Add MXNet backend

binder/environment.yml

@@ -0,0 +1,111 @@
+name: pyhf
+channels:
+- pytorch
+- https://conda.anaconda.org/NLeSC
+- defaults
+dependencies:
+- ca-certificates=2017.08.26=h1d4fec5_0
+- certifi=2018.1.18=py36_0
+- cffi=1.11.4=py36h9745a5d_0
+- cudatoolkit=8.0=3
+- cudnn=7.0.5=cuda8.0_0
+- freetype=2.8=hab7d2ae_1
+- intel-openmp=2018.0.0=hc7b2577_8
+- jpeg=9b=h024ee3a_2
+- libedit=3.1=heed3624_0
+- libffi=3.2.1=hd88cf55_4
+- libgcc-ng=7.2.0=h7cc24e2_2
+- libgfortran-ng=7.2.0=h9f7466a_2
+- libpng=1.6.34=hb9fc6fc_0
+- libstdcxx-ng=7.2.0=h7a57d05_2
+- libtiff=4.0.9=h28f6b97_0
+- mkl=2018.0.1=h19d6760_4
+- nccl=1.3.4=cuda8.0_1
+- ncurses=6.0=h9df7e31_2
+- numpy=1.14.0=py36h3dfced4_1
+- olefile=0.45.1=py36_0
+- openssl=1.0.2n=hb7f436b_0
+- pillow=5.0.0=py36h3deb7b8_0
+- pip=9.0.1=py36h6c6f9ce_4
+- pycparser=2.18=py36hf9f622e_1
+- python=3.6.4=hc3d631a_1
+- pytorch=0.3.0=py36cuda8.0cudnn7.0_0
+- readline=7.0=ha6073c6_4
+- setuptools=38.4.0=py36_0
+- six=1.11.0=py36h372c433_1
+- sqlite=3.22.0=h1bed415_0
+- tk=8.6.7=hc745277_3
+- torchvision=0.2.0=py36_0
+- wheel=0.30.0=py36hfd4bba0_1
+- xz=5.2.3=h55aa19d_2
+- zlib=1.2.11=ha838bed_2
+- cuda90=1.0=h6433d27_0
+- pip:
+  - absl-py>=0.1.10
+  - ansiwrap>=0.8.3
+  - attrs>=17.4.0
+  - bleach>=1.5.0
+  - boto3>=1.5.26
+  - botocore>=1.8.40
+  - chardet>=3.0.4
+  - click>=6.7
+  - coverage>=4.5.1
+  - cycler>=0.10.0
+  - decorator>=4.2.1
+  - docutils>=0.14
+  - entrypoints>=0.2.3
+  - future>=0.16.0
+  - graphviz>=0.8.1
+  - html5lib>=0.9999999
+  - idna>=2.6
+  - ipython>=6.2.1
+  - ipython-genutils>=0.2.0
+  - jedi>=0.11.1
+  - jinja2>=2.10
+  - jmespath>=0.9.3
+  - jsonschema>=2.6.0
+  - jupyter-client>=5.2.2
+  - jupyter-core>=4.4.0
+  - markdown>=2.6.11
+  - markupsafe>=1.0
+  - matplotlib>=2.1.2
+  - mistune>=0.8.3
+  - mxnet>=1.0.0.post4
+  - nbconvert>=5.3.1
+  - nbformat>=4.4.0
+  - pandas>=0.22.0
+  - pandocfilters>=1.4.2
+  - papermill>=0.12.2
+  - parso>=0.1.1
+  - pexpect>=4.4.0
+  - pickleshare>=0.7.4
+  - pluggy>=0.6.0
+  - prompt-toolkit>=1.0.15
+  - protobuf>=3.5.1
+  - ptyprocess>=0.5.2
+  - py>=1.5.2
+  - pygments>=2.2.0
+  - pyhf>=0.0.4
+  - pyparsing>=2.2.0
+  - pytest>=3.4.0
+  - pytest-cov>=2.5.1
+  - python-dateutil>=2.6.1
+  - pytz>=2018.3
+  - pyyaml>=3.12
+  - pyzmq>=17.0.0
+  - requests>=2.18.4
+  - s3transfer>=0.1.12
+  - scipy>=1.0.0
+  - simplegeneric>=0.8.1
+  - tensorflow>=1.5.0
+  - tensorflow-tensorboard>=1.5.1
+  - testpath>=0.3.1
+  - textwrap3>=0.9.1
+  - torch>=0.3.0
+  - tornado>=4.5.3
+  - tqdm>=4.19.5
+  - traitlets>=4.3.2
+  - uproot>=2.6.10
+  - urllib3>=1.22
+  - wcwidth>=0.1.7
+  - werkzeug>=0.14.1

examples/notebooks/example-mxnet.ipynb

@@ -0,0 +1,96 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Populating the interactive namespace from numpy and matplotlib\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pylab inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pyhf\n",
+    "from pyhf import hfpdf\n",
+    "from pyhf.simplemodels import hepdata_like\n",
+    "import mxnet as mx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--------\n",
+      "as MXNet\n",
+      "--------\n",
+      "<class 'mxnet.ndarray.ndarray.NDArray'> \n",
+      "[-22.87784958]\n",
+      "<NDArray 1 @cpu(0)>\n"
+     ]
+    }
+   ],
+   "source": [
+    "source = {\n",
+    "  \"binning\": [2,-0.5,1.5],\n",
+    "  \"bindata\": {\n",
+    "    \"data\": [120.0, 180.0],\n",
+    "    \"bkg\": [100.0, 150.0],\n",
+    "    \"bkgerr\": [10.0, 10.0],\n",
+    "    \"sig\": [30.0, 95.0]\n",
+    "  }\n",
+    "}\n",
+    "\n",
+    "pdf = hepdata_like(source['bindata']['sig'], source['bindata']['bkg'], source['bindata']['bkgerr'])\n",
+    "data = source['bindata']['data'] + pdf.config.auxdata\n",
+    "\n",
+    "init_pars = pdf.config.suggested_init()\n",
+    "par_bounds = pdf.config.suggested_bounds()\n",
+    "\n",
+    "\n",
+    "print('--------\\nas MXNet\\n--------')\n",
+    "pyhf.tensorlib = pyhf.mxnet_backend()\n",
+    "v = pdf.logpdf(init_pars, data)\n",
+    "print(type(v),v)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

pyhf/__init__.py

@@ -18,6 +18,12 @@
 except ImportError:
     pass
 
+try:
+    from .tensor.mxnet_backend import mxnet_backend
+    assert mxnet_backend
+except ImportError:
+    pass
+
 
 tensorlib = numpy_backend()
 optimizer = scipy_optimizer()