test for invalid sampling methods

pysgmcmc/tests/bayesian_neural_network/test_invalid_inputs.py

@@ -0,0 +1,100 @@
+import pytest
+import tensorflow as tf
+try:
+    from hypothesis import given
+    from hypothesis.strategies import (
+        one_of, floats, complex_numbers, lists,
+        sets, fractions, text, integers
+    )
+except ImportError:
+    HYPOTHESIS_INSTALLED = False
+else:
+    HYPOTHESIS_INSTALLED = True
+
+from pysgmcmc.models.bayesian_neural_network import BayesianNeuralNetwork
+
+
+@given(
+    one_of(
+        floats(), complex_numbers(), lists(integers(), max_size=10),
+        sets(integers(), max_size=10), fractions(), text(),
+        integers(max_value=0)
+    )
+)
+def test_invalid_n_nets(n_nets):
+    with pytest.raises(AssertionError):
+        graph = tf.Graph()
+        with tf.Session(graph=graph) as session:
+            BayesianNeuralNetwork(n_nets=n_nets, session=session)
+
+
+@given(
+    one_of(
+        floats(), complex_numbers(), lists(integers(), max_size=10),
+        sets(integers(), max_size=10), fractions(), text(),
+        integers(max_value=0)
+    )
+)
+def test_invalid_n_iters(n_iters):
+    with pytest.raises(AssertionError):
+        graph = tf.Graph()
+        with tf.Session(graph=graph) as session:
+            BayesianNeuralNetwork(n_iters=n_iters, session=session)
+
+
+@given(
+    one_of(
+        floats(), complex_numbers(), lists(integers(), max_size=10),
+        sets(integers(), max_size=10), fractions(), text(),
+        integers(max_value=-1)
+    )
+)
+def test_invalid_burn_in_steps(burn_in_steps):
+    with pytest.raises(AssertionError):
+        graph = tf.Graph()
+        with tf.Session(graph=graph) as session:
+            BayesianNeuralNetwork(burn_in_steps=burn_in_steps, session=session)
+
+
+@given(
+    one_of(
+        floats(), complex_numbers(), lists(integers(), max_size=10),
+        sets(integers(), max_size=10), fractions(), text(),
+        integers(max_value=-1)
+    )
+)
+def test_invalid_sample_steps(sample_steps):
+    with pytest.raises(AssertionError):
+        graph = tf.Graph()
+        with tf.Session(graph=graph) as session:
+            BayesianNeuralNetwork(sample_steps=sample_steps, session=session)
+
+
+@given(
+    one_of(
+        floats(), complex_numbers(), lists(integers(), max_size=10),
+        sets(integers(), max_size=10), fractions(), text(),
+        integers(max_value=-1)
+    )
+)
+def test_invalid_batch_size(batch_size):
+    with pytest.raises(AssertionError):
+        graph = tf.Graph()
+        with tf.Session(graph=graph) as session:
+            BayesianNeuralNetwork(batch_size=batch_size, session=session)
+
+
+@given(
+    one_of(
+        floats(), complex_numbers(), lists(integers(), max_size=10),
+        sets(integers(), max_size=10), fractions(), text(),
+        integers()
+    )
+)
+def test_invalid_sampling_methods(sampling_method):
+    with pytest.raises(ValueError):
+        graph = tf.Graph()
+        with tf.Session(graph=graph) as session:
+            BayesianNeuralNetwork(
+                sampling_method=sampling_method, session=session
+            )