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ml

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.

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JonTriebenbach
JonTriebenbach commented Sep 2, 2020

Bug Report

These tests were run on s390x. s390x is big-endian architecture.

Failure log for helper_test.py

________________________________________________ TestHelperTensorFunctions.test_make_tensor ________________________________________________

self = <helper_test.TestHelperTensorFunctions testMethod=test_make_tensor>

    def test_make_tensor(self):  # type: () -> None
    
PhilipMay
PhilipMay commented Jun 12, 2020

MLflow seems to have a length limit of 5000 when setting tags (see below).

[...]
  File "/home/smay/miniconda3/envs/py38/lib/python3.8/site-packages/mlflow/utils/validation.py", line 136, in _validate_length_limit
    raise MlflowException(
mlflow.exceptions.MlflowException: Tag value '[0.8562690322984875, 0.8544098885636596, 0.8544098885636596, 0.8544098885636596, 0.85440988856365
mmlspark
brunocous
brunocous commented Sep 2, 2020

I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?

bcleenders
bcleenders commented Oct 2, 2020

When a user wants to stream data to a date-partitioned BQ table, the way to do this is:

//noinspection ScalaStyle
class DayPartitionFunction()
  extends SerializableFunction[ValueInSingleWindow[TableRow], TableDestination] {
  override def apply(input: ValueInSingleWindow[TableRow]): TableDestination = {
    val partition = DateTimeFormat.forPattern("yyyyMMdd").withZone(DateTimeZo
BentoML
shihgianlee
shihgianlee commented Aug 21, 2020

Is your feature request related to a problem? Please describe.
We have a mechanism to capture logs in production that doesn't require log files collection. However, there is no option to disable local log files generation.

Describe the solution you'd like
A configuration option for user to disable logging to files.

Describe alternatives you've considered
Accept the default beh

joelberkeley-secondmind
joelberkeley-secondmind commented Oct 10, 2020

Bug

When I use tf dtypes as default float, I encounter errors in gpflow code that tries to convert numpy array dtypes using the default float.

To reproduce

>>> with gpflow.config.as_context(gpflow.config.Config(float=tf.float64)):
...     gpflow.quadrature.gauss_hermite.gh_points_and_weights(1)
... 
Traceback (most recent call last):
  File "<stdin>", line 2, in <modul
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