Current implementation of Go binding can not specify options.

GPUOptions struct is in internal package. And go generate doesn't work for protobuf directory. So we can't specify GPUOptions for NewSession.

New Operator

Describe the operator

Why is this operator necessary? What does it accomplish?

This is a frequently used operator in tensorflow/keras

Can this operator be constructed using existing onnx operators?

If so, why not add it as a function?

I don't know.

Is this operator used by any model currently? Which one?

Are you willing to contribute it?

Motivation

We often construct an MlflowException instance with error_code=INVALID_PARAMETER_VALUE:

import mlflow.exceptions from MlflowException
from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE

raise MlflowException(
    "error message",
    error_code=INVALID_PARAMETER_VALUE,
)

If we had a class method invalid_parameter_value:

/kind feature

Why you need this feature:

Sub-issue of kubeflow/kubeflow#6353

To have support for K8s 1.22 we need to ensure all our crud web apps, Jupyter, TensorBoards, Volumes, are using the v1 version of SubjectAccessReviews. https://kubernetes.io/docs/reference/using-api/deprec

Typo under the description: Returns a containing. Returns a what?

Document Details

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• ID: d2dc315d-96d7-e54f-6e90-fec6ed09481c
• Version Independent ID: ab5d0a68-35d6-ef5f-786e-d89e7fee8034
• Content: [DataFrameColumn.Info Method (Microsoft.Data.Analysis)](https://docs.microsoft.com/e

Introduction 📝 📈 🔧 🏗️

This tutorial should go over training a model using MindsDB that predicts Machine Failure. Example dataset can be found here.

Tutorial summary 🧾

The tutorial should follow the below steps 🔢 :

• Connect

Is your feature request related to a problem? Please describe.
With the March release of time series module, we have the ability to plot multiple forecasts in a single plot. This works ok if we have different models (such as from the output of compare_models). But sometimes, we want to compare different versions of the same model in which case, we get the same legend

from py

I am using metaflow locally but with the AWS service (e.g. the actual compute is happening locally rather than in AWS batch but the metadata is using AWS). When I access the run data through run.data I get new local directories with names like metaflow.s3.w3efey1k, which I presume is because metaflow pulls from S3 into that directory, and then un-pickles the result from there. Is there a way t

🚨🚨 Feature Request

• A new implementation (Improvement, Extension)

Is your feature request related to a problem?

Currently, if a user tries to access an index that is larger than the dataset length or tensor length, an internal error is thrown which is not easy to understand.

Description of the possible solution

We can catch the error and throw a more descriptive e

In Ue format string it represent float with comma separator, it crash css style

To fix it you can Round/replace/incluse culture info

samples/csharp/end-to-end-apps/ScalableSentimentAnalysisBlazorWebApp/BlazorSentiment.Client/Shared/HappinessScale.razor

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?

你好，请问怎么装载 ONNX 模型，目前只看到 Oneflow->ONNX 工具，没有找到 ONNX->Oneflow 工具。

Is your feature request related to a problem? Please describe.
Currently in feature_store.yaml, we can only specify a region for DynamoDB provider. As a result, it requires an actual DynamoDB to be available when we want to do local development/testing or integration testing in a sandbox environment.

Describe the solution you'd like
A way to solve this is to let user pass an endpoint