From fdf840847e5556a99fae2dbee2b6a3b61e8363f0 Mon Sep 17 00:00:00 2001 From: Vandana Kannan Date: Tue, 18 Dec 2018 15:22:29 -0800 Subject: [PATCH] Some corrections --- tests/python-pytest/onnx/mxnet_export_test.py | 7 +------ tests/python-pytest/onnx/test_models.py | 7 +------ tests/python-pytest/onnx/test_node.py | 2 +- 3 files changed, 3 insertions(+), 13 deletions(-) diff --git a/tests/python-pytest/onnx/mxnet_export_test.py b/tests/python-pytest/onnx/mxnet_export_test.py index 8e6dc74e01ff..6c81198a8bca 100644 --- a/tests/python-pytest/onnx/mxnet_export_test.py +++ b/tests/python-pytest/onnx/mxnet_export_test.py @@ -15,12 +15,7 @@ # specific language governing permissions and limitations # under the License. -""" -Tests for individual operators -This module contains operator tests which currently do not exist on -ONNX backend test framework. Once we have PRs on the ONNX repo and get -those PRs merged, this file will get EOL'ed. -""" + # pylint: disable=too-many-locals,wrong-import-position,import-error from __future__ import absolute_import import os diff --git a/tests/python-pytest/onnx/test_models.py b/tests/python-pytest/onnx/test_models.py index ab38c065c116..46080c6daecc 100644 --- a/tests/python-pytest/onnx/test_models.py +++ b/tests/python-pytest/onnx/test_models.py @@ -15,12 +15,7 @@ # specific language governing permissions and limitations # under the License. -""" -Tests for individual operators -This module contains operator tests which currently do not exist on -ONNX backend test framework. Once we have PRs on the ONNX repo and get -those PRs merged, this file will get EOL'ed. -""" + # pylint: disable=too-many-locals,wrong-import-position,import-error from __future__ import absolute_import import sys diff --git a/tests/python-pytest/onnx/test_node.py b/tests/python-pytest/onnx/test_node.py index 7498f44425b8..2e7bda8633b4 100644 --- a/tests/python-pytest/onnx/test_node.py +++ b/tests/python-pytest/onnx/test_node.py @@ -50,7 +50,7 @@ def get_rnd(shape, low=-1.0, high=1.0, dtype=np.float32): return (np.random.uniform(low, high, np.prod(shape)).reshape(shape).astype(np.float32)) elif dtype == np.int32: - return (np.random.uniform(low, high, + return (np.random.randint(low, high, np.prod(shape)).reshape(shape).astype(np.float32)) elif dtype == np.bool_: return np.random.choice(a=[False, True], size=shape).astype(np.float32)