tensorflow/lite/testing/op_tests/right_shift.py
# Copyright 2023 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 right_shift operator."""
import tensorflow 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_right_shift_tests(options):
"""Generate examples for right_shift."""
test_parameters = [
{
"input_dtype": [
tf.uint8,
tf.int8,
tf.uint16,
tf.int16,
tf.uint32,
tf.int32,
],
"input_shape_pair": [
([], []),
([2, 3, 4], [2, 3, 4]),
([1, 1, 1, 3], [1, 1, 1, 3]),
([5, 5], [1]),
([10], [2, 4, 10]),
([2, 3, 3], [2, 3]), # this test case is intended to fail
],
},
]
def build_graph(parameters):
"""Build the right_shift testing graph."""
input_value1 = tf.compat.v1.placeholder(
dtype=parameters["input_dtype"],
name="input1",
shape=parameters["input_shape_pair"][0],
)
input_value2 = tf.compat.v1.placeholder(
dtype=parameters["input_dtype"],
name="input2",
shape=parameters["input_shape_pair"][1],
)
out = tf.bitwise.right_shift(input_value1, input_value2)
return [input_value1, input_value2], [out]
def build_inputs(parameters, sess, inputs, outputs):
input_value1 = create_tensor_data(
parameters["input_dtype"], parameters["input_shape_pair"][0]
)
input_value2 = create_tensor_data(
parameters["input_dtype"], parameters["input_shape_pair"][1]
)
return [input_value1, input_value2], sess.run(
outputs, feed_dict=dict(zip(inputs, [input_value1, input_value2]))
)
make_zip_of_tests(
options,
test_parameters,
build_graph,
build_inputs,
expected_tf_failures=6,
)