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chore: import upstream snapshot with attribution
2026-07-13 12:14:16 +08:00

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Python

# Copyright 2020 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 rfft2d."""
import tensorflow as tf
from tensorflow.lite.testing.zip_test_utils import create_tensor_data
from tensorflow.lite.testing.zip_test_utils import ExtraConvertOptions
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_rfft_tests(options):
"""Make a set of tests to do rfft."""
test_parameters = [{
"input_dtype": [tf.float32],
"input_shape": [[8], [8, 8], [3, 8, 8], [3, 8]],
"fft_length": [None, [4], [8], [16]]
}]
def build_graph(parameters):
input_value = tf.compat.v1.placeholder(
dtype=parameters["input_dtype"],
name="input",
shape=parameters["input_shape"])
outs = tf.signal.rfft(input_value, fft_length=parameters["fft_length"])
return [input_value], [outs]
def build_inputs(parameters, sess, inputs, outputs):
input_value = create_tensor_data(parameters["input_dtype"],
parameters["input_shape"])
return [input_value], sess.run(
outputs, feed_dict=dict(zip(inputs, [input_value])))
extra_convert_options = ExtraConvertOptions()
make_zip_of_tests(options, test_parameters, build_graph, build_inputs,
extra_convert_options)