STT-tensorflow/tensorflow/lite/testing/op_tests/abs.py
Suharsh Sivakumar 7270ba4e6d Add dynamic_range_quantize to generated op_test infra.
Will add to all op_tests to get complete coverage in subsequent CLs.

PiperOrigin-RevId: 316177819
Change-Id: I3fe9d13e7116aa849111a27ab38b4c1815ee82e2
2020-06-12 14:43:05 -07:00

51 lines
2.0 KiB
Python

# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Test configs for abs."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow.compat.v1 as tf
from tensorflow.lite.testing.zip_test_utils import create_tensor_data
from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
from tensorflow.lite.testing.zip_test_utils import register_make_test_function
@register_make_test_function()
def make_abs_tests(options):
"""Make a set of tests to do abs."""
# Chose a set of parameters
test_parameters = [{
"input_shape": [[], [1], [2, 3], [1, 1, 1, 1], [1, 3, 4, 3],
[3, 15, 14, 3], [3, 1, 2, 4, 6], [2, 2, 3, 4, 5, 6]],
"dynamic_range_quantize": [False, True]
}]
def build_graph(parameters):
input_tensor = tf.compat.v1.placeholder(
dtype=tf.float32, name="input", shape=parameters["input_shape"])
out = tf.abs(input_tensor)
return [input_tensor], [out]
def build_inputs(parameters, sess, inputs, outputs):
input_values = create_tensor_data(
np.float32, parameters["input_shape"], min_value=-10, max_value=10)
return [input_values], sess.run(
outputs, feed_dict=dict(zip(inputs, [input_values])))
make_zip_of_tests(options, test_parameters, build_graph, build_inputs)