From 82f31a16dc3ef9e4e620ec85d438334a65ce0b2e Mon Sep 17 00:00:00 2001
From: Pratik Gandhi <travpreneur@gmail.com>
Date: Mon, 5 Oct 2026 11:32:02 -0700
Subject: [PATCH] Fix relative links in the legacy BERT, Transformer and NLP
 docs

---
 official/README-TPU.md                | 2 +-
 official/legacy/bert/README.md        | 6 +++---
 official/legacy/transformer/README.md | 2 +-
 official/nlp/docs/train.md            | 2 +-
 4 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/official/README-TPU.md b/official/README-TPU.md
index d1c0d4ee2b5..0a39cb28e25 100644
--- a/official/README-TPU.md
+++ b/official/README-TPU.md
@@ -6,7 +6,7 @@
     BERT, which stands for Bidirectional Encoder Representations from
     Transformers.
     [BERT FineTuning with Cloud TPU](https://cloud.google.com/ai-platform/training/docs/algorithms/bert-start) provides step by step instructions on Cloud TPU training. You can look [Bert MNLI Tensorboard.dev metrics](https://tensorboard.dev/experiment/LijZ1IrERxKALQfr76gndA) for MNLI fine tuning task.
-*   [transformer](nlp/transformer): A transformer model to translate the WMT
+*   [transformer](legacy/transformer): A transformer model to translate the WMT
     English to German dataset.
         [Training transformer on Cloud TPU](https://cloud.google.com/tpu/docs/tutorials/transformer-2.x) for step by step instructions on Cloud TPU training.
 
diff --git a/official/legacy/bert/README.md b/official/legacy/bert/README.md
index 82bd5e9d9c5..461bac0c6a4 100644
--- a/official/legacy/bert/README.md
+++ b/official/legacy/bert/README.md
@@ -37,7 +37,7 @@ in order to keep consistent with BERT paper.
 Pretrained checkpoints can be found in the following links:
 
 **Note: We have switched BERT implementation
-to use Keras functional-style networks in [nlp/modeling](../modeling).
+to use Keras functional-style networks in [nlp/modeling](../../nlp/modeling).
 The new checkpoints are:**
 
 *   **[`BERT-Large, Uncased (Whole Word Masking)`](https://storage.googleapis.com/cloud-tpu-checkpoints/bert/keras_bert/wwm_uncased_L-24_H-1024_A-16.tar.gz)**:
@@ -126,7 +126,7 @@ pip install tf-nightly
 ### Pre-training
 
 There is no change to generate pre-training data. Please use the script
-[`../data/create_pretraining_data.py`](../data/create_pretraining_data.py)
+[`../../nlp/data/create_pretraining_data.py`](../../nlp/data/create_pretraining_data.py)
 which is essentially branched from the [BERT research repo](https://github.com/google-research/bert)
 to get processed pre-training data and it adapts to TF2 symbols and python3
 compatibility.
@@ -152,7 +152,7 @@ python models/official/nlp/data/create_pretraining_data.py \
 ### Fine-tuning
 
 To prepare the fine-tuning data for final model training, use the
-[`../data/create_finetuning_data.py`](../data/create_finetuning_data.py) script.
+[`../../nlp/data/create_finetuning_data.py`](../../nlp/data/create_finetuning_data.py) script.
 Resulting datasets in `tf_record` format and training meta data should be later
 passed to training or evaluation scripts. The task-specific arguments are
 described in the following sections:
diff --git a/official/legacy/transformer/README.md b/official/legacy/transformer/README.md
index 1edf4f85963..261b5fee697 100644
--- a/official/legacy/transformer/README.md
+++ b/official/legacy/transformer/README.md
@@ -207,7 +207,7 @@ A brief look at each component in the code:
 * [ffn_layer.py](ffn_layer.py): Defines the feedforward network that is used in the encoder/decoder stacks. The network is composed of 2 fully connected layers.
 
 Other files:
-* [beam_search.py](beam_search.py) contains the beam search implementation, which is used during model inference to find high scoring translations.
+* [beam_search.py](../../nlp/modeling/ops/beam_search.py) contains the beam search implementation, which is used during model inference to find high scoring translations.
 
 ### Model Trainer
 [transformer_main.py](transformer_main.py) creates an `TransformerTask` to train and evaluate the model using tf.keras.
diff --git a/official/nlp/docs/train.md b/official/nlp/docs/train.md
index d53fa30dca5..77b7156cd6e 100644
--- a/official/nlp/docs/train.md
+++ b/official/nlp/docs/train.md
@@ -189,7 +189,7 @@ python3 data/create_finetuning_data.py \
 ```
 
 Resulting training and evaluation datasets in `tf_record` format will be later
-passed to [train.py](train.py).
+passed to [train.py](../train.py).
 
 Then you can execute the following commands to start the training and evaluation
 job.