From a21ea6ea14efc6ac61e8ffd8c28d17c1374c7fe6 Mon Sep 17 00:00:00 2001
From: Brett Kuprel <brkuprel@gmail.com>
Date: Mon, 4 Jul 2022 07:28:44 -0400
Subject: [PATCH] update replicate, clear cuda cache if cuda available

---
 README.rst           | 12 ++++++------
 cog.yaml             |  2 +-
 replicate/predict.py | 10 +++++-----
 setup.py             |  2 +-
 4 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/README.rst b/README.rst
index 1871749..726495c 100644
--- a/README.rst
+++ b/README.rst
@@ -4,13 +4,13 @@ min(DALL·E)
 |Open In Colab|   |Replicate|   |Join us on Discord|
 
 This is a fast, minimal implementation of Boris Dayma’s `DALL·E
-Mini <https://github.com/borisdayma/dalle-mini>`__. It has been stripped
+Mega <https://github.com/borisdayma/dalle-mini>`__. It has been stripped
 down for inference and converted to PyTorch. The only third party
 dependencies are numpy, requests, pillow and torch.
 
-To generate a 3x3 grid of DALL·E Mega images it takes - **35 seconds**
-with a P100 in Colab - **15 seconds** with an A100 on Replicate -
-**TBD** with an H100 (@NVIDIA?)
+It takes - **35 seconds** to generate a 3x3 grid with a P100 in Colab -
+**16 seconds** to generate a 4x4 grid with an A100 on Replicate -
+**TBD** to generate a 4x4 grid with an H100 (@NVIDIA?)
 
 The flax model and code for converting it to torch can be found
 `here <https://github.com/kuprel/min-dalle-flax>`__.
@@ -40,7 +40,7 @@ not already there. Once everything has finished initializing, call
 
 .. code:: python
 
-   text = 'Dali painting of WallE'
+   text = 'Dali painting of WALL·E'
    image = model.generate_image(text, seed=0, grid_size=4)
    display(image)
 
@@ -81,7 +81,7 @@ Use ``image_from_text.py`` to generate images from the command line.
 
 .. code:: bash
 
-   $ python image_from_text.py --text='artificial intelligence' --seed=7
+   $ python image_from_text.py --text='artificial intelligence' --no-mega --seed=7
 
 .. code:: bash
 
diff --git a/cog.yaml b/cog.yaml
index 55d328d..1453f1a 100644
--- a/cog.yaml
+++ b/cog.yaml
@@ -6,7 +6,7 @@ build:
     - "libgl1-mesa-glx"
     - "libglib2.0-0"
   python_packages:
-    - "min-dalle==0.2.13"
+    - "min-dalle==0.2.14"
   run:
     - pip install torch==1.10.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html
 
diff --git a/replicate/predict.py b/replicate/predict.py
index bbe39d0..f14d853 100644
--- a/replicate/predict.py
+++ b/replicate/predict.py
@@ -11,17 +11,17 @@ class Predictor(BasePredictor):
         self,
         text: str = Input(
             description='Text',
-            default='court sketch of godzilla on trial'
+            default='Dali painting of WALL·E'
         ),
         seed: int = Input(
-            description='Seed',
-            default=6
+            description='Set the seed to a positive number for reproducible results',
+            default=-1
         ),
         grid_size: int = Input(
-            description='Grid Size',
+            description='Size of the image grid',
             ge=1,
             le=4,
-            default=3
+            default=4
         )
     ) -> Path:
         image = self.model.generate_image(text, seed, grid_size=grid_size)
diff --git a/setup.py b/setup.py
index 1949018..a55a824 100644
--- a/setup.py
+++ b/setup.py
@@ -5,7 +5,7 @@ setuptools.setup(
     name='min-dalle',
     description = 'min(DALL·E)',
     long_description=(Path(__file__).parent / "README.rst").read_text(),
-    version='0.2.13',
+    version='0.2.14',
     author='Brett Kuprel',
     author_email='brkuprel@gmail.com',
     url='https://github.com/kuprel/min-dalle',