Fix markdown issues (mlflow#1369)

docs/source/R-api.rst

@@ -381,11 +381,11 @@ Extracts the ID of the run or experiment.
 Arguments
 ---------
 
-+------------+----------------------------------------------------+
-| Argument   | Description                                        |
-+============+====================================================+
-| ``object`` | An ``mlflow_run`` or ``mlflow_experiment`` object. |
-+------------+----------------------------------------------------+
+========== ==================================================
+Argument   Description
+========== ==================================================
+``object`` An ``mlflow_run`` or ``mlflow_experiment`` object.
+========== ==================================================
 
 ``mlflow_list_artifacts``
 =========================
@@ -893,17 +893,13 @@ to be used by package authors to extend the supported MLflow models.
 Arguments
 ---------
 
-+-----------------------------------+-----------------------------------+
-| Argument                          | Description                       |
-+===================================+===================================+
-| ``model``                         | The loaded MLflow model flavor.   |
-+-----------------------------------+-----------------------------------+
-| ``data``                          | A data frame to perform scoring.  |
-+-----------------------------------+-----------------------------------+
-| ``...``                           | Optional additional arguments     |
-|                                   | passed to underlying predict      |
-|                                   | methods.                          |
-+-----------------------------------+-----------------------------------+
+========= ===================================================================
+Argument  Description
+========= ===================================================================
+``model`` The loaded MLflow model flavor.
+``data``  A data frame to perform scoring.
+``...``   Optional additional arguments passed to underlying predict methods.
+========= ===================================================================
 
 ``mlflow_rename_experiment``
 ============================
@@ -1211,20 +1207,14 @@ model types.
 Arguments
 ---------
 
-+-----------------------------------+-----------------------------------+
-| Argument                          | Description                       |
-+===================================+===================================+
-| ``model``                         | The model that will perform a     |
-|                                   | prediction.                       |
-+-----------------------------------+-----------------------------------+
-| ``path``                          | Destination path where this       |
-|                                   | MLflow compatible model will be   |
-|                                   | saved.                            |
-+-----------------------------------+-----------------------------------+
-| ``...``                           | Optional additional arguments.    |
-+-----------------------------------+-----------------------------------+
-| ``conda_env``                     | Path to Conda dependencies file.  |
-+-----------------------------------+-----------------------------------+
+============= ==================================================================
+Argument      Description
+============= ==================================================================
+``model``     The model that will perform a prediction.
+``path``      Destination path where this MLflow compatible model will be saved.
+``...``       Optional additional arguments.
+``conda_env`` Path to Conda dependencies file.
+============= ==================================================================
 
 ``mlflow_search_runs``
 ======================
@@ -1403,11 +1393,11 @@ experiments.
 Arguments
 ---------
 
-+----------+--------------------------------------+
-| Argument | Description                          |
-+==========+======================================+
-| ``uri``  | The URI to the remote MLflow server. |
-+----------+--------------------------------------+
+======== ====================================
+Argument Description
+======== ====================================
+``uri``  The URI to the remote MLflow server.
+======== ====================================
 
 ``mlflow_source``
 =================
@@ -1426,11 +1416,11 @@ called via ``Rscript`` from the terminal or through the MLflow CLI.
 Arguments
 ---------
 
-+----------+----------------------------------------------------------+
-| Argument | Description                                              |
-+==========+==========================================================+
-| ``uri``  | Path to an R script, can be a quoted or unquoted string. |
-+----------+----------------------------------------------------------+
+======== ========================================================
+Argument Description
+======== ========================================================
+``uri``  Path to an R script, can be a quoted or unquoted string.
+======== ========================================================
 
 ``mlflow_start_run``
 ====================

docs/source/projects.rst

@@ -99,8 +99,8 @@ Docker container environment
 
   Environment variables, such as ``MLFLOW_TRACKING_URI``, are propagated inside the Docker container 
   during project execution. Additionally, :ref:`runs <concepts>` and 
-  :ref:`experiments <organizing-runs-in-experiments>` created by the project are saved to the 
-  tracking server specified by your :ref:`tracking URI <where-runs-are-recorded>`. When running 
+  :ref:`experiments <organizing_runs_in_experiments>` created by the project are saved to the 
+  tracking server specified by your :ref:`tracking URI <where_runs_are_recorded>`. When running 
   against a local tracking URI, MLflow mounts the host system's tracking directory
   (e.g., a local ``mlruns`` directory) inside the container so that metrics, parameters, and 
   artifacts logged during project execution are accessible afterwards.

mlflow/h2o.py

@@ -26,7 +26,7 @@
 def get_default_conda_env():
     """
     :return: The default Conda environment for MLflow Models produced by calls to
-    :func:`save_model()` and :func:`log_model()`.
+             :func:`save_model()` and :func:`log_model()`.
     """
     import h2o
 

mlflow/keras.py

@@ -28,7 +28,7 @@
 def get_default_conda_env():
     """
     :return: The default Conda environment for MLflow Models produced by calls to
-    :func:`save_model()` and :func:`log_model()`.
+             :func:`save_model()` and :func:`log_model()`.
     """
     import keras
     import tensorflow as tf

mlflow/models/__init__.py

@@ -104,9 +104,8 @@ def predict(self, model_uri, input_path, output_path, content_type, json_format)
         :param json_format: Only applies if content_type == 'json'. Specifies how is the input data
                             encoded in json. Can be one of {'split', 'records'} mirroring the
                             behavior of Pandas orient attribute. The default is 'split' which
-                            expects dict like data: {'index' -> [index],
-                                                     'columns' -> [columns],
-                                                     'data' -> [values]}, where index is optional.
+                            expects dict like data: ``{'index' -> [index], 'columns' -> [columns],
+                            'data' -> [values]}``, where index is optional.
                             For more information see "https://pandas.pydata.org/
                             pandas-docs/stable/reference/api/pandas.read_json.html"
         """

mlflow/pyfunc/__init__.py

@@ -364,6 +364,7 @@ def spark_udf(spark, model_uri, result_type="double"):
                         :class:`pyspark.sql.types.DataType` object or a DDL-formatted type string.
                         Only a primitive type or an array (pyspark.sql.types.ArrayType) of primitive
                         types are allowed. The following classes of result type are supported:
+
                         - "int" or pyspark.sql.types.IntegerType: The leftmost integer that can fit
                           in int32 result is returned or exception is raised if there is none.
                         - "long" or pyspark.sql.types.LongType: The leftmost long integer that can

mlflow/pytorch/__init__.py

@@ -42,7 +42,7 @@
 def get_default_conda_env():
     """
     :return: The default Conda environment for MLflow Models produced by calls to
-    :func:`save_model()` and :func:`log_model()`.
+             :func:`save_model()` and :func:`log_model()`.
     """
     import torch
     import torchvision

mlflow/sklearn.py

@@ -39,7 +39,7 @@
 def get_default_conda_env(include_cloudpickle=False):
     """
     :return: The default Conda environment for MLflow Models produced by calls to
-    :func:`save_model()` and :func:`log_model()`.
+             :func:`save_model()` and :func:`log_model()`.
     """
     import sklearn
     pip_deps = None

mlflow/spark.py

@@ -47,7 +47,7 @@
 def get_default_conda_env():
     """
     :return: The default Conda environment for MLflow Models produced by calls to
-    :func:`save_model()` and :func:`log_model()`.
+             :func:`save_model()` and :func:`log_model()`.
     """
     import pyspark
 

mlflow/tensorflow.py

@@ -36,7 +36,7 @@
 def get_default_conda_env():
     """
     :return: The default Conda environment for MLflow Models produced by calls to
-    :func:`save_model()` and :func:`log_model()`.
+             :func:`save_model()` and :func:`log_model()`.
     """
     import tensorflow as tf
     return _mlflow_conda_env(