wehub-resource-sync
130 lines
4.4 KiB
Python
130 lines
4.4 KiB
Python
# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Test configs for roll."""
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import numpy as np
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import tensorflow as tf
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from tensorflow.lite.testing.zip_test_utils import create_tensor_data
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from tensorflow.lite.testing.zip_test_utils import ExtraConvertOptions
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from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
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from tensorflow.lite.testing.zip_test_utils import register_make_test_function
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test_parameters = [
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# Scalar axis.
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{
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"input_dtype": [tf.float32, tf.int32],
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"input_shape": [[2, 4, 5], [3, 8, 4]],
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"shift": [1, -3, 5],
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"axis": [0, 1, 2],
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},
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# 1-D axis.
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{
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"input_dtype": [tf.float32, tf.int32],
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"input_shape": [[2, 4, 5], [3, 8, 4]],
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"shift": [[1], [-3], [5]],
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"axis": [[0], [1], [2]],
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},
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# Multiple axis.
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{
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"input_dtype": [tf.float32, tf.int32],
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"input_shape": [[2, 4, 5], [3, 8, 4]],
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"shift": [[1, 3, 2], [3, -6, 5], [-5, 7, 8]],
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"axis": [[0, 1, 2]],
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},
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# Duplicate axis.
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{
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"input_dtype": [tf.float32],
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"input_shape": [[2, 4, 5], [3, 8, 4]],
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"shift": [[1, 3, -2]],
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"axis": [[0, 1, 1]],
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},
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]
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@register_make_test_function()
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def make_roll_with_constant_tests(options):
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"""Make a set of tests to do roll with constant shift and axis."""
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def build_graph(parameters):
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input_value = tf.compat.v1.placeholder(
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dtype=parameters["input_dtype"],
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name="input",
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shape=parameters["input_shape"])
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outs = tf.roll(
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input_value, shift=parameters["shift"], axis=parameters["axis"])
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return [input_value], [outs]
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def build_inputs(parameters, sess, inputs, outputs):
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input_value = create_tensor_data(parameters["input_dtype"],
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parameters["input_shape"])
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return [input_value], sess.run(
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outputs, feed_dict=dict(zip(inputs, [input_value])))
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make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
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@register_make_test_function()
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def make_roll_tests(options):
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"""Make a set of tests to do roll."""
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ext_test_parameters = test_parameters + [
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# Scalar axis.
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{
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"input_dtype": [tf.float32, tf.int32],
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"input_shape": [[None, 8, 4]],
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"shift": [-3, 5],
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"axis": [1, 2],
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}
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]
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def set_dynamic_shape(shape):
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return [4 if x is None else x for x in shape]
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def get_shape(param):
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if np.isscalar(param):
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return []
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return [len(param)]
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def get_value(param, dtype):
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if np.isscalar(param):
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return np.dtype(dtype).type(param)
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return np.array(param).astype(dtype)
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def build_graph(parameters):
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input_tensor = tf.compat.v1.placeholder(
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dtype=parameters["input_dtype"],
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name="input",
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shape=parameters["input_shape"])
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shift_tensor = tf.compat.v1.placeholder(
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dtype=tf.int64, name="shift", shape=get_shape(parameters["shift"]))
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axis_tensor = tf.compat.v1.placeholder(
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dtype=tf.int64, name="axis", shape=get_shape(parameters["axis"]))
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outs = tf.roll(input_tensor, shift_tensor, axis_tensor)
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return [input_tensor, shift_tensor, axis_tensor], [outs]
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def build_inputs(parameters, sess, inputs, outputs):
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input_value = create_tensor_data(
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parameters["input_dtype"], set_dynamic_shape(parameters["input_shape"]))
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shift_value = get_value(parameters["shift"], np.int64)
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axis_value = get_value(parameters["axis"], np.int64)
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return [input_value, shift_value, axis_value], sess.run(
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outputs,
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feed_dict=dict(zip(inputs, [input_value, shift_value, axis_value])))
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extra_convert_options = ExtraConvertOptions()
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extra_convert_options.allow_custom_ops = True
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make_zip_of_tests(options, ext_test_parameters, build_graph, build_inputs,
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extra_convert_options)
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