[docs] Update Bolts link

README.md

@@ -342,27 +342,27 @@ class LitAutoEncoder(pl.LightningModule):
 - [MNIST on TPUs](https://colab.research.google.com/github/PytorchLightning/pytorch-lightning/blob/master/notebooks/06-mnist-tpu-training.ipynb)
 
 ###### Contrastive Learning
-- [BYOL](https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#byol)
-- [CPC v2](https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#cpc-v2)
-- [Moco v2](https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#moco-v2)
-- [SIMCLR](https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#simclr)
+- [BYOL](https://lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#byol)
+- [CPC v2](https://lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#cpc-v2)
+- [Moco v2](https://lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#moco-v2)
+- [SIMCLR](https://lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#simclr)
 
 ###### NLP
 - [BERT](https://colab.research.google.com/github/PytorchLightning/pytorch-lightning/blob/master/notebooks/04-transformers-text-classification.ipynb)
-- [GPT-2](https://pytorch-lightning-bolts.readthedocs.io/en/latest/convolutional.html#gpt-2)
+- [GPT-2](https://lightning-bolts.readthedocs.io/en/latest/convolutional.html#gpt-2)
 
 
 ###### Reinforcement Learning
-- [DQN](https://pytorch-lightning-bolts.readthedocs.io/en/latest/reinforce_learn.html#dqn-models)
-- [Dueling-DQN](https://pytorch-lightning-bolts.readthedocs.io/en/latest/reinforce_learn.html#dueling-dqn)
-- [Reinforce](https://pytorch-lightning-bolts.readthedocs.io/en/latest/reinforce_learn.html#reinforce)
+- [DQN](https://lightning-bolts.readthedocs.io/en/latest/reinforce_learn.html#dqn-models)
+- [Dueling-DQN](https://lightning-bolts.readthedocs.io/en/latest/reinforce_learn.html#dueling-dqn)
+- [Reinforce](https://lightning-bolts.readthedocs.io/en/latest/reinforce_learn.html#reinforce)
 
 ###### Vision
 - [GAN](https://colab.research.google.com/github/PytorchLightning/pytorch-lightning/blob/master/notebooks/03-basic-gan.ipynb)
 
 ###### Classic ML
-- [Logistic Regression](https://pytorch-lightning-bolts.readthedocs.io/en/latest/classic_ml.html#logistic-regression)
-- [Linear Regression](https://pytorch-lightning-bolts.readthedocs.io/en/latest/classic_ml.html#linear-regression)
+- [Logistic Regression](https://lightning-bolts.readthedocs.io/en/latest/classic_ml.html#logistic-regression)
+- [Linear Regression](https://lightning-bolts.readthedocs.io/en/latest/classic_ml.html#linear-regression)
 
 ---
 

docs/source/ecosystem/bolts.rst

@@ -1,11 +1,11 @@
 Bolts
 =====
-`PyTorch Lightning Bolts <https://pytorch-lightning-bolts.readthedocs.io/en/latest/>`_, is our official collection
+`PyTorch Lightning Bolts <https://lightning-bolts.readthedocs.io/en/latest/>`_, is our official collection
 of prebuilt models across many research domains.
 
 .. code-block:: bash
 
-    pip install pytorch-lightning-bolts
+    pip install lightning-bolts
 
 In bolts we have:
 

docs/source/extensions/callbacks.rst

@@ -71,10 +71,10 @@ Examples
 --------
 You can do pretty much anything with callbacks.
 
-- `Add a MLP to fine-tune self-supervised networks <https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_callbacks.html#sslonlineevaluator>`_.
-- `Find how to modify an image input to trick the classification result <https://pytorch-lightning-bolts.readthedocs.io/en/latest/vision_callbacks.html#confused-logit>`_.
-- `Interpolate the latent space of any variational model <https://pytorch-lightning-bolts.readthedocs.io/en/latest/variational_callbacks.html#latent-dim-interpolator>`_.
-- `Log images to Tensorboard for any model <https://pytorch-lightning-bolts.readthedocs.io/en/latest/vision_callbacks.html#tensorboard-image-generator>`_.
+- `Add a MLP to fine-tune self-supervised networks <https://lightning-bolts.readthedocs.io/en/latest/self_supervised_callbacks.html#sslonlineevaluator>`_.
+- `Find how to modify an image input to trick the classification result <https://lightning-bolts.readthedocs.io/en/latest/vision_callbacks.html#confused-logit>`_.
+- `Interpolate the latent space of any variational model <https://lightning-bolts.readthedocs.io/en/latest/variational_callbacks.html#latent-dim-interpolator>`_.
+- `Log images to Tensorboard for any model <https://lightning-bolts.readthedocs.io/en/latest/vision_callbacks.html#tensorboard-image-generator>`_.
 
 
 --------------
@@ -85,7 +85,7 @@ Lightning has a few built-in callbacks.
 
 .. note::
     For a richer collection of callbacks, check out our
-    `bolts library <https://pytorch-lightning-bolts.readthedocs.io/en/latest/callbacks.html>`_.
+    `bolts library <https://lightning-bolts.readthedocs.io/en/latest/callbacks.html>`_.
 
 .. currentmodule:: pytorch_lightning.callbacks
 

docs/source/index.rst

@@ -79,14 +79,14 @@ PyTorch Lightning Documentation
 
    ecosystem/pytorch_ecoystem
    ecosystem/community_examples
-   Autoencoder <https://pytorch-lightning-bolts.readthedocs.io/en/latest/autoencoders.html#autoencoders>
-   BYOL <https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#byol>
-   DQN <https://pytorch-lightning-bolts.readthedocs.io/en/latest/reinforce_learn.html#deep-q-network-dqn>
-   GAN <https://pytorch-lightning-bolts.readthedocs.io/en/latest/gans.html#basic-gan>
-   GPT-2 <https://pytorch-lightning-bolts.readthedocs.io/en/latest/convolutional.html#gpt-2>
-   Image-GPT <https://pytorch-lightning-bolts.readthedocs.io/en/latest/convolutional.html#image-gpt>
-   SimCLR <https://pytorch-lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#simclr>
-   VAE <https://pytorch-lightning-bolts.readthedocs.io/en/latest/autoencoders.html#basic-vae>
+   Autoencoder <https://lightning-bolts.readthedocs.io/en/latest/autoencoders.html#autoencoders>
+   BYOL <https://lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#byol>
+   DQN <https://lightning-bolts.readthedocs.io/en/latest/reinforce_learn.html#deep-q-network-dqn>
+   GAN <https://lightning-bolts.readthedocs.io/en/latest/gans.html#basic-gan>
+   GPT-2 <https://lightning-bolts.readthedocs.io/en/latest/convolutional.html#gpt-2>
+   Image-GPT <https://lightning-bolts.readthedocs.io/en/latest/convolutional.html#image-gpt>
+   SimCLR <https://lightning-bolts.readthedocs.io/en/latest/self_supervised_models.html#simclr>
+   VAE <https://lightning-bolts.readthedocs.io/en/latest/autoencoders.html#basic-vae>
 
 .. toctree::
    :maxdepth: 1

notebooks/07-cifar10-baseline.ipynb

@@ -61,7 +61,7 @@
         "id": "ziAQCrE-TYWG"
       },
       "source": [
-        "! pip install pytorch-lightning pytorch-lightning-bolts -qU"
+        "! pip install pytorch-lightning lightning-bolts -qU"
       ],
       "execution_count": null,
       "outputs": []

pl_examples/README.md

@@ -1,6 +1,6 @@
 # Examples
 Our most robust examples showing all sorts of implementations
-can be found in our sister library [PyTorch-Lightning-Bolts](https://pytorch-lightning-bolts.readthedocs.io/en/latest/convolutional.html#gpt-2).
+can be found in our sister library [PyTorch-Lightning-Bolts](https://lightning-bolts.readthedocs.io/en/latest/convolutional.html#gpt-2).
 
 ---
 
@@ -15,5 +15,5 @@ In this folder we add 3 simple examples:
 
 ## Domain examples
 This folder contains older examples. You should instead use the examples
-in [PyTorch-Lightning-Bolts](https://pytorch-lightning-bolts.readthedocs.io/en/latest/convolutional.html#gpt-2)
+in [PyTorch-Lightning-Bolts](https://lightning-bolts.readthedocs.io/en/latest/convolutional.html#gpt-2)
 for advanced use cases.

pl_examples/basic_examples/conv_sequential_example.py

@@ -199,7 +199,7 @@ def instantiate_datamodule(args):
 if __name__ == "__main__":
     cli_lightning_logo()
 
-    assert _BOLTS_AVAILABLE, "Bolts is required for this example, install it via pip install pytorch-lightning-bolts"
+    assert _BOLTS_AVAILABLE, "Bolts is required for this example, install it via pip install lightning-bolts"
     assert _FAIRSCALE_PIPE_AVAILABLE, "FairScale and PyTorch 1.6 is required for this example."
 
     parser = ArgumentParser(description="Pipe Example")