Update .png to .PNG for some thumbnails

Author: Jessica Lin

recipes_source/recipes_index.rst

@@ -33,65 +33,65 @@ Recipes are bite-sized bite-sized, actionable examples of how to use specific Py
 .. customcarditem::
    :header: Loading data in PyTorch
    :card_description: Learn how to use PyTorch packages to prepare and load common datasets for your model.
-   :image: ../_static/img/thumbnails/cropped/loading-data.png
+   :image: ../_static/img/thumbnails/cropped/loading-data.PNG
    :link: ../recipes/recipes/loading_data_recipe.html
    :tags: Basics
 
 
 .. customcarditem::
    :header: Defining a Neural Network
    :card_description: Learn how to use PyTorch's torch.nn package to create and define a neural network the MNIST dataset.
-   :image: ../_static/img/thumbnails/cropped/defining-a-network.png
+   :image: ../_static/img/thumbnails/cropped/defining-a-network.PNG
    :link: ../recipes/recipes/defining_a_neural_network.html
    :tags: Basics
 
 .. customcarditem::
    :header: What is a state_dict in PyTorch
    :card_description: Learn how state_dict objects, Python dictionaries, are used in saving or loading models from PyTorch.
-   :image: ../_static/img/thumbnails/cropped/what-is-a-state-dict.png
+   :image: ../_static/img/thumbnails/cropped/what-is-a-state-dict.PNG
    :link: ../recipes/recipes/what_is_state_dict.html
    :tags: Basics
 
 .. customcarditem::
    :header: Saving and loading models for inference in PyTorch
    :card_description: Learn about the two approaches for saving and loading models for inference in PyTorch - via the state_dict and via the entire model.
-   :image: ../_static/img/thumbnails/cropped/saving-and-loading-models-for-inference.png
+   :image: ../_static/img/thumbnails/cropped/saving-and-loading-models-for-inference.PNG
    :link: ../recipes/recipes/saving_and_loading_models_for_inference.html
    :tags: Basics
 
 
 .. customcarditem::
    :header: Saving and loading a general checkpoint in PyTorch
    :card_description: Saving and loading a general checkpoint model for inference or resuming training can be helpful for picking up where you last left off. In this recipe, explore how to save and load multiple checkpoints.
-   :image: ../_static/img/thumbnails/cropped/saving-and-loading-general-checkpoint.png
+   :image: ../_static/img/thumbnails/cropped/saving-and-loading-general-checkpoint.PNG
    :link: ../recipes/recipes/saving_and_loading_a_general_checkpoint.html
    :tags: Basics
 
 .. customcarditem::
    :header: Saving and loading multiple models in one file using PyTorch
    :card_description: In this recipe, learn how saving and loading multiple models can be helpful for reusing models that you have previously trained.
-   :image: ../_static/img/thumbnails/cropped/saving-multiple-models.png
+   :image: ../_static/img/thumbnails/cropped/saving-multiple-models.PNG
    :link: ../recipes/recipes/saving_multiple_models_in_one_file.html
    :tags: Basics
 
 .. customcarditem::
    :header: Warmstarting model using parameters from a different model in PyTorch
    :card_description: Learn how warmstarting the training process by partially loading a model or loading a partial model can help your model converge much faster than training from scratch.
-   :image: ../_static/img/thumbnails/cropped/warmstarting-models.png
+   :image: ../_static/img/thumbnails/cropped/warmstarting-models.PNG
    :link: ../recipes/recipes/warmstarting_model_using_parameters_from_a_different_model.html
    :tags: Basics
 
 .. customcarditem::
    :header: Saving and loading models across devices in PyTorch
    :card_description: Learn how saving and loading models across devices (CPUs and GPUs) is relatively straightforward using PyTorch.
-   :image: ../_static/img/thumbnails/cropped/saving-and-loading-models-across-devices.png
+   :image: ../_static/img/thumbnails/cropped/saving-and-loading-models-across-devices.PNG
    :link: ../recipes/recipes/save_load_across_devices.html
    :tags: Basics
 
 .. customcarditem::
    :header: Zeroing out gradients in PyTorch
    :card_description: Learn when you should zero out graidents and how doing so can help increase the accuracy of your model.
-   :image: ../_static/img/thumbnails/cropped/zeroing-out-gradients.png
+   :image: ../_static/img/thumbnails/cropped/zeroing-out-gradients.PNG
    :link: ../recipes/recipes/zeroing_out_gradients.html
    :tags: Basics