tfdbg CLI: add initial support for command "run -p": profiler mode
Accompanying changes: * In list_profile / lp output, let the time unit be consistent across all ops, so that the results are easier to read. * Add the --time_unit option flag to list_profile / lp. * Add start time to the lp output table; allow sorting by start time. PiperOrigin-RevId: 155690128
This commit is contained in:
Shanqing Cai
TensorFlower Gardener
parent
e09b0b6ebf
commit
c4c22e7568
@ -44,6 +44,11 @@ COLOR_RED = "red"
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COLOR_WHITE = "white"
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COLOR_YELLOW = "yellow"
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TIME_UNIT_US = "us"
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TIME_UNIT_MS = "ms"
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TIME_UNIT_S = "s"
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TIME_UNITS = [TIME_UNIT_US, TIME_UNIT_MS, TIME_UNIT_S]
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def bytes_to_readable_str(num_bytes, include_b=False):
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"""Generate a human-readable string representing number of bytes.
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@ -75,12 +80,32 @@ def bytes_to_readable_str(num_bytes, include_b=False):
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return result
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def time_to_readable_str(value):
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if not value:
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def time_to_readable_str(value_us, force_time_unit=None):
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"""Convert time value to human-readable string.
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Args:
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value_us: time value in microseconds.
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force_time_unit: force the output to use the specified time unit. Must be
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in TIME_UNITS.
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Returns:
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Human-readable string representation of the time value.
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Raises:
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ValueError: if force_time_unit value is not in TIME_UNITS.
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"""
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if not value_us:
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return "0"
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suffixes = ["us", "ms", "s"]
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order = min(len(suffixes) - 1, int(math.log(value, 10) / 3))
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return "{:.3g}{}".format(value / math.pow(10.0, 3*order), suffixes[order])
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if force_time_unit:
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if force_time_unit not in TIME_UNITS:
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raise ValueError("Invalid time unit: %s" % force_time_unit)
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order = TIME_UNITS.index(force_time_unit)
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time_unit = force_time_unit
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return "{:.10g}{}".format(value_us / math.pow(10.0, 3*order), time_unit)
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else:
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order = min(len(TIME_UNITS) - 1, int(math.log(value_us, 10) / 3))
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time_unit = TIME_UNITS[order]
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return "{:.3g}{}".format(value_us / math.pow(10.0, 3*order), time_unit)
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def parse_ranges_highlight(ranges_string):
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@ -84,6 +84,26 @@ class TimeToReadableStrTest(test_util.TensorFlowTestCase):
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def testSecondTime(self):
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self.assertEqual("40s", cli_shared.time_to_readable_str(40e6))
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def testForceTimeUnit(self):
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self.assertEqual("40s",
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cli_shared.time_to_readable_str(
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40e6, force_time_unit=cli_shared.TIME_UNIT_S))
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self.assertEqual("40000ms",
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cli_shared.time_to_readable_str(
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40e6, force_time_unit=cli_shared.TIME_UNIT_MS))
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self.assertEqual("40000000us",
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cli_shared.time_to_readable_str(
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40e6, force_time_unit=cli_shared.TIME_UNIT_US))
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self.assertEqual("4e-05s",
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cli_shared.time_to_readable_str(
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40, force_time_unit=cli_shared.TIME_UNIT_S))
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self.assertEqual("0",
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cli_shared.time_to_readable_str(
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0, force_time_unit=cli_shared.TIME_UNIT_S))
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with self.assertRaisesRegexp(ValueError, r"Invalid time unit: ks"):
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cli_shared.time_to_readable_str(100, force_time_unit="ks")
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class GetRunStartIntroAndDescriptionTest(test_util.TensorFlowTestCase):
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@ -50,6 +50,7 @@ class ProfileDatum(object):
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self.node_exec_stats = node_exec_stats
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self.file_line = file_line
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self.op_type = op_type
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self.start_time = self.node_exec_stats.all_start_micros
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self.op_time = (self.node_exec_stats.op_end_rel_micros -
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self.node_exec_stats.op_start_rel_micros)
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@ -62,31 +63,45 @@ class ProfileDatum(object):
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class ProfileDataTableView(object):
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"""Table View of profiling data."""
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def __init__(self, profile_datum_list):
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def __init__(self, profile_datum_list, time_unit=cli_shared.TIME_UNIT_US):
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"""Constructor.
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Args:
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profile_datum_list: List of `ProfileDatum` objects.
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time_unit: must be in cli_shared.TIME_UNITS.
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"""
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self._profile_datum_list = profile_datum_list
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self.formatted_start_time = [
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datum.start_time for datum in profile_datum_list]
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self.formatted_op_time = [
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cli_shared.time_to_readable_str(datum.op_time)
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cli_shared.time_to_readable_str(datum.op_time,
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force_time_unit=time_unit)
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for datum in profile_datum_list]
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self.formatted_exec_time = [
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cli_shared.time_to_readable_str(
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datum.node_exec_stats.all_end_rel_micros)
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datum.node_exec_stats.all_end_rel_micros,
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force_time_unit=time_unit)
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for datum in profile_datum_list]
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self._column_sort_ids = [SORT_OPS_BY_OP_NAME, SORT_OPS_BY_OP_TIME,
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SORT_OPS_BY_EXEC_TIME, SORT_OPS_BY_LINE]
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self._column_names = ["Node",
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"Start Time (us)",
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"Op Time (%s)" % time_unit,
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"Exec Time (%s)" % time_unit,
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"Filename:Lineno(function)"]
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self._column_sort_ids = [SORT_OPS_BY_OP_NAME, SORT_OPS_BY_START_TIME,
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SORT_OPS_BY_OP_TIME, SORT_OPS_BY_EXEC_TIME,
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SORT_OPS_BY_LINE]
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def value(self, row, col):
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if col == 0:
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return self._profile_datum_list[row].node_exec_stats.node_name
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elif col == 1:
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return self.formatted_op_time[row]
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return self.formatted_start_time[row]
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elif col == 2:
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return self.formatted_exec_time[row]
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return self.formatted_op_time[row]
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elif col == 3:
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return self.formatted_exec_time[row]
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elif col == 4:
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return self._profile_datum_list[row].file_line
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else:
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raise IndexError("Invalid column index %d." % col)
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@ -95,10 +110,10 @@ class ProfileDataTableView(object):
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return len(self._profile_datum_list)
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def column_count(self):
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return 4
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return len(self._column_names)
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def column_names(self):
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return ["Node", "Op Time", "Exec Time", "Filename:Lineno(function)"]
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return self._column_names
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def column_sort_id(self, col):
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return self._column_sort_ids[col]
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@ -246,6 +261,12 @@ class ProfileAnalyzer(object):
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dest="reverse",
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action="store_true",
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help="sort the data in reverse (descending) order")
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ap.add_argument(
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"--time_unit",
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dest="time_unit",
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type=str,
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default=cli_shared.TIME_UNIT_US,
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help="Time unit (" + " | ".join(cli_shared.TIME_UNITS) + ")")
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self._arg_parsers["list_profile"] = ap
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@ -294,7 +315,7 @@ class ProfileAnalyzer(object):
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output.extend(
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self._get_list_profile_lines(
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device_stats.device, index, device_count,
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profile_data, parsed.sort_by, parsed.reverse))
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profile_data, parsed.sort_by, parsed.reverse, parsed.time_unit))
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return output
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def _get_profile_data_generator(self):
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@ -328,7 +349,7 @@ class ProfileAnalyzer(object):
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def _get_list_profile_lines(
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self, device_name, device_index, device_count,
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profile_datum_list, sort_by, sort_reverse):
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profile_datum_list, sort_by, sort_reverse, time_unit):
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"""Get `RichTextLines` object for list_profile command for a given device.
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Args:
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@ -341,20 +362,24 @@ class ProfileAnalyzer(object):
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SORT_OPS_BY_MEMORY or SORT_OPS_BY_LINE.
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sort_reverse: (bool) Whether to sort in descending instead of default
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(ascending) order.
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time_unit: time unit, must be in cli_shared.TIME_UNITS.
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Returns:
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`RichTextLines` object containing a table that displays profiling
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information for each op.
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"""
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profile_data = ProfileDataTableView(profile_datum_list)
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profile_data = ProfileDataTableView(profile_datum_list, time_unit=time_unit)
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# Calculate total time early to calculate column widths.
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total_op_time = sum(datum.op_time for datum in profile_datum_list)
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total_exec_time = sum(datum.node_exec_stats.all_end_rel_micros
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for datum in profile_datum_list)
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device_total_row = [
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"Device Total", cli_shared.time_to_readable_str(total_op_time),
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cli_shared.time_to_readable_str(total_exec_time)]
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"Device Total", "",
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cli_shared.time_to_readable_str(total_op_time,
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force_time_unit=time_unit),
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cli_shared.time_to_readable_str(total_exec_time,
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force_time_unit=time_unit)]
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# Calculate column widths.
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column_widths = [
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@ -130,7 +130,8 @@ class ProfileAnalyzerTest(test_util.TensorFlowTestCase):
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self._assertAtLeastOneLineMatches("Device 1 of", prof_output)
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expected_headers = [
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"Node", "Op Time", "Exec Time", r"Filename:Lineno\(function\)"]
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"Node", r"Start Time \(us\)", r"Op Time \(.*\)", r"Exec Time \(.*\)",
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r"Filename:Lineno\(function\)"]
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self._assertAtLeastOneLineMatches(
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".*".join(expected_headers), prof_output)
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self._assertAtLeastOneLineMatches(r"^Add/", prof_output)
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@ -242,10 +243,49 @@ class ProfileAnalyzerTest(test_util.TensorFlowTestCase):
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self._assertAtLeastOneLineMatches(r"Add/123", prof_output)
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self._assertNoLinesMatch(r"Mul/456", prof_output)
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def testSpecifyingTimeUnit(self):
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node1 = step_stats_pb2.NodeExecStats(
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node_name="Add/123",
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all_start_micros=123,
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op_start_rel_micros=3,
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op_end_rel_micros=5,
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all_end_rel_micros=4)
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node2 = step_stats_pb2.NodeExecStats(
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node_name="Mul/456",
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all_start_micros=122,
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op_start_rel_micros=1,
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op_end_rel_micros=2,
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all_end_rel_micros=5)
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run_metadata = config_pb2.RunMetadata()
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device1 = run_metadata.step_stats.dev_stats.add()
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device1.device = "deviceA"
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device1.node_stats.extend([node1, node2])
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graph = test.mock.MagicMock()
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op1 = test.mock.MagicMock()
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op1.name = "Add/123"
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op1.traceback = [("a/b/file2", 10, "some_var")]
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op1.type = "add"
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op2 = test.mock.MagicMock()
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op2.name = "Mul/456"
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op2.traceback = [("a/b/file1", 11, "some_var")]
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op2.type = "mul"
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graph.get_operations.return_value = [op1, op2]
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prof_analyzer = profile_analyzer_cli.ProfileAnalyzer(graph, run_metadata)
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# Force time unit.
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prof_output = prof_analyzer.list_profile(["--time_unit", "ms"]).lines
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self._assertAtLeastOneLineMatches(r"Add/123.*0\.002ms", prof_output)
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self._assertAtLeastOneLineMatches(r"Mul/456.*0\.005ms", prof_output)
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self._assertAtLeastOneLineMatches(r"Device Total.*0\.009ms", prof_output)
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def _atLeastOneLineMatches(self, pattern, lines):
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pattern_re = re.compile(pattern)
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for line in lines:
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if pattern_re.match(line):
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if pattern_re.search(line):
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return True
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return False
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@ -76,7 +76,8 @@ EOF
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CUSTOM_DUMP_ROOT=$(mktemp -d)
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mkdir -p ${CUSTOM_DUMP_ROOT}
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cat << EOF | ${DEBUG_TFLEARN_IRIS_BIN} --debug --fake_data --train_steps=1 --dump_root="${CUSTOM_DUMP_ROOT}" --ui_type=readline
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cat << EOF | ${DEBUG_TFLEARN_IRIS_BIN} --debug --fake_data --train_steps=2 --dump_root="${CUSTOM_DUMP_ROOT}" --ui_type=readline
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run -p
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run -f has_inf_or_nan
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EOF
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@ -219,6 +219,9 @@ class OnRunStartAction(object):
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# Run once with debug tensor-watching.
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DEBUG_RUN = "debug_run"
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# Run once with profiler.
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PROFILE_RUN = "profile_run"
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# Run without debug tensor-watching.
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NON_DEBUG_RUN = "non_debug_run"
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@ -425,7 +428,7 @@ class BaseDebugWrapperSession(session.SessionInterface):
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decorated_run_options = options or config_pb2.RunOptions()
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run_metadata = run_metadata or config_pb2.RunMetadata()
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self._decorate_run_options(
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self._decorate_run_options_for_debug(
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decorated_run_options,
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run_start_resp.debug_urls,
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debug_ops=run_start_resp.debug_ops,
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@ -454,6 +457,19 @@ class BaseDebugWrapperSession(session.SessionInterface):
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client_graph_def=self._sess.graph.as_graph_def(),
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tf_error=tf_error)
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elif run_start_resp.action == OnRunStartAction.PROFILE_RUN:
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decorated_run_options = options or config_pb2.RunOptions()
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run_metadata = run_metadata or config_pb2.RunMetadata()
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self._decorate_run_options_for_profile(decorated_run_options)
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retvals = self._sess.run(fetches,
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feed_dict=feed_dict,
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options=decorated_run_options,
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run_metadata=run_metadata)
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run_end_req = OnRunEndRequest(
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run_start_resp.action,
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run_metadata=run_metadata,
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client_graph_def=self._sess.graph.as_graph_def())
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elif (run_start_resp.action == OnRunStartAction.NON_DEBUG_RUN or
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run_start_resp.action == OnRunStartAction.INVOKE_STEPPER):
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if run_start_resp.action == OnRunStartAction.INVOKE_STEPPER:
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@ -496,14 +512,15 @@ class BaseDebugWrapperSession(session.SessionInterface):
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raise NotImplementedError(
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"partial_run is not implemented for debug-wrapper sessions.")
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def _decorate_run_options(self,
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run_options,
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debug_urls,
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debug_ops="DebugIdentity",
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node_name_regex_whitelist=None,
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op_type_regex_whitelist=None,
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tensor_dtype_regex_whitelist=None,
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tolerate_debug_op_creation_failures=False):
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def _decorate_run_options_for_debug(
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self,
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run_options,
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debug_urls,
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debug_ops="DebugIdentity",
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node_name_regex_whitelist=None,
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op_type_regex_whitelist=None,
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tensor_dtype_regex_whitelist=None,
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tolerate_debug_op_creation_failures=False):
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"""Modify a RunOptions object for debug tensor watching.
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Specifies request for outputting partition graphs. Adds
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@ -534,6 +551,15 @@ class BaseDebugWrapperSession(session.SessionInterface):
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tensor_dtype_regex_whitelist=tensor_dtype_regex_whitelist,
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tolerate_debug_op_creation_failures=tolerate_debug_op_creation_failures)
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def _decorate_run_options_for_profile(self, run_options):
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"""Modify a RunOptions object for profiling TensorFlow graph execution.
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Args:
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run_options: (RunOptions) the modified RunOptions object.
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"""
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run_options.trace_level = config_pb2.RunOptions.FULL_TRACE
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@abc.abstractmethod
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def on_session_init(self, request):
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"""Callback invoked during construction of the debug-wrapper session.
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@ -130,6 +130,8 @@ class LocalCLIDebugHook(session_run_hook.SessionRunHook,
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on_run_start_response.tensor_dtype_regex_whitelist),
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tolerate_debug_op_creation_failures=(
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on_run_start_response.tolerate_debug_op_creation_failures)))
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elif self._performed_action == framework.OnRunStartAction.PROFILE_RUN:
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self._decorate_run_options_for_profile(run_args.options)
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elif self._performed_action == framework.OnRunStartAction.INVOKE_STEPPER:
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# The _finalized property must be set to False so that the NodeStepper
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# can insert ops for retrieving TensorHandles.
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@ -27,6 +27,7 @@ import tempfile
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from tensorflow.python.debug.cli import analyzer_cli
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from tensorflow.python.debug.cli import cli_shared
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from tensorflow.python.debug.cli import debugger_cli_common
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from tensorflow.python.debug.cli import profile_analyzer_cli
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from tensorflow.python.debug.cli import stepper_cli
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from tensorflow.python.debug.cli import ui_factory
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from tensorflow.python.debug.lib import debug_data
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@ -162,6 +163,12 @@ class LocalCLIDebugWrapperSession(framework.BaseDebugWrapperSession):
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default="",
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help="Regular-expression filter for tensor dtype to be watched in the "
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"run, e.g., (float32|float64), int.*")
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ap.add_argument(
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"-p",
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"--profile",
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dest="profile",
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action="store_true",
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help="Run and profile TensorFlow graph execution.")
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self._argparsers["run"] = ap
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ap = argparse.ArgumentParser(
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@ -318,12 +325,16 @@ class LocalCLIDebugWrapperSession(framework.BaseDebugWrapperSession):
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passed_filter = self._active_tensor_filter
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self._active_tensor_filter = None
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self._prep_cli_for_run_end(debug_dump, request.tf_error, passed_filter)
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self._prep_debug_cli_for_run_end(
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debug_dump, request.tf_error, passed_filter)
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self._run_start_response = self._launch_cli()
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# Clean up the dump generated by this run.
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||||
self._remove_dump_root()
|
||||
elif request.performed_action == framework.OnRunStartAction.PROFILE_RUN:
|
||||
self._prep_profile_cli_for_run_end(self._sess.graph, request.run_metadata)
|
||||
self._run_start_response = self._launch_cli()
|
||||
else:
|
||||
# No debug information to show following a non-debug run() call.
|
||||
self._run_start_response = None
|
||||
@ -336,7 +347,7 @@ class LocalCLIDebugWrapperSession(framework.BaseDebugWrapperSession):
|
||||
if os.path.isdir(self._dump_root):
|
||||
shutil.rmtree(self._dump_root)
|
||||
|
||||
def _prep_cli_for_run_end(self, debug_dump, tf_error, passed_filter):
|
||||
def _prep_debug_cli_for_run_end(self, debug_dump, tf_error, passed_filter):
|
||||
"""Prepare (but not launch) CLI for run-end, with debug dump from the run.
|
||||
|
||||
Args:
|
||||
@ -391,6 +402,12 @@ class LocalCLIDebugWrapperSession(framework.BaseDebugWrapperSession):
|
||||
if help_intro:
|
||||
self._run_cli.set_help_intro(help_intro)
|
||||
|
||||
def _prep_profile_cli_for_run_end(self, py_graph, run_metadata):
|
||||
self._init_command = "lp"
|
||||
self._run_cli = profile_analyzer_cli.create_profiler_ui(
|
||||
py_graph, run_metadata, ui_type=self._ui_type)
|
||||
self._title = "run-end (profiler mode): " + self._run_description
|
||||
|
||||
def _launch_cli(self):
|
||||
"""Launch the interactive command-line interface.
|
||||
|
||||
@ -425,13 +442,18 @@ class LocalCLIDebugWrapperSession(framework.BaseDebugWrapperSession):
|
||||
def _run_handler(self, args, screen_info=None):
|
||||
"""Command handler for "run" command during on-run-start."""
|
||||
|
||||
_ = screen_info # Currently unused.
|
||||
del screen_info # Currently unused.
|
||||
|
||||
parsed = self._argparsers["run"].parse_args(args)
|
||||
parsed.node_name_filter = parsed.node_name_filter or None
|
||||
parsed.op_type_filter = parsed.op_type_filter or None
|
||||
parsed.tensor_dtype_filter = parsed.tensor_dtype_filter or None
|
||||
|
||||
if parsed.profile:
|
||||
raise debugger_cli_common.CommandLineExit(
|
||||
exit_token=framework.OnRunStartResponse(
|
||||
framework.OnRunStartAction.PROFILE_RUN, []))
|
||||
|
||||
if parsed.till_filter_pass:
|
||||
# For the run-till-bad-numerical-value-appears mode, use the DEBUG_RUN
|
||||
# option to access the intermediate tensors, and set the corresponding
|
||||
|
||||
@ -71,15 +71,21 @@ class LocalCLIDebuggerWrapperSessionForTest(
|
||||
"tf_errors": [],
|
||||
"run_start_cli_run_numbers": [],
|
||||
"run_end_cli_run_numbers": [],
|
||||
"profiler_py_graphs": [],
|
||||
"profiler_run_metadata": [],
|
||||
}
|
||||
|
||||
def _prep_cli_for_run_start(self):
|
||||
pass
|
||||
|
||||
def _prep_cli_for_run_end(self, debug_dump, tf_error, passed_filter):
|
||||
def _prep_debug_cli_for_run_end(self, debug_dump, tf_error, passed_filter):
|
||||
self.observers["debug_dumps"].append(debug_dump)
|
||||
self.observers["tf_errors"].append(tf_error)
|
||||
|
||||
def _prep_profile_cli_for_run_end(self, py_graph, run_metadata):
|
||||
self.observers["profiler_py_graphs"].append(py_graph)
|
||||
self.observers["profiler_run_metadata"].append(run_metadata)
|
||||
|
||||
def _launch_cli(self):
|
||||
if self._is_run_start:
|
||||
self.observers["run_start_cli_run_numbers"].append(self._run_call_count)
|
||||
@ -468,6 +474,19 @@ class LocalCLIDebugWrapperSessionTest(test_util.TensorFlowTestCase):
|
||||
self.assertEqual(1, dumps.size)
|
||||
self.assertEqual("w_int_inner", dumps.dumped_tensor_data[0].node_name)
|
||||
|
||||
def testRunUnderProfilerModeWorks(self):
|
||||
wrapped_sess = LocalCLIDebuggerWrapperSessionForTest(
|
||||
[["-p"], []], self.sess)
|
||||
|
||||
wrapped_sess.run(self.w_int)
|
||||
|
||||
self.assertEqual(1, len(wrapped_sess.observers["profiler_run_metadata"]))
|
||||
self.assertTrue(
|
||||
wrapped_sess.observers["profiler_run_metadata"][0].step_stats)
|
||||
self.assertEqual(1, len(wrapped_sess.observers["profiler_py_graphs"]))
|
||||
self.assertIsInstance(
|
||||
wrapped_sess.observers["profiler_py_graphs"][0], ops.Graph)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
googletest.main()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user