Fix: bug in benchmark tests

.travis.yml

@@ -7,11 +7,11 @@ python:
 before_install:
   - pip install --upgrade pip setuptools wheel
 install:
-  - pip install --ignore-installed -U -q -e .[tensorflow,torch,mxnet,minuit,develop]  # Ensure right version of NumPy installed
+  - pip install --ignore-installed -U -q -e .[tensorflow,torch,mxnet,minuit,develop]
   - pip freeze
 script:
   - pyflakes pyhf
-  - pytest --ignore tests/benchmarks/ --ignore tests/test_notebooks.py
+  - pytest -r sx --ignore tests/benchmarks/ --ignore tests/test_notebooks.py
 after_success: coveralls
 
 # always test (on both 'push' and 'pr' builds in Travis)
@@ -45,17 +45,17 @@ jobs:
     before_install:
       - pip install --upgrade pip setuptools wheel
     install:
-      - pip install --ignore-installed -U -q -e .[tensorflow,torch,mxnet,develop]
+      - pip install --ignore-installed -U -q -e .[tensorflow,torch,mxnet,minuit,develop]
       - pip freeze
-    script: pytest --benchmark-sort=mean tests/benchmarks/
+    script: pytest -r sx --benchmark-sort=mean tests/benchmarks/
   - stage: docs
     python: '3.6'
     before_install:
       - sudo apt-get update
       - sudo apt-get -qq install pandoc
       - pip install --upgrade pip setuptools wheel
     install:
-      - pip install --ignore-installed -U -q -e .[tensorflow,torch,mxnet,develop]
+      - pip install --ignore-installed -U -q -e .[tensorflow,torch,mxnet,minuit,develop]
       - pip freeze
     script:
     - python -m doctest README.md

pyhf/tensor/numpy_backend.py

@@ -1,6 +1,6 @@
 import numpy as np
 import logging
-from scipy.special import gammaln, xlogy
+from scipy.special import gammaln
 from scipy.stats import norm
 log = logging.getLogger(__name__)
 

tests/benchmarks/test_benchmark.py

@@ -1,6 +1,5 @@
 import pyhf
 from pyhf.simplemodels import hepdata_like
-import tensorflow as tf
 import numpy as np
 import pytest
 
@@ -64,11 +63,6 @@ def generate_source_poisson(n_bins):
 
 
 def runOnePoint(pdf, data):
-    if isinstance(pyhf.tensorlib, pyhf.tensor.tensorflow_backend):
-        # Reset the TensorFlow graph and session for each run
-        tf.reset_default_graph()
-        pyhf.tensorlib.session = tf.Session()
-
     return pyhf.utils.runOnePoint(1.0, data, pdf,
                                   pdf.config.suggested_init(),
                                   pdf.config.suggested_bounds())
@@ -80,19 +74,7 @@ def runOnePoint(pdf, data):
 
 
 @pytest.mark.parametrize('n_bins', bins, ids=bin_ids)
-@pytest.mark.parametrize('backend',
-                         [
-                             pyhf.tensor.numpy_backend(),
-                             pyhf.tensor.tensorflow_backend(session=tf.Session()),
-                             pyhf.tensor.pytorch_backend(),
-                             # pyhf.tensor.mxnet_backend(),
-                         ],
-                         ids=[
-                             'numpy',
-                             'tensorflow',
-                             'pytorch',
-                             # 'mxnet',
-                         ])
+@pytest.mark.skip_mxnet
 def test_runOnePoint(benchmark, backend, n_bins):
     """
     Benchmark the performance of pyhf.runOnePoint()

tests/test_pdf.py

@@ -57,13 +57,8 @@ def test_core_pdf_broadcasting(backend):
     assert broadcasted.shape    == np.array(data).shape
     assert np.all(naive_python  == broadcasted)
 
-<<<<<<< dd198c062e2415192815c27d224d2897b7b9c2bd
 @pytest.mark.only_numpy
 def test_pdf_integration_staterror(backend):
-=======
-
-def test_pdf_integration_staterror():
->>>>>>> Wrap json.load in with clause to safely load and close
     spec = {
         'channels': [
             {
@@ -111,16 +106,9 @@ def test_pdf_integration_staterror():
     for c,e in zip(computed,expected):
         assert c==e
 
-<<<<<<< dd198c062e2415192815c27d224d2897b7b9c2bd
 @pytest.mark.only_numpy
 def test_pdf_integration_histosys(backend):
     source = json.load(open('validation/data/2bin_histosys_example2.json'))
-=======
-
-def test_pdf_integration_histosys():
-    with open('validation/data/2bin_histosys_example2.json') as read_json:
-        source = json.load(read_json)
->>>>>>> Wrap json.load in with clause to safely load and close
     spec = {
         'channels': [
             {
@@ -171,17 +159,7 @@ def test_pdf_integration_histosys():
 
 @pytest.mark.skip_mxnet
 def test_pdf_integration_normsys(backend):
-<<<<<<< dd198c062e2415192815c27d224d2897b7b9c2bd
     source = json.load(open('validation/data/2bin_histosys_example2.json'))
-=======
-    pyhf.set_backend(backend)
-    if isinstance(pyhf.tensorlib, pyhf.tensor.tensorflow_backend):
-        tf.reset_default_graph()
-        pyhf.tensorlib.session = tf.Session()
-
-    with open('validation/data/2bin_histosys_example2.json') as read_json:
-        source = json.load(read_json)
->>>>>>> Wrap json.load in with clause to safely load and close
     spec = {
         'channels': [
             {
@@ -217,16 +195,9 @@ def test_pdf_integration_normsys(backend):
     pars[pdf.config.par_slice('mu')], pars[pdf.config.par_slice('bkg_norm')] = [[0.0], [-1.0]]
     assert np.allclose(pyhf.tensorlib.tolist(pdf.expected_data(pars, include_auxdata = False)),[100*0.9,150*0.9])
 
-<<<<<<< dd198c062e2415192815c27d224d2897b7b9c2bd
 @pytest.mark.only_numpy
 def test_pdf_integration_shapesys(backend):
     source = json.load(open('validation/data/2bin_histosys_example2.json'))
-=======
-
-def test_pdf_integration_shapesys():
-    with open('validation/data/2bin_histosys_example2.json') as read_json:
-        source = json.load(read_json)
->>>>>>> Wrap json.load in with clause to safely load and close
     spec = {
         'channels': [
             {
@@ -321,12 +292,4 @@ def test_invalid_modifier_name_resuse():
     with pytest.raises(pyhf.exceptions.InvalidNameReuse):
         pdf = pyhf.Model(spec, poiname = 'reused_name')
 
-<<<<<<< dd198c062e2415192815c27d224d2897b7b9c2bd
-    pdf  = pyhf.Model(spec, poiname = 'reused_name', qualify_names = True)
-<<<<<<< 01c6b81aeb46c5f30df8f698666fae1a2595f5a4
-
-=======
->>>>>>> Remove use of poisson_from_normal=True from everywhere
-=======
     pdf = pyhf.Model(spec, poiname = 'reused_name', qualify_names = True)
->>>>>>> Wrap json.load in with clause to safely load and close

tests/test_tensor.py

@@ -52,6 +52,8 @@ def test_common_tensor_backends(backend):
     with pytest.raises(Exception):
         tb.simple_broadcast([1], [2, 3], [5, 6, 7])
 
+    # poisson(lambda=0) is not defined, should return NaN
+    assert tb.tolist(pyhf.tensorlib.poisson([0, 0, 1, 1], [0, 1, 0, 1])) == pytest.approx([np.nan, 0.3678794503211975, 0.0, 0.3678794503211975], nan_ok=True)
 
 def test_einsum(backend):
     tb = pyhf.tensorlib