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Metric
(
*
,
name
:
typing
.
Optional
[
str
]
=
None
,
customFunction
:
typing
.
Optional
[
typing
.
Callable
[[
...
],
typing
.
Any
]]
=
None
,
promptTemplate
:
typing
.
Optional
[
str
]
=
None
,
judgeModel
:
typing
.
Optional
[
str
]
=
None
,
judgeModelGenerationConfig
:
typing
.
Optional
[
google
.
genai
.
types
.
GenerationConfig
]
=
None
,
judgeModelSamplingCount
:
typing
.
Optional
[
int
]
=
None
,
judgeModelSystemInstruction
:
typing
.
Optional
[
str
]
=
None
,
returnRawOutput
:
typing
.
Optional
[
bool
]
=
None
,
parseAndReduceFn
:
typing
.
Optional
[
typing
.
Callable
[[
...
],
typing
.
Any
]]
=
None
,
aggregateSummaryFn
:
typing
.
Optional
[
typing
.
Callable
[[
...
],
typing
.
Any
]]
=
None
,
rubricGroupName
:
typing
.
Optional
[
str
]
=
None
,
metricSpecParameters
:
typing
.
Optional
[
dict
[
str
,
typing
.
Any
]]
=
None
,
**
extra_data
:
typing
.
Any
)
The metric used for evaluation.
Methods
Metric
Metric
(
*
,
name
:
typing
.
Optional
[
str
]
=
None
,
customFunction
:
typing
.
Optional
[
typing
.
Callable
[[
...
],
typing
.
Any
]]
=
None
,
promptTemplate
:
typing
.
Optional
[
str
]
=
None
,
judgeModel
:
typing
.
Optional
[
str
]
=
None
,
judgeModelGenerationConfig
:
typing
.
Optional
[
google
.
genai
.
types
.
GenerationConfig
]
=
None
,
judgeModelSamplingCount
:
typing
.
Optional
[
int
]
=
None
,
judgeModelSystemInstruction
:
typing
.
Optional
[
str
]
=
None
,
returnRawOutput
:
typing
.
Optional
[
bool
]
=
None
,
parseAndReduceFn
:
typing
.
Optional
[
typing
.
Callable
[[
...
],
typing
.
Any
]]
=
None
,
aggregateSummaryFn
:
typing
.
Optional
[
typing
.
Callable
[[
...
],
typing
.
Any
]]
=
None
,
rubricGroupName
:
typing
.
Optional
[
str
]
=
None
,
metricSpecParameters
:
typing
.
Optional
[
dict
[
str
,
typing
.
Any
]]
=
None
,
**
extra_data
:
typing
.
Any
)
Create a new model by parsing and validating input data from keyword arguments.
Raises [ ValidationError
][pydantic_core.ValidationError] if the input data cannot be
validated to form a valid model.
self
is explicitly positional-only to allow self
as a field name.
model_post_init
model_post_init
(
context
:
Any
,
/
)
-
> None
This function is meant to behave like a BaseModel method to initialise private attributes.
It takes context as an argument since that's what pydantic-core passes when calling it.
to_yaml_file
to_yaml_file
(
file_path
:
str
,
version
:
typing
.
Optional
[
str
]
=
None
)
-
> None
Dumps the metric object to a YAML file.
Exceptions
Type
Description
ImportError
If the pyyaml library is not installed.
validate_name
validate_name
(
model
:
vertexai
.
_genai
.
types
.
common
.
Metric
,
)
-
> vertexai
.
_genai
.
types
.
common
.
Metric
API documentation for validate_name
method.
