STT-tensorflow/tensorflow/lite/testing/op_tests/minimum.py
Thai Nguyen ee940c2bea Add 5D support for TFLite Maximum Minimum
PiperOrigin-RevId: 302632680
Change-Id: I1d14cc1afe01888d731e3e68a398f2907e18f174
2020-03-24 03:37:45 -07:00

75 lines
2.6 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 minimum."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
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_minimum_tests(options):
"""Make a set of tests to do minimum."""
test_parameters = [{
"input_dtype": [tf.float32],
"input_shape_1": [[], [3], [1, 100], [4, 2, 3], [5, 224, 224, 3],
[5, 32, 32, 1, 1], [5, 32, 32, 1, 1]],
"input_shape_2": [[], [3], [1, 100], [4, 2, 3], [5, 224, 224, 3],
[5, 32, 32, 1, 1], [5, 32, 32, 1, 3]],
"fully_quantize": [False, True],
}]
def build_graph(parameters):
"""Build the minimum op testing graph."""
input_tensor_1 = tf.compat.v1.placeholder(
dtype=parameters["input_dtype"],
name="input_1",
shape=parameters["input_shape_1"])
input_tensor_2 = tf.compat.v1.placeholder(
dtype=parameters["input_dtype"],
name="input_2",
shape=parameters["input_shape_2"])
out = tf.minimum(input_tensor_1, input_tensor_2)
return [input_tensor_1, input_tensor_2], [out]
def build_inputs(parameters, sess, inputs, outputs):
"""Builds the inputs for the model above."""
values = [
create_tensor_data(
parameters["input_dtype"],
parameters["input_shape_1"],
min_value=-1,
max_value=1),
create_tensor_data(
parameters["input_dtype"],
parameters["input_shape_2"],
min_value=-1,
max_value=1)
]
return values, sess.run(outputs, feed_dict=dict(zip(inputs, values)))
make_zip_of_tests(
options,
test_parameters,
build_graph,
build_inputs,
expected_tf_failures=44)