From 6de5a04f95dc32a4656dd7beff699f42a1776c5f Mon Sep 17 00:00:00 2001
From: Adrian Garcia Badaracco <1755071+adriangb@users.noreply.github.com>
Date: Mon, 30 Aug 2021 19:36:15 -0500
Subject: [PATCH] MAINT: Prepare for 0.4.0 release (#242)

---
 HISTORY.md              | 12 ++++++++++++
 README.md               |  7 +++++++
 docs/source/install.rst | 19 +++++++++++++------
 pyproject.toml          |  2 +-
 4 files changed, 33 insertions(+), 7 deletions(-)

diff --git a/HISTORY.md b/HISTORY.md
index fb8098c95..b4822a0a0 100644
--- a/HISTORY.md
+++ b/HISTORY.md
@@ -1,5 +1,17 @@
 # History
 
+## 0.4.0 (2021-08-30)
+
+Features:
+
+* Support routed parameters to callbacks (#233)
+
+Changes:
+
+* Official support for extra keyword arguments (`**kwargs`) in `fit()`, `predict()` and `predict_proba()` that are routed directly to Keras (#238)
+* Remove hard dependency on `tensorflow`, allowing users to choose `tensorflow-cpu` or other distributions in environments where they can't control `pip` arguments (#237)
+* Remove hard dependency on `tensorflow`, allowing users to choose `tensorflow-cpu` or other distributions (#237)
+
 ## 0.3.1 (2021-04-12)
 
 Fixes:
diff --git a/README.md b/README.md
index 5cf93d8b5..dfbf1be3a 100644
--- a/README.md
+++ b/README.md
@@ -24,6 +24,13 @@ pip install scikeras
 
 The only dependencies are `scikit-learn>=0.22` and `TensorFlow>=2.4.0`.
 
+You will need to manually install TensorFlow; due to TensorFlow's packaging it is not a direct dependency of SciKeras.
+You can do this by running:
+
+```bash
+pip install tensorflow
+```
+
 ### Migrating from `tf.keras.wrappers.scikit_learn`
 
 Please see the [migration](https://www.adriangb.com/scikeras/stable/migration.html) section of our documentation.
diff --git a/docs/source/install.rst b/docs/source/install.rst
index 85f072551..3c90370ee 100644
--- a/docs/source/install.rst
+++ b/docs/source/install.rst
@@ -17,15 +17,22 @@ To install with pip, run:
 
 We recommend to use a virtual environment for this.
 
-To install without any dependencies, eg. to use a custom
-TensorFlow build or `tensorflow-cpu`_, you can instruct pip to ignore dependencies:
+You will need to manually install TensorFlow; due to TensorFlow's packaging it is not a direct dependency of SciKeras.
+You can do this by running:
+
+.. code:: bash
+
+    pip install tensorflow
+
+This allows you to install an alternative TensorFlow binary, for example `tensorflow-cpu`_.
+
+You can also install SciKeras without any dependencies, for example to install a nightly version of Scikit-Learn:
 
 .. code:: bash
 
     pip install --no-deps scikeras
 
-Then manually install compatible versions of TensorFlow and Scikit-Learn.
-As of SciKeras v0.3.3, the minimum required versions are as follows:
+As of SciKeras v0.4.0, the minimum required versions are as follows:
 
 - TensorFlow: v2.4.0
 - Scikit-Learn: v0.22.0
@@ -33,8 +40,8 @@ As of SciKeras v0.3.3, the minimum required versions are as follows:
 Developer Installation
 ~~~~~~~~~~~~~~~~~~~~~~
 
-If you would like to use the must recent additions to scikeras or
-help development, you should install scikeras from source.
+If you would like to use the must recent additions to SciKeras or
+help development, you should install SciKeras from source.
 
 We use Poetry_ to manage dependencies.
 
diff --git a/pyproject.toml b/pyproject.toml
index 5fff24adc..ccd6d2c30 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -27,7 +27,7 @@ license = "MIT"
 name = "scikeras"
 readme = "README.md"
 repository = "https://github.com/adriangb/scikeras"
-version = "0.3.3"
+version = "0.4.0"
 
 [tool.poetry.dependencies]
 importlib-metadata = {version = "^3", python = "<3.8"}