V1HpChoice
polyaxon.polyflow.matrix.params.V1HpChoice(kind='choice', value=None)
Choice
picks a value from a of list values.
params:
paramTest:
kind: choice
value: [1, 2, 3, 4, 5]
from polyaxon.polyflow import V1HpChoice
param_test = V1HpChoice(value=[1, 2, 3, 4, 5])
V1HpPChoice
polyaxon.polyflow.matrix.params.V1HpPChoice(kind='pchoice', value=None)
PChoice
picks a value with a probability from a list of
[(value, probability), (value, probability), …].
params:
paramTest:
kind: pchoice
value: [(1, 0.1), (2, 0.1), (3, 0.8)]
from polyaxon.polyflow import V1HpPChoice
param_test = V1HpPChoice(value=[("A", 0.1), ("B", 0.1), ("C", 0.8)])
V1HpDateRange
polyaxon.polyflow.matrix.params.V1HpDateRange(kind='daterange', value=None)
DateRange
picks a value from a generated list of values using [start, stop, step]
,
you can pass values in these forms:
["2019-06-24", "2019-06-25", 3600 * 24]
{start: "2019-06-24 00:00", stop: "2019-06-28 00:00", step: 1}
Step (frequency): represents a timedelta in days.
params:
paramTest:
kind: daterange
value: ["2019-06-22", "2019-07-25", 1]
from polyaxon.polyflow import V1HpDateRange
param_test = V1HpDateRange(value=["2019-06-22", "2019-06-25", 2])
V1HpDateTimeRange
polyaxon.polyflow.matrix.params.V1HpDateTimeRange(kind='datetimerange', value=None)
DateTimeRange
picks a value from a generated list of values using [start, stop, step]
,
you can pass values in these forms:
["2019-06-24T21:20:07+02:00", "2019-06-25T21:20:07+02:00", 3600]
{start: "2019-06-24 00:00", stop: "2019-06-28 00:00", step: 3600 * 4}
Step (frequency): represents a timedelta in seconds.
params:
paramTest:
kind: datetimerange
value: ["2019-06-22 21:00", "2019-06-25 21:00", 3600]
from polyaxon.polyflow import V1HpDateTimeRange
param_test = V1HpDateTimeRange(value=["2019-06-22 21:00", "2019-06-25 21:00", 3600])
V1HpRange
polyaxon.polyflow.matrix.params.V1HpRange(kind='range', value=None)
Range
picks a value from a generated list of values using [start, stop, step]
,
you can pass values in these forms:
- [1, 10, 2]
- {start: 1, stop: 10, step: 2}
- ‘1:10:2’
params:
paramTest:
kind: range
value: [1, 10, 2]
from polyaxon.polyflow import V1HpRange
param_test = V1HpRange(value=[1, 10, 2])
V1HpLinSpace
polyaxon.polyflow.matrix.params.V1HpLinSpace(kind='linspace', value=None)
LinSpace
picks a value from a generated list of steps from start to stop spaced evenly
on a linear scale [start, stop, step]
, you can pass values in these forms:
- [1, 10, 20]
- {start: 1, stop: 10, num: 20}
- ‘1:10:20’
params:
paramTest:
kind: linspace
value: [1, 10, 20]
from polyaxon.polyflow import V1HpLinSpace
param_test = V1HpLinSpace(value=[1, 10, 20])
V1HpLogSpace
polyaxon.polyflow.matrix.params.V1HpLogSpace(kind='logspace', value=None)
LogSpace
picks a value from a generated list of steps from start to stop spaced evenly
on a log scale [start, stop, step]
, you can pass values in these forms:
- [1, 10, 20]
- {start: 1, stop: 10, num: 20}
- ‘1:10:20’
params:
paramTest:
kind: logspace
value: [1, 10, 20]
from polyaxon.polyflow import V1HpLogSpace
param_test = V1HpLinSpace(value=[1, 10, 20])
V1HpGeomSpace
polyaxon.polyflow.matrix.params.V1HpGeomSpace(kind='geomspace', value=None)
GeomSpace
picks a value from a generated list of steps from start to stop spaced evenly
on a geometric progression [start, stop, step]
, you can pass values in these forms:
- [1, 10, 20]
- {start: 1, stop: 10, num: 20}
- ‘1:10:20’
params:
paramTest:
kind: geomspace
value: [1, 10, 20]
from polyaxon.polyflow import V1HpGeomSpace
param_test = V1HpGeomSpace(value=[1, 10, 20])
V1HpUniform
polyaxon.polyflow.matrix.params.V1HpUniform(kind='uniform', value=None)
Uniform
draws samples from a uniform distribution over the half-open
interval [low, high)
, you can pass values in these forms:
- 0:1
- [0, 1]
- {‘low’: 0, ‘high’: 1}
params:
paramTest:
kind: uniform
value: [0, 1]
from polyaxon.polyflow import V1HpUniform
param_test = V1HpUniform(value=[0, 1])
V1HpQUniform
polyaxon.polyflow.matrix.params.V1HpQUniform(kind='quniform', value=None)
QUniform
samples from a quantized uniform distribution over [low, high]
(round(uniform(low, high) / q) * q
),
you can pass values in these forms:
- 0:1:0.1
- [0, 1, 0.1]
- {‘low’: 0, ‘high’: 1, ‘q’: 0.1}
params:
paramTest:
kind: quniform
value: [0, 1, 0.1]
from polyaxon.polyflow import V1HpQUniform
param_test = V1HpQUniform(value=[0, 1, 0.1])
V1HpLogUniform
polyaxon.polyflow.matrix.params.V1HpLogUniform(kind='loguniform', value=None)
LogUniform
samples from a log uniform distribution over[low, high]
,
you can pass values in these forms:
- 0:1
- [0, 1]
- {‘low’: 0, ‘high’: 1}
params:
paramTest:
kind: loguniform
value: [0, 1]
from polyaxon.polyflow import V1HpLogUniform
param_test = V1HpLogUniform(value=[0, 1])
V1HpQLogUniform
polyaxon.polyflow.matrix.params.V1HpQLogUniform(kind='qloguniform', value=None)
LogUniform
samples from a log uniform distribution over[low, high]
,
you can pass values in these forms:
- 0:1:0.1
- [0, 1, 0.1]
- {‘low’: 0, ‘high’: 1, ‘q’: 0.1}
params:
paramTest:
kind: qloguniform
value: [0, 1, 0.1]
from polyaxon.polyflow import V1HpQLogUniform
param_test = V1HpQLogUniform(value=[0, 1, 0.1])
V1HpNormal
polyaxon.polyflow.matrix.params.V1HpNormal(kind='normal', value=None)
Normal
draws random samples from a normal (Gaussian) distribution defined by
[loc, scale]
, you can pass values in these forms:
- 0:1
- [0, 1]
- {‘loc’: 0, ‘scale’: 1}
params:
paramTest:
kind: normal
value: [0, 1]
from polyaxon.polyflow import V1HpNormal
param_test = V1HpNormal(value=[0, 1])
V1HpQNormal
polyaxon.polyflow.matrix.params.V1HpQNormal(kind='qnormal', value=None)
QNormal
draws random samples from a quantized normal (Gaussian) distribution defined by
[loc, scale]
, you can pass values in these forms:
- 0:1:0.1
- [0, 1, 0.1]
- {‘loc’: 0, ‘scale’: 1, ‘q’: 0.1}
params:
paramTest:
kind: qnormal
value: [0, 1, 0.1]
from polyaxon.polyflow import V1HpQNormal
param_test = V1HpNormal(value=[0, 1, 0.1])
V1HpLogNormal
polyaxon.polyflow.matrix.params.V1HpLogNormal(kind='lognormal', value=None)
LogNormal
draws random samples from a log normal (Gaussian) distribution defined by
[loc, scale]
, you can pass values in these forms:
- 0:1
- [0, 1]
- {‘loc’: 0, ‘scale’: 1}
params:
paramTest:
kind: lognormal
value: [0, 1]
from polyaxon.polyflow import V1HpLogNormal
param_test = V1HpLogNormal(value=[0, 1])
V1HpQLogNormal
polyaxon.polyflow.matrix.params.V1HpQLogNormal(kind='qlognormal', value=None)
QLogNormal
draws random samples from a log normal (Gaussian) distribution defined by
[loc, scale]
, you can pass values in these forms:
- 0:1:0.1
- [0, 1, 0.1]
- {‘loc’: 0, ‘scale’: 1, ‘q’: 0.1}
params:
paramTest:
kind: qlognormal
value: [0, 1, 0.1]
from polyaxon.polyflow import V1HpQLogNormal
param_test = V1HpQLogNormal(value=[0, 1])