Comments (4)
Please upgrade your adanet to version >= 0.5.0. You can then pass you custom_metrics
to the adanet.Estimator
constructor's metric_fn
argument: https://adanet.readthedocs.io/en/v0.5.0/adanet.html#estimator
from adanet.
Thanks. For others the metric_fn
should return a tuple of (value, update_op)
. An example will look like the following metric_fn
def custom_metrics(predictions, features, labels):
return {
'customMetric': (tf.constant(0.0), tf.add(tf.constant(0.0) , tf.constant(0.0) ) )
}
Also the example function my_auc
in https://www.tensorflow.org/api_docs/python/tf/contrib/estimator/add_metrics has wrong order of arguments.
Closing this issue.
from adanet.
Generally you want the value
element of the tuple to be a variable, and for the update_op
to mutate it somehow. For example look at tf.metrics.accuracy
.
from adanet.
Yes, Thanks for more specific and elaborate example tf.metric.accuracy
.
from adanet.
Related Issues (20)
- `input_fn` called multiple times in `Estimator.train` HOT 5
- relation to AutoML tables in GCP HOT 2
- Question regarding architecture HOT 3
- adanet.ensemble.Ensembler not used in Tutorials? HOT 5
- Adding different loss to tf.estimator.Head HOT 2
- Correct place to add custom metric_fn? HOT 3
- Early stopping 'best-practice' using Adanet
- Interpretation of serialized "architecture_summary" HOT 2
- simple_dnn should not work !
- [Bug] AutoEnsembleEstimator() cannot be instatiated if tf< 2.x HOT 1
- I am having errors and do not know what to do... HOT 1
- Evaluation issue using TPUEstimator HOT 2
- RuntimeError with adanet_tpu tutorial using TF2.2 and Adanet 0.9.0
- AttributeError: module 'adanet' has no attribute 'AutoEnsembleEstimator'
- Is there any code to compute FLOPs and parameter size of adanet?
- Error on running tutorial notebook in Google colab
- Using AdaNet ModelFlow with pre-trained models HOT 1
- Got `AttributeError: 'NoneType' object has no attribute 'logits'` error while applying tutorial
- Is this repository deprecated? HOT 1
- Design suggestions of _IterationBuilder._best_loss from adanet.core.iteration
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from adanet.