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vllm.profiler.utils

TablePrinter

Source code in vllm/profiler/utils.py 
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class TablePrinter:

    def __init__(self, row_cls: type[dataclasses.dataclass],
                 column_widths: dict[str, int]):
        self.row_cls = row_cls
        self.fieldnames = [x.name for x in dataclasses.fields(row_cls)]
        self.column_widths = column_widths
        assert set(self.column_widths.keys()) == set(self.fieldnames)

    def print_table(self, rows: list[dataclasses.dataclass]):
        self._print_header()
        self._print_line()
        for row in rows:
            self._print_row(row)

    def _print_header(self):
        for i, f in enumerate(self.fieldnames):
            last = (i == len(self.fieldnames) - 1)
            col_width = self.column_widths[f]
            print(trim_string_back(f, col_width).ljust(col_width),
                  end=" | " if not last else "\n")

    def _print_row(self, row):
        assert isinstance(row, self.row_cls)

        for i, f in enumerate(self.fieldnames):
            last = (i == len(self.fieldnames) - 1)
            col_width = self.column_widths[f]
            val = getattr(row, f)

            val_str = ""
            if isinstance(val, str):
                val_str = trim_string_back(val, col_width).ljust(col_width)
            elif type(val) in [float, int]:
                val_str = f"{float(val):>.2f}".rjust(col_width)
            else:
                val_str = f"{val}".rjust(col_width)
            print(val_str, end=" | " if not last else "\n")

    def _print_line(self):
        total_col_width = 0
        for column_width in self.column_widths.values():
            total_col_width += column_width
        print("=" * (total_col_width + 3 * (len(self.column_widths) - 1)))

column_widths instance-attribute 

column_widths = column_widths

fieldnames instance-attribute 

fieldnames = [name for x in fields(row_cls)]

row_cls instance-attribute 

row_cls = row_cls

__init__ 

__init__(
    row_cls: type[dataclass], column_widths: dict[str, int]
)
Source code in vllm/profiler/utils.py 
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def __init__(self, row_cls: type[dataclasses.dataclass],
             column_widths: dict[str, int]):
    self.row_cls = row_cls
    self.fieldnames = [x.name for x in dataclasses.fields(row_cls)]
    self.column_widths = column_widths
    assert set(self.column_widths.keys()) == set(self.fieldnames)

_print_header 

_print_header()
Source code in vllm/profiler/utils.py 
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def _print_header(self):
    for i, f in enumerate(self.fieldnames):
        last = (i == len(self.fieldnames) - 1)
        col_width = self.column_widths[f]
        print(trim_string_back(f, col_width).ljust(col_width),
              end=" | " if not last else "\n")

_print_line 

_print_line()
Source code in vllm/profiler/utils.py 
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def _print_line(self):
    total_col_width = 0
    for column_width in self.column_widths.values():
        total_col_width += column_width
    print("=" * (total_col_width + 3 * (len(self.column_widths) - 1)))

_print_row 

_print_row(row)
Source code in vllm/profiler/utils.py 
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def _print_row(self, row):
    assert isinstance(row, self.row_cls)

    for i, f in enumerate(self.fieldnames):
        last = (i == len(self.fieldnames) - 1)
        col_width = self.column_widths[f]
        val = getattr(row, f)

        val_str = ""
        if isinstance(val, str):
            val_str = trim_string_back(val, col_width).ljust(col_width)
        elif type(val) in [float, int]:
            val_str = f"{float(val):>.2f}".rjust(col_width)
        else:
            val_str = f"{val}".rjust(col_width)
        print(val_str, end=" | " if not last else "\n")

print_table 

print_table(rows: list[dataclass])
Source code in vllm/profiler/utils.py 
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def print_table(self, rows: list[dataclasses.dataclass]):
    self._print_header()
    self._print_line()
    for row in rows:
        self._print_row(row)

event_arg_repr 

event_arg_repr(arg) -> str
Source code in vllm/profiler/utils.py 
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def event_arg_repr(arg) -> str:
    if arg is None or type(arg) in [float, int, bool, str]:
        return f"{arg}"
    elif isinstance(arg, list):
        return f"[{', '.join([event_arg_repr(x) for x in arg])}]"
    elif isinstance(arg, tuple):
        return f"({', '.join([event_arg_repr(x) for x in arg])})"
    else:
        assert isinstance(arg,
                          _TensorMetadata), f"Unsupported type: {type(arg)}"
        sizes_str = ', '.join([str(x) for x in arg.sizes])
        return f"{str(arg.dtype).replace('torch.', '')}[{sizes_str}]"

event_has_module 

event_has_module(event: _ProfilerEvent) -> bool
Source code in vllm/profiler/utils.py 
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def event_has_module(event: _ProfilerEvent) -> bool:
    event_type, typed_event = event.typed
    if event_type == _EventType.PyCall:
        return typed_event.module is not None
    return False

event_is_torch_op 

event_is_torch_op(event: _ProfilerEvent) -> bool
Source code in vllm/profiler/utils.py 
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def event_is_torch_op(event: _ProfilerEvent) -> bool:
    return event.tag == _EventType.TorchOp

event_module_repr 

event_module_repr(event: _ProfilerEvent) -> str
Source code in vllm/profiler/utils.py 
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def event_module_repr(event: _ProfilerEvent) -> str:
    assert event_has_module(event)
    module = event.typed[1].module
    if module.parameters and len(module.parameters) > 0:
        args_str = ', '.join(
            [f'{x[0]}={event_arg_repr(x[1])}' for x in module.parameters])
        return f"{module.cls_name}({args_str})"
    else:
        return module.cls_name

event_torch_op_repr 

event_torch_op_repr(event: _ProfilerEvent) -> str
Source code in vllm/profiler/utils.py 
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def event_torch_op_repr(event: _ProfilerEvent) -> str:
    assert event.tag == _EventType.TorchOp
    args_str = ', '.join([event_arg_repr(x) for x in event.typed[1].inputs])
    return f"{event.name}({args_str})".replace("aten::", "")

event_torch_op_stack_trace 

event_torch_op_stack_trace(
    curr_event: _ProfilerEvent,
    until: Callable[[_ProfilerEvent], bool],
) -> str
Source code in vllm/profiler/utils.py 
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def event_torch_op_stack_trace(curr_event: _ProfilerEvent,
                               until: Callable[[_ProfilerEvent], bool]) -> str:
    trace = ""
    curr_event = curr_event.parent
    while curr_event and not until(curr_event):
        if event_is_torch_op(curr_event):
            if len(trace) > 0:
                trace += " <- "
            trace += event_torch_op_repr(curr_event)
        curr_event = curr_event.parent

    return trace

indent_string 

indent_string(
    string: str,
    indent: int,
    indent_style: Union[Callable[[int], str], str] = " ",
) -> str
Source code in vllm/profiler/utils.py 
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def indent_string(string: str,
                  indent: int,
                  indent_style: Union[Callable[[int], str], str] = " ") -> str:
    if indent:
        if isinstance(indent_style, str):
            return indent_style * indent + string
        else:
            return indent_style(indent) + string
    else:
        return string

trim_string_back 

trim_string_back(string, width)
Source code in vllm/profiler/utils.py 
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def trim_string_back(string, width):
    if len(string) > width:
        offset = len(string) - width + 3
        string = string[:-offset]
        if len(string) > 3:
            string = string + "..."
    return string

trim_string_front 

trim_string_front(string, width)
Source code in vllm/profiler/utils.py 
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def trim_string_front(string, width):
    if len(string) > width:
        offset = len(string) - width + 3
        string = string[offset:]
        if len(string) > 3:
            string = "..." + string[3:]
    return string