tensorflow/lite/testing/op_tests/random_uniform.py
# Copyright 2021 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 random_uniform."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
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_random_uniform_tests(options):
"""Make a set of tests to do random_uniform."""
test_parameters = [{
"input_shape": [[1]],
"input_dtype": [tf.int32],
"shape": [[10]],
"seed": [None, 0, 1234],
"seed2": [0, 5678],
"dtype": [tf.float32],
}, {
"input_shape": [[3]],
"input_dtype": [tf.int32],
"shape": [[2, 3, 4]],
"seed": [0, 1234],
"seed2": [None, 0, 5678],
"dtype": [tf.float32],
}]
def build_graph(parameters):
"""Build the op testing graph."""
tf.compat.v1.set_random_seed(seed=parameters["seed"])
input_value = tf.compat.v1.placeholder(
name="shape",
shape=parameters["input_shape"],
dtype=parameters["input_dtype"])
out = tf.random.uniform(
shape=input_value, dtype=parameters["dtype"], seed=parameters["seed2"])
return [input_value], [out]
def build_inputs(parameters, sess, inputs, outputs):
input_value = create_tensor_data(
parameters["input_dtype"],
parameters["input_shape"],
min_value=1,
max_value=10)
return [input_value], sess.run(
outputs, feed_dict=dict(zip(inputs, [input_value])))
make_zip_of_tests(options, test_parameters, build_graph, build_inputs)