Added Random Normal Init and fixed optimizer hyperparameters

[arshagarwal]

In response to the discussions in this pull request, this pull request adds Random normal initializer with mean 0 and std-dev 1, and fixes the optimizer hyper-parameters as per DC-GAN paper.

I am sure there is a more graceful way to do this, but I found this way much easier than to fix code in the same pull request. Sorry about that!

[github-actions[bot]]

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• site/en/guide/advanced_autodiff.ipynb
• site/en/guide/autodiff.ipynb
• site/en/guide/basic_training_loops.ipynb
• site/en/guide/checkpoint.ipynb
• site/en/guide/data.ipynb
• site/en/guide/data_performance.ipynb
• site/en/guide/distributed_training.ipynb
• site/en/guide/eager.ipynb
• site/en/guide/estimator.ipynb
• site/en/guide/function.ipynb
• site/en/guide/gpu.ipynb
• site/en/guide/graph_optimization.ipynb
• site/en/guide/intro_to_graphs.ipynb
• site/en/guide/intro_to_modules.ipynb
• site/en/guide/migrate.ipynb
• site/en/guide/mixed_precision.ipynb
• site/en/guide/ragged_tensor.ipynb
• site/en/guide/random_numbers.ipynb
• site/en/guide/saved_model.ipynb
• site/en/guide/tensor.ipynb
• site/en/guide/tf_numpy.ipynb
• site/en/guide/tpu.ipynb
• site/en/guide/upgrade.ipynb
• site/en/guide/variable.ipynb
• site/en/r1/guide/autograph.ipynb
• site/en/r1/guide/distribute_strategy.ipynb
• site/en/r1/guide/eager.ipynb
• site/en/r1/guide/keras.ipynb
• site/en/r1/guide/ragged_tensors.ipynb
• site/en/r1/tutorials/_index.ipynb
• site/en/r1/tutorials/distribute/keras.ipynb
• site/en/r1/tutorials/distribute/tpu_custom_training.ipynb
• site/en/r1/tutorials/distribute/training_loops.ipynb
• site/en/r1/tutorials/eager/automatic_differentiation.ipynb
• site/en/r1/tutorials/eager/custom_layers.ipynb
• site/en/r1/tutorials/eager/custom_training.ipynb
• site/en/r1/tutorials/eager/custom_training_walkthrough.ipynb
• site/en/r1/tutorials/eager/eager_basics.ipynb
• site/en/r1/tutorials/estimators/boosted_trees.ipynb
• site/en/r1/tutorials/estimators/boosted_trees_model_understanding.ipynb
• site/en/r1/tutorials/estimators/cnn.ipynb
• site/en/r1/tutorials/estimators/linear.ipynb
• site/en/r1/tutorials/images/hub_with_keras.ipynb
• site/en/r1/tutorials/images/transfer_learning.ipynb
• site/en/r1/tutorials/keras/basic_classification.ipynb
• site/en/r1/tutorials/keras/basic_regression.ipynb
• site/en/r1/tutorials/keras/basic_text_classification.ipynb
• site/en/r1/tutorials/keras/overfit_and_underfit.ipynb
• site/en/r1/tutorials/keras/save_and_restore_models.ipynb
• site/en/r1/tutorials/load_data/images.ipynb
• site/en/r1/tutorials/load_data/tf_records.ipynb
• site/en/r1/tutorials/non-ml/mandelbrot.ipynb
• site/en/r1/tutorials/non-ml/pdes.ipynb
• site/en/r1/tutorials/representation/unicode.ipynb
• site/en/r1/tutorials/sequences/text_generation.ipynb
• site/en/tutorials/customization/basics.ipynb
• site/en/tutorials/customization/custom_layers.ipynb
• site/en/tutorials/customization/custom_training.ipynb
• site/en/tutorials/customization/custom_training_walkthrough.ipynb
• site/en/tutorials/distribute/custom_training.ipynb
• site/en/tutorials/distribute/input.ipynb
• site/en/tutorials/distribute/keras.ipynb
• site/en/tutorials/distribute/multi_worker_with_estimator.ipynb
• site/en/tutorials/distribute/multi_worker_with_keras.ipynb
• site/en/tutorials/distribute/save_and_load.ipynb
• site/en/tutorials/estimator/boosted_trees.ipynb
• site/en/tutorials/estimator/boosted_trees_model_understanding.ipynb
• site/en/tutorials/estimator/keras_model_to_estimator.ipynb
• site/en/tutorials/estimator/linear.ipynb
• site/en/tutorials/estimator/premade.ipynb
• site/en/tutorials/generative/adversarial_fgsm.ipynb
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• site/en/tutorials/generative/cyclegan.ipynb
• site/en/tutorials/generative/dcgan.ipynb
• site/en/tutorials/generative/deepdream.ipynb
• site/en/tutorials/generative/pix2pix.ipynb
• site/en/tutorials/generative/style_transfer.ipynb
• site/en/tutorials/images/classification.ipynb
• site/en/tutorials/images/cnn.ipynb
• site/en/tutorials/images/data_augmentation.ipynb
• site/en/tutorials/images/segmentation.ipynb
• site/en/tutorials/images/transfer_learning.ipynb
• site/en/tutorials/images/transfer_learning_with_hub.ipynb
• site/en/tutorials/interpretability/integrated_gradients.ipynb
• site/en/tutorials/keras/classification.ipynb
• site/en/tutorials/keras/keras_tuner.ipynb
• site/en/tutorials/keras/overfit_and_underfit.ipynb
• site/en/tutorials/keras/regression.ipynb
• site/en/tutorials/keras/save_and_load.ipynb
• site/en/tutorials/keras/text_classification.ipynb
• site/en/tutorials/keras/text_classification_with_hub.ipynb
• site/en/tutorials/load_data/csv.ipynb
• site/en/tutorials/load_data/images.ipynb
• site/en/tutorials/load_data/numpy.ipynb
• site/en/tutorials/load_data/pandas_dataframe.ipynb
• site/en/tutorials/load_data/text.ipynb
• site/en/tutorials/load_data/tfrecord.ipynb
• site/en/tutorials/load_data/unicode.ipynb
• site/en/tutorials/quickstart/advanced.ipynb
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• site/en/tutorials/reinforcement_learning/actor_critic.ipynb
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• site/en/tutorials/structured_data/imbalanced_data.ipynb
• site/en/tutorials/structured_data/preprocessing_layers.ipynb
• site/en/tutorials/structured_data/time_series.ipynb
• site/en/tutorials/text/image_captioning.ipynb
• site/en/tutorials/text/nmt_with_attention.ipynb
• site/en/tutorials/text/text_classification_rnn.ipynb
• site/en/tutorials/text/text_generation.ipynb
• site/en/tutorials/text/transformer.ipynb
• site/en/tutorials/text/word_embeddings.ipynb
• tools/templates/notebook.ipynb
• tools/templates/subsite/g3doc/tutorials/notebook.ipynb

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[MarkDaoust]

Friendly ping @yashk2810

[lamberta]

Merge conflict, please rebase