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chore: import upstream snapshot with attribution
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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 exp."""
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_exp_tests(options):
"""Make a set of tests to do exp."""
test_parameters = [
{
"input_dtype": [tf.float32],
"input_shape": [[], [3], [1, 100], [4, 2, 3], [5, 224, 224, 3]],
"input_range": [(-100, 9)],
},
{
"input_dtype": [tf.float32],
"input_shape": [[], [3], [1, 100], [4, 2, 3], [5, 224, 224, 3]],
"input_range": [(-2, 2)],
"fully_quantize": [True],
"quant_16x8": [False, True],
},
]
def build_graph(parameters):
"""Build the exp op testing graph."""
input_tensor = tf.compat.v1.placeholder(
dtype=parameters["input_dtype"],
name="input",
shape=parameters["input_shape"])
out = tf.exp(input_tensor)
return [input_tensor], [out]
def build_inputs(parameters, sess, inputs, outputs):
min_value, max_value = parameters["input_range"]
values = [
create_tensor_data(
parameters["input_dtype"],
parameters["input_shape"],
min_value=min_value,
max_value=max_value,
)
]
return values, sess.run(outputs, feed_dict=dict(zip(inputs, values)))
make_zip_of_tests(options, test_parameters, build_graph, build_inputs)