Tensorflow

Feature request

We currently have 2 monocular depth estimation models in the library, namely DPT and GLPN.

It would be great to have a pipeline for this task, with the following API:

from transformers import pipeline

pipe = pipeline("depth-estimation")
pipe("ca

What happened + What you expected to happen

1. Getting a ton of warnings from pytorch-lightning about deprecation of certain hooks.
2. Expect no warnings.
3. The TuneCallback has old hooks such as keyboard_interrupt which have been deprecated.
   The most list of the deprecated hooks

Adding a Dataset

• Name: Stanford dog dataset
• Description: The dataset is about 120 classes for a total of 20.580 images. You can find the dataset here http://vision.stanford.edu/aditya86/ImageNetDogs/
• Paper: http://vision.stanford.edu/aditya86/ImageNetDogs/
• Data: *[link to the Github repository or current dataset location](http://vision.stanford.edu/aditya86/Ima

Bug with GPU Model

Currently, while using pruning methods like TaylorFOWeight Pruner, If I use a model on GPU for getting the metrics (as calculated for getting masks), it fails on line while creating masks. The reason why it fails i

Feature Description

We want to enable the users to specify the value ranges for any argument in the blocks.
The following code example shows a typical use case.
The users can specify the number of units in a DenseBlock to be either 10 or 20.

Code Example

import au