item_c"])

    assert mock_print.call_count == 3
    call_args = [arg.args for arg in mock_print.call_args_list]
    assert call_args == [
        ("item_a",),
        ("item_b",),
        ("item_c",),

	z := obj.(*erasureServerPools)

	erasureDisks, err := z.GetDisks(0, 0)
	if err != nil {
		t.Fatal(err)
	}

	for i, test := range testCases {
		t.Run(fmt.Sprintf("case-%d", i), func(t *testing.T) {
			_, err = obj.PutObject(ctx, bucket, object, mustGetPutObjReader(t, bytes.NewReader(data), int64(len(data)), "", ""), ObjectOptions{})
			if err != nil {

			if err != nil {
				t.Fatal(err)
			}

			if err = s3Select.Open(file); err != nil {
				t.Fatal(err)
			}

			fmt.Printf("R: \nE: %s\n" /* string(w.response), */, string(testCase.expectedResult))

			w := &testResponseWriter{}
			s3Select.Evaluate(w)
			s3Select.Close()

			if !reflect.DeepEqual(w.response, testCase.expectedResult) {
				resp := http.Response{