From b65d07ed6b13e83757cfb01818580080960ef75d Mon Sep 17 00:00:00 2001 From: vishal Date: Fri, 5 Jul 2019 20:59:48 +0000 Subject: [PATCH] Fix end to end docs links --- docs/pipelines/aggregators-custom.md | 2 +- docs/pipelines/aggregators.md | 2 +- docs/pipelines/estimators-custom.md | 4 ++-- docs/pipelines/estimators.md | 2 +- docs/pipelines/transformers-custom.md | 2 +- docs/pipelines/transformers.md | 2 +- 6 files changed, 7 insertions(+), 7 deletions(-) diff --git a/docs/pipelines/aggregators-custom.md b/docs/pipelines/aggregators-custom.md index 3ed733e68c..ba5e029258 100644 --- a/docs/pipelines/aggregators-custom.md +++ b/docs/pipelines/aggregators-custom.md @@ -50,4 +50,4 @@ requirements-parser==0.2.0 packaging==19.0.0 ``` -You can install additional PyPI packages and import your own Python packages. See [Python Packages](../advanced/python-packages.md) for more details. +You can install additional PyPI packages and import your own Python packages. See [Python Packages](python-packages.md) for more details. diff --git a/docs/pipelines/aggregators.md b/docs/pipelines/aggregators.md index 62c16d7bfa..7155177246 100644 --- a/docs/pipelines/aggregators.md +++ b/docs/pipelines/aggregators.md @@ -2,7 +2,7 @@ An aggregator converts a set of columns and arbitrary values into a single value. Each aggregator has an input type and an output type. Aggregators run before transformers. -Custom aggregators can be implemented in Python or PySpark. See the [implementation docs](../implementations/aggregators.md) for a detailed guide. +Custom aggregators can be implemented in Python or PySpark. See the [implementation docs](aggregators.md) for a detailed guide. ## Config diff --git a/docs/pipelines/estimators-custom.md b/docs/pipelines/estimators-custom.md index a29f5ccf30..f55f7f958a 100644 --- a/docs/pipelines/estimators-custom.md +++ b/docs/pipelines/estimators-custom.md @@ -50,7 +50,7 @@ def create_estimator(run_config, model_config): ## Pre-installed Packages -You can import PyPI packages or your own Python packages to help create more complex models. See [Python Packages](../advanced/python-packages.md) for more details. +You can import PyPI packages or your own Python packages to help create more complex models. See [Python Packages](python-packages.md) for more details. The following packages have been pre-installed and can be used in your implementations: @@ -63,7 +63,7 @@ requirements-parser==0.2.0 packaging==19.0.0 ``` -You can install additional PyPI packages and import your own Python packages. See [Python Packages](../advanced/python-packages.md) for more details. +You can install additional PyPI packages and import your own Python packages. See [Python Packages](python-packages.md) for more details. # Tensorflow Transformations diff --git a/docs/pipelines/estimators.md b/docs/pipelines/estimators.md index c9874d1103..ff48e0ef83 100644 --- a/docs/pipelines/estimators.md +++ b/docs/pipelines/estimators.md @@ -2,7 +2,7 @@ An estimator defines how to train a model. -Custom estimators can be implemented in Python or PySpark. See the [implementation docs](../implementations/estimators.md) for a detailed guide. +Custom estimators can be implemented in Python or PySpark. See the [implementation docs](estimators.md) for a detailed guide. ## Config diff --git a/docs/pipelines/transformers-custom.md b/docs/pipelines/transformers-custom.md index a84b7dd626..72f2e62c88 100644 --- a/docs/pipelines/transformers-custom.md +++ b/docs/pipelines/transformers-custom.md @@ -95,4 +95,4 @@ requirements-parser==0.2.0 packaging==19.0.0 ``` -You can install additional PyPI packages and import your own Python packages. See [Python Packages](../advanced/python-packages.md) for more details. +You can install additional PyPI packages and import your own Python packages. See [Python Packages](python-packages.md) for more details. diff --git a/docs/pipelines/transformers.md b/docs/pipelines/transformers.md index 7f3687e071..34f90baafe 100644 --- a/docs/pipelines/transformers.md +++ b/docs/pipelines/transformers.md @@ -2,7 +2,7 @@ A transformer converts a set of columns and arbitrary values into a single transformed column. Each transformer has an input type and an output column type. -Custom transformers can be implemented in Python or PySpark. See the [implementation docs](../implementations/transformers.md) for a detailed guide. +Custom transformers can be implemented in Python or PySpark. See the [implementation docs](transformers.md) for a detailed guide. ## Config