JNA libpython bindings to the tech ecosystem.
We aim to integrate Python into Clojure at a deep level. This means that we want to be able to load/use python modules almost as if they were Clojure namespaces. We also want to be able to use Clojure to extend Python objects. I gave a talk at Clojure Conj 2019 that outlines more of what is going on.
This code is a concrete example that generates an embedding for faces:
(ns facial-rec.face-feature
(:require [libpython-clj.require :refer [require-python]]
[libpython-clj.python :refer [py. py.. py.-] :as py]
[tech.v2.datatype :as dtype]))
(require-python 'mxnet
'(mxnet ndarray module io model))
(require-python 'cv2)
(require-python '[numpy :as np])
(defn load-model
[& {:keys [model-path checkpoint]
:or {model-path "models/recognition/model"
checkpoint 0}}]
(let [[sym arg-params aux-params] (mxnet.model/load_checkpoint model-path checkpoint)
all-layers (py. sym get_internals)
target-layer (py/get-item all-layers "fc1_output")
model (mxnet.module/Module :symbol target-layer
:context (mxnet/cpu)
:label_names nil)]
(py. model bind :data_shapes [["data" [1 3 112 112]]])
(py. model set_params arg-params aux-params)
model))
(defonce model (load-model))
(defn face->feature
[img-path]
(py/with-gil-stack-rc-context
(if-let [new-img (cv2/imread img-path)]
(let [new-img (cv2/cvtColor new-img cv2/COLOR_BGR2RGB)
new-img (np/transpose new-img [2 0 1])
input-blob (np/expand_dims new-img :axis 0)
data (mxnet.ndarray/array input-blob)
batch (mxnet.io/DataBatch :data [data])]
(py. model forward batch :is_train false)
(-> (py. model get_outputs)
first
(py. asnumpy)
(#(dtype/make-container :java-array :float32 %))))
(throw (Exception. (format "Failed to load img: %s" img-path))))))
(ns my-py-clj.config
(:require [libpython-clj.python :as py]))
;; When you use conda, it should look like this.
(py/initialize! :python-executable "/opt/anaconda3/envs/my_env/bin/python3.7"
:library-path "/opt/anaconda3/envs/my_env/lib/libpython3.7m.dylib")
{...
;; This namespace going to run when the REPL is up.
:repl-options {:init-ns my-py-clj.config}
...}
user> (require '[libpython-clj.require :refer [require-python]])
...logging info....
nil
user> (require-python '[numpy :as np])
nil
user> (def test-ary (np/array [[1 2][3 4]]))
#'user/test-ary
user> test-ary
[[1 2]
[3 4]]
We have a document on all the features but beginning usage is pretty simple. Import your modules, use the things from Clojure. We have put effort into making sure things like sequences and ranges transfer between the two languages.
One very complimentary aspect of Python with respect to Clojure is it's integration with cutting edge native libraries. Our support isn't perfect so some understanding of the mechanism is important to diagnose errors and issues.
Current, we launch the python3 executable and print out various different bits of
configuration as json. We parse the json and use the output to attempt to find
the libpython3.Xm.so
shared library so for example if we are loading python
3.6 we look for libpython3.6m.so
on Linux or libpython3.6m.dylib
on the Mac.
This pathway has allowed us support Conda albeit with some work. For examples using Conda, check out the facial rec repository above or look into how we build our test docker containers.
New to Clojure or the JVM? Try remixing the nextjournal entry and playing around there. For more resources on learning and getting more comfortable with Clojure, we have an introductory document.
To install jar to local .m2 :
$ lein install
$ lein deploy clojars
This command will sign jar before deploy, using your gpg key. (see dev/src/build.clj for signing options)
Copyright © 2019 Chris Nuernberger
This program and the accompanying materials are made available under the terms of the Eclipse Public License 2.0 which is available at http://www.eclipse.org/legal/epl-2.0.
Can you improve this documentation? These fine people already did:
Chris Nuernberger, Ertuğrul Çetin, Carin Meier, Arsene Rei & skullgoblet1089Edit on GitHub
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