77 lines
2.9 KiB
Python
77 lines
2.9 KiB
Python
# Copyright 2019 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 scatter_nd."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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import tensorflow.compat.v1 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 make_zip_of_tests
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from tensorflow.lite.testing.zip_test_utils import register_make_test_function
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@register_make_test_function()
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def make_scatter_nd_tests(options):
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"""Make a set of tests to do scatter_nd."""
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test_parameters = [{
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"indices_dtype": [tf.int32],
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"indices_shape": [[4, 1]],
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"indices_value": [[[4], [3], [1], [7]]],
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"updates_dtype": [tf.int32, tf.int64, tf.float32],
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"updates_shape": [[4]],
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"shape_dtype": [tf.int32],
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"shape_shape": [[1]],
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"shape_value": [[8]]
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}, {
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"indices_dtype": [tf.int32],
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"indices_shape": [[4, 2]],
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"indices_value": [[[0, 0], [1, 0], [0, 2], [1, 2]]],
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"updates_dtype": [tf.int32, tf.int64, tf.float32],
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"updates_shape": [[4, 5]],
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"shape_dtype": [tf.int32],
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"shape_shape": [[3]],
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"shape_value": [[2, 3, 5]]
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}]
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def build_graph(parameters):
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"""Build the scatter_nd op testing graph."""
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indices = tf.compat.v1.placeholder(
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dtype=parameters["indices_dtype"],
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name="indices",
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shape=parameters["indices_shape"])
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updates = tf.compat.v1.placeholder(
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dtype=parameters["updates_dtype"],
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name="updates",
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shape=parameters["updates_shape"])
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shape = tf.compat.v1.placeholder(
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dtype=parameters["shape_dtype"],
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name="shape",
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shape=parameters["shape_shape"])
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out = tf.scatter_nd(indices, updates, shape)
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return [indices, updates, shape], [out]
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def build_inputs(parameters, sess, inputs, outputs):
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indices = np.array(parameters["indices_value"])
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updates = create_tensor_data(parameters["updates_dtype"],
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parameters["updates_shape"])
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shape = np.array(parameters["shape_value"])
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return [indices, updates, shape], sess.run(
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outputs, feed_dict=dict(zip(inputs, [indices, updates, shape])))
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make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
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