61 lines
2.3 KiB
Python
61 lines
2.3 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 embedding_lookup."""
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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 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_embedding_lookup_tests(options):
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"""Make a set of tests to do gather."""
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test_parameters = [
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{
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"params_dtype": [tf.float32],
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"params_shape": [[10], [10, 10]],
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"ids_dtype": [tf.int32],
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"ids_shape": [[3], [5]],
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},
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]
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def build_graph(parameters):
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"""Build the gather op testing graph."""
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params = tf.compat.v1.placeholder(
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dtype=parameters["params_dtype"],
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name="params",
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shape=parameters["params_shape"])
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ids = tf.compat.v1.placeholder(
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dtype=parameters["ids_dtype"],
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name="ids",
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shape=parameters["ids_shape"])
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out = tf.nn.embedding_lookup(params, ids)
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return [params, ids], [out]
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def build_inputs(parameters, sess, inputs, outputs):
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params = create_tensor_data(parameters["params_dtype"],
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parameters["params_shape"])
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ids = create_tensor_data(parameters["ids_dtype"], parameters["ids_shape"],
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0, parameters["params_shape"][0] - 1)
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return [params, ids], sess.run(
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outputs, feed_dict=dict(zip(inputs, [params, ids])))
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make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
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