# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """TensorFlow monitoring APIs.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import collections import functools import time from tensorflow.core.framework import summary_pb2 from tensorflow.python import pywrap_tfe from tensorflow.python.client import pywrap_tf_session from tensorflow.python.framework import c_api_util from tensorflow.python.util import compat _MetricMethod = collections.namedtuple('MetricMethod', 'create delete get_cell') _counter_methods = [ _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewCounter0, delete=pywrap_tfe.TFE_MonitoringDeleteCounter0, get_cell=pywrap_tfe.TFE_MonitoringGetCellCounter0), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewCounter1, delete=pywrap_tfe.TFE_MonitoringDeleteCounter1, get_cell=pywrap_tfe.TFE_MonitoringGetCellCounter1), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewCounter2, delete=pywrap_tfe.TFE_MonitoringDeleteCounter2, get_cell=pywrap_tfe.TFE_MonitoringGetCellCounter2), ] _int_gauge_methods = [ _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewIntGauge0, delete=pywrap_tfe.TFE_MonitoringDeleteIntGauge0, get_cell=pywrap_tfe.TFE_MonitoringGetCellIntGauge0), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewIntGauge1, delete=pywrap_tfe.TFE_MonitoringDeleteIntGauge1, get_cell=pywrap_tfe.TFE_MonitoringGetCellIntGauge1), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewIntGauge2, delete=pywrap_tfe.TFE_MonitoringDeleteIntGauge2, get_cell=pywrap_tfe.TFE_MonitoringGetCellIntGauge2), ] _string_gauge_methods = [ _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewStringGauge0, delete=pywrap_tfe.TFE_MonitoringDeleteStringGauge0, get_cell=pywrap_tfe.TFE_MonitoringGetCellStringGauge0), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewStringGauge1, delete=pywrap_tfe.TFE_MonitoringDeleteStringGauge1, get_cell=pywrap_tfe.TFE_MonitoringGetCellStringGauge1), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewStringGauge2, delete=pywrap_tfe.TFE_MonitoringDeleteStringGauge2, get_cell=pywrap_tfe.TFE_MonitoringGetCellStringGauge2), ] _bool_gauge_methods = [ _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewBoolGauge0, delete=pywrap_tfe.TFE_MonitoringDeleteBoolGauge0, get_cell=pywrap_tfe.TFE_MonitoringGetCellBoolGauge0), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewBoolGauge1, delete=pywrap_tfe.TFE_MonitoringDeleteBoolGauge1, get_cell=pywrap_tfe.TFE_MonitoringGetCellBoolGauge1), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewBoolGauge2, delete=pywrap_tfe.TFE_MonitoringDeleteBoolGauge2, get_cell=pywrap_tfe.TFE_MonitoringGetCellBoolGauge2), ] _sampler_methods = [ _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewSampler0, delete=pywrap_tfe.TFE_MonitoringDeleteSampler0, get_cell=pywrap_tfe.TFE_MonitoringGetCellSampler0), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewSampler1, delete=pywrap_tfe.TFE_MonitoringDeleteSampler1, get_cell=pywrap_tfe.TFE_MonitoringGetCellSampler1), _MetricMethod( create=pywrap_tfe.TFE_MonitoringNewSampler2, delete=pywrap_tfe.TFE_MonitoringDeleteSampler2, get_cell=pywrap_tfe.TFE_MonitoringGetCellSampler2), ] class Metric(object): """The base class of metric.""" __slots__ = ["_metric", "_metric_name", "_metric_methods", "_label_length"] def __init__(self, metric_name, metric_methods, label_length, *args): """Creates a new metric. Args: metric_name: name of the metric class. metric_methods: list of swig metric methods. label_length: length of label args. *args: the arguments to call create method. """ self._metric_name = metric_name self._metric_methods = metric_methods self._label_length = label_length if label_length >= len(self._metric_methods): raise ValueError('Cannot create {} metric with label >= {}'.format( self._metric_name, len(self._metric_methods))) self._metric = self._metric_methods[self._label_length].create(*args) def __del__(self): try: deleter = self._metric_methods[self._label_length].delete metric = self._metric except AttributeError: return if deleter is not None: deleter(metric) def get_cell(self, *labels): """Retrieves the cell.""" if len(labels) != self._label_length: raise ValueError('The {} expects taking {} labels'.format( self._metric_name, self._label_length)) return self._metric_methods[self._label_length].get_cell( self._metric, *labels) class CounterCell(object): """CounterCell stores each value of a Counter.""" __slots__ = ["_cell"] def __init__(self, cell): """Creates a new CounterCell. Args: cell: A c pointer of TFE_MonitoringCounterCell. """ self._cell = cell def increase_by(self, value): """Atomically increments the value. Args: value: non-negative value. """ pywrap_tfe.TFE_MonitoringCounterCellIncrementBy(self._cell, value) def value(self): """Retrieves the current value.""" return pywrap_tfe.TFE_MonitoringCounterCellValue(self._cell) class Counter(Metric): """A stateful class for updating a cumulative integer metric. This class encapsulates a set of values (or a single value for a label-less metric). Each value is identified by a tuple of labels. The class allows the user to increment each value. """ __slots__ = [] def __init__(self, name, description, *labels): """Creates a new Counter. Args: name: name of the new metric. description: description of the new metric. *labels: The label list of the new metric. """ super(Counter, self).__init__('Counter', _counter_methods, len(labels), name, description, *labels) def get_cell(self, *labels): """Retrieves the cell.""" return CounterCell(super(Counter, self).get_cell(*labels)) class IntGaugeCell(object): """A single integer value stored in an `IntGauge`.""" __slots__ = ["_cell"] def __init__(self, cell): """Creates a new IntGaugeCell. Args: cell: A c pointer of TFE_MonitoringIntGaugeCell. """ self._cell = cell def set(self, value): """Atomically set the value. Args: value: integer value. """ pywrap_tfe.TFE_MonitoringIntGaugeCellSet(self._cell, value) def value(self): """Retrieves the current value.""" return pywrap_tfe.TFE_MonitoringIntGaugeCellValue(self._cell) class IntGauge(Metric): """A stateful class for updating a gauge-like integer metric. This class encapsulates a set of integer values (or a single value for a label-less metric). Each value is identified by a tuple of labels. The class allows the user to set each value. """ __slots__ = [] def __init__(self, name, description, *labels): """Creates a new IntGauge. Args: name: name of the new metric. description: description of the new metric. *labels: The label list of the new metric. """ super(IntGauge, self).__init__('IntGauge', _int_gauge_methods, len(labels), name, description, *labels) def get_cell(self, *labels): """Retrieves the cell.""" return IntGaugeCell(super(IntGauge, self).get_cell(*labels)) class StringGaugeCell(object): """A single string value stored in an `StringGauge`.""" __slots__ = ["_cell"] def __init__(self, cell): """Creates a new StringGaugeCell. Args: cell: A c pointer of TFE_MonitoringStringGaugeCell. """ self._cell = cell def set(self, value): """Atomically set the value. Args: value: string value. """ pywrap_tfe.TFE_MonitoringStringGaugeCellSet(self._cell, value) def value(self): """Retrieves the current value.""" with c_api_util.tf_buffer() as buffer_: pywrap_tfe.TFE_MonitoringStringGaugeCellValue(self._cell, buffer_) value = pywrap_tf_session.TF_GetBuffer(buffer_).decode('utf-8') return value class StringGauge(Metric): """A stateful class for updating a gauge-like string metric. This class encapsulates a set of string values (or a single value for a label-less metric). Each value is identified by a tuple of labels. The class allows the user to set each value. """ __slots__ = [] def __init__(self, name, description, *labels): """Creates a new StringGauge. Args: name: name of the new metric. description: description of the new metric. *labels: The label list of the new metric. """ super(StringGauge, self).__init__('StringGauge', _string_gauge_methods, len(labels), name, description, *labels) def get_cell(self, *labels): """Retrieves the cell.""" return StringGaugeCell(super(StringGauge, self).get_cell(*labels)) class BoolGaugeCell(object): """A single boolean value stored in an `BoolGauge`.""" __slots__ = ["_cell"] def __init__(self, cell): """Creates a new BoolGaugeCell. Args: cell: A c pointer of TFE_MonitoringBoolGaugeCell. """ self._cell = cell def set(self, value): """Atomically set the value. Args: value: bool value. """ pywrap_tfe.TFE_MonitoringBoolGaugeCellSet(self._cell, value) def value(self): """Retrieves the current value.""" return pywrap_tfe.TFE_MonitoringBoolGaugeCellValue(self._cell) class BoolGauge(Metric): """A stateful class for updating a gauge-like bool metric. This class encapsulates a set of boolean values (or a single value for a label-less metric). Each value is identified by a tuple of labels. The class allows the user to set each value. """ __slots__ = [] def __init__(self, name, description, *labels): """Creates a new BoolGauge. Args: name: name of the new metric. description: description of the new metric. *labels: The label list of the new metric. """ super(BoolGauge, self).__init__('BoolGauge', _bool_gauge_methods, len(labels), name, description, *labels) def get_cell(self, *labels): """Retrieves the cell.""" return BoolGaugeCell(super(BoolGauge, self).get_cell(*labels)) class SamplerCell(object): """SamplerCell stores each value of a Sampler.""" __slots__ = ["_cell"] def __init__(self, cell): """Creates a new SamplerCell. Args: cell: A c pointer of TFE_MonitoringSamplerCell. """ self._cell = cell def add(self, value): """Atomically add a sample. Args: value: float value. """ pywrap_tfe.TFE_MonitoringSamplerCellAdd(self._cell, value) def value(self): """Retrieves the current distribution of samples. Returns: A HistogramProto describing the distribution of samples. """ with c_api_util.tf_buffer() as buffer_: pywrap_tfe.TFE_MonitoringSamplerCellValue(self._cell, buffer_) proto_data = pywrap_tf_session.TF_GetBuffer(buffer_) histogram_proto = summary_pb2.HistogramProto() histogram_proto.ParseFromString(compat.as_bytes(proto_data)) return histogram_proto class Buckets(object): """Bucketing strategies for the samplers.""" __slots__ = ["buckets"] def __init__(self, buckets): """Creates a new Buckets. Args: buckets: A c pointer of TFE_MonitoringBuckets. """ self.buckets = buckets def __del__(self): pywrap_tfe.TFE_MonitoringDeleteBuckets(self.buckets) class ExponentialBuckets(Buckets): """Exponential bucketing strategy. Sets up buckets of the form: [-DBL_MAX, ..., scale * growth^i, scale * growth_factor^(i + 1), ..., DBL_MAX]. """ __slots__ = [] def __init__(self, scale, growth_factor, bucket_count): """Creates a new exponential Buckets. Args: scale: float growth_factor: float bucket_count: integer """ super(ExponentialBuckets, self).__init__( pywrap_tfe.TFE_MonitoringNewExponentialBuckets(scale, growth_factor, bucket_count)) class Sampler(Metric): """A stateful class for updating a cumulative histogram metric. This class encapsulates a set of histograms (or a single histogram for a label-less metric) configured with a list of increasing bucket boundaries. Each histogram is identified by a tuple of labels. The class allows the user to add a sample to each histogram value. """ __slots__ = [] def __init__(self, name, buckets, description, *labels): """Creates a new Sampler. Args: name: name of the new metric. buckets: bucketing strategy of the new metric. description: description of the new metric. *labels: The label list of the new metric. """ super(Sampler, self).__init__('Sampler', _sampler_methods, len(labels), name, buckets.buckets, description, *labels) def get_cell(self, *labels): """Retrieves the cell.""" return SamplerCell(super(Sampler, self).get_cell(*labels)) class MonitoredTimer(object): """A context manager to measure the walltime and increment a Counter cell.""" __slots__ = ["cell", "t"] def __init__(self, cell): """Creates a new MonitoredTimer. Args: cell: the cell associated with the time metric that will be inremented. """ self.cell = cell def __enter__(self): self.t = time.time() return self def __exit__(self, exception_type, exception_value, traceback): del exception_type, exception_value, traceback micro_seconds = (time.time() - self.t) * 1000000 self.cell.increase_by(int(micro_seconds)) def monitored_timer(cell): """A function decorator for adding MonitoredTimer support. Arguments: cell: the cell associated with the time metric that will be inremented. Returns: A decorator that measure the function runtime and increment the specified counter cell. """ def actual_decorator(func): @functools.wraps(func) def wrapper(*args, **kwargs): with MonitoredTimer(cell): return func(*args, **kwargs) return wrapper return actual_decorator