103 lines
3.3 KiB
Python
103 lines
3.3 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 concat."""
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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_concat_tests(options):
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"""Make a set of tests to do concatenation."""
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test_parameters = [{
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"base_shape": [[1, 3, 4, 3], [3, 4]],
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"num_tensors": [1, 2, 3, 4, 5, 6],
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"axis": [0, 1, 2, 3, -3, -2, -1],
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"type": [tf.float32, tf.uint8, tf.int32, tf.int64],
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"fully_quantize": [False],
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"quant_16x8": [False],
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"dynamic_range_quantize": [False],
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}, {
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"base_shape": [[1, 3, 4, 3], [3, 4], [2, 3, 4, 3]],
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"num_tensors": [1, 2, 3, 4, 5, 6],
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"axis": [1, 2, 3, -3, -2, -1],
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"type": [tf.float32],
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"fully_quantize": [True],
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"quant_16x8": [False],
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"dynamic_range_quantize": [False],
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}, {
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"base_shape": [[1, 3, 4, 3]],
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"num_tensors": [6],
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"axis": [-1],
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"type": [tf.float32],
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"fully_quantize": [True],
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"quant_16x8": [True],
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"dynamic_range_quantize": [False],
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}, {
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"base_shape": [[1, 3, 4, 3]],
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"num_tensors": [6],
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"axis": [1],
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"type": [tf.float32],
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"fully_quantize": [False],
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"quant_16x8": [False],
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"dynamic_range_quantize": [True],
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}]
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def get_shape(parameters, delta):
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"""Return a tweaked version of 'base_shape'."""
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axis = parameters["axis"]
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shape = parameters["base_shape"][:]
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if axis < 0:
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axis += len(shape)
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if axis < len(shape):
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shape[axis] += delta
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return shape
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def build_graph(parameters):
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all_tensors = []
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for n in range(0, parameters["num_tensors"]):
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input_tensor = tf.compat.v1.placeholder(
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dtype=parameters["type"],
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name=("input%d" % n),
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shape=get_shape(parameters, n))
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all_tensors.append(input_tensor)
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out = tf.concat(all_tensors, parameters["axis"])
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return all_tensors, [out]
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def build_inputs(parameters, sess, inputs, outputs):
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all_values = []
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for n in range(0, parameters["num_tensors"]):
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input_values = create_tensor_data(
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parameters["type"],
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get_shape(parameters, n),
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min_value=-1,
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max_value=1)
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all_values.append(input_values)
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return all_values, sess.run(
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outputs, feed_dict=dict(zip(inputs, all_values)))
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make_zip_of_tests(
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options,
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test_parameters,
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build_graph,
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build_inputs,
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expected_tf_failures=75)
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