80 lines
3.1 KiB
Python
80 lines
3.1 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 nearest upsample."""
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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_nearest_upsample_tests(options):
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"""Make a set of tests to do nearest_upsample."""
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# Chose a set of parameters
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test_parameters = [{
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"input_shape": [[1, 10, 10, 64], [3, 8, 32]],
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"scale_n_axis": [([2, 2], [1, 2]), ([3, 4], [1, 2]), ([3], [1])],
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"dtype": [tf.float32, tf.int32],
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}]
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def new_shape_for_upsample(original_shape, scales, axis):
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"""Calculate the input shape & ones shape, also the upsample shape."""
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input_new_shape = []
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ones_new_shape = []
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upsample_new_shape = []
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j = 0
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for i in range(len(original_shape)):
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input_new_shape.append(original_shape[i])
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ones_new_shape.append(1)
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if j < len(scales) and axis[j] == i:
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input_new_shape.append(1)
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ones_new_shape.append(scales[j])
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upsample_new_shape.append(original_shape[i] * scales[j])
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j += 1
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else:
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upsample_new_shape.append(original_shape[i])
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return input_new_shape, ones_new_shape, upsample_new_shape
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def build_graph(parameters):
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"""Build the nearest upsample testing graph."""
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input_shape = parameters["input_shape"]
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input_tensor = tf.compat.v1.placeholder(
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dtype=parameters["dtype"], name="input", shape=input_shape)
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scales, axis = parameters["scale_n_axis"]
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input_new_shape, ones_new_shape, new_shape = new_shape_for_upsample(
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input_shape, scales, axis)
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out = tf.compat.v1.reshape(input_tensor,
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input_new_shape) * tf.compat.v1.ones(
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ones_new_shape, dtype=parameters["dtype"])
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out = tf.compat.v1.reshape(out, new_shape)
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return [input_tensor], [out]
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def build_inputs(parameters, sess, inputs, outputs):
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input_values = create_tensor_data(
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parameters["dtype"],
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parameters["input_shape"],
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min_value=-10,
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max_value=10)
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return [input_values], sess.run(
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outputs, feed_dict=dict(zip(inputs, [input_values])))
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make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
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