Add tests for pretrained weights of Keras Applications.
PiperOrigin-RevId: 289376982 Change-Id: I76620361cf0018051e51849856dc6cc3101e0327
This commit is contained in:
Yanhui Liang
TensorFlower Gardener
parent
fbdf6b193f
commit
c25b583371
@ -50,6 +50,205 @@ tf_py_test(
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],
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)
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# Add target for each application module file, to make sure it only
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# runs the test for the application models contained in that
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# application module when it has been modified.
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tf_py_test(
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name = "applications_load_weight_test_resnet",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=resnet"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_resnet_v2",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=resnet_v2"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_vgg16",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=vgg16"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_vgg19",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=vgg19"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_xception",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=xception"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_inception_v3",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=inception_v3"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_inception_resnet_v2",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=inception_resnet_v2"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_mobilenet",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=mobilenet"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_mobilenet_v2",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=mobilenet_v2"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_densenet",
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size = "large",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=densenet"],
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main = "applications_load_weight_test.py",
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shard_count = 3,
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_efficientnet",
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size = "large",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=efficientnet"],
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main = "applications_load_weight_test.py",
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shard_count = 8,
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "applications_load_weight_test_nasnet",
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srcs = ["applications_load_weight_test.py"],
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args = ["--module=nasnet"],
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main = "applications_load_weight_test.py",
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tags = [
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"no_oss", # TODO(b/146940090): fix kokoro error
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"no_pip",
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],
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deps = [
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":applications",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "imagenet_utils_test",
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size = "medium",
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@ -0,0 +1,114 @@
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# Copyright 2020 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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"""Integration tests for Keras applications."""
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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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from absl import flags
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from absl.testing import parameterized
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import numpy as np
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from tensorflow.python.keras.applications import densenet
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from tensorflow.python.keras.applications import efficientnet
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from tensorflow.python.keras.applications import inception_resnet_v2
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from tensorflow.python.keras.applications import inception_v3
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from tensorflow.python.keras.applications import mobilenet
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from tensorflow.python.keras.applications import mobilenet_v2
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from tensorflow.python.keras.applications import nasnet
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from tensorflow.python.keras.applications import resnet
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from tensorflow.python.keras.applications import resnet_v2
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from tensorflow.python.keras.applications import vgg16
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from tensorflow.python.keras.applications import vgg19
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from tensorflow.python.keras.applications import xception
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from tensorflow.python.keras.preprocessing import image
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from tensorflow.python.keras.utils import data_utils
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from tensorflow.python.platform import test
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ARG_TO_MODEL = {
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'resnet': (resnet, [resnet.ResNet50, resnet.ResNet101, resnet.ResNet152]),
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'resnet_v2': (resnet_v2, [resnet_v2.ResNet50V2, resnet_v2.ResNet101V2,
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resnet_v2.ResNet152V2]),
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'vgg16': (vgg16, [vgg16.VGG16]),
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'vgg19': (vgg19, [vgg19.VGG19]),
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'xception': (xception, [xception.Xception]),
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'inception_v3': (inception_v3, [inception_v3.InceptionV3]),
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'inception_resnet_v2': (inception_resnet_v2,
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[inception_resnet_v2.InceptionResNetV2]),
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'mobilenet': (mobilenet, [mobilenet.MobileNet]),
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'mobilenet_v2': (mobilenet_v2, [mobilenet_v2.MobileNetV2]),
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'densenet': (densenet, [densenet.DenseNet121,
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densenet.DenseNet169, densenet.DenseNet201]),
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'nasnet': (nasnet, [nasnet.NASNetMobile, nasnet.NASNetLarge]),
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'efficientnet': (efficientnet,
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[efficientnet.EfficientNetB0, efficientnet.EfficientNetB1,
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efficientnet.EfficientNetB2, efficientnet.EfficientNetB3,
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efficientnet.EfficientNetB4, efficientnet.EfficientNetB5,
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efficientnet.EfficientNetB6, efficientnet.EfficientNetB7])
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}
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TEST_IMAGE_PATH = ('https://storage.googleapis.com/tensorflow/'
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'keras-applications/tests/elephant.jpg')
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_IMAGENET_CLASSES = 1000
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# Add a flag to define which application module file is tested.
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# This is set as an 'arg' in the build target to guarantee that
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# it only triggers the tests of the application models in the module
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# if that module file has been modified.
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FLAGS = flags.FLAGS
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flags.DEFINE_string('module', None,
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'Application module used in this test.')
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def _get_elephant(target_size):
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# For models that don't include a Flatten step,
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# the default is to accept variable-size inputs
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# even when loading ImageNet weights (since it is possible).
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# In this case, default to 299x299.
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if target_size[0] is None:
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target_size = (299, 299)
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test_image = data_utils.get_file('elephant.jpg', TEST_IMAGE_PATH)
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img = image.load_img(test_image, target_size=tuple(target_size))
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x = image.img_to_array(img)
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return np.expand_dims(x, axis=0)
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class ApplicationsLoadWeightTest(test.TestCase, parameterized.TestCase):
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def assertShapeEqual(self, shape1, shape2):
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if len(shape1) != len(shape2):
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raise AssertionError(
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'Shapes are different rank: %s vs %s' % (shape1, shape2))
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if shape1 != shape2:
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raise AssertionError('Shapes differ: %s vs %s' % (shape1, shape2))
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def test_application_pretrained_weights_loading(self):
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app_module = ARG_TO_MODEL[FLAGS.module][0]
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apps = ARG_TO_MODEL[FLAGS.module][1]
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for app in apps:
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model = app(weights='imagenet')
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self.assertShapeEqual(model.output_shape, (None, _IMAGENET_CLASSES))
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x = _get_elephant(model.input_shape[1:3])
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x = app_module.preprocess_input(x)
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preds = model.predict(x)
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names = [p[1] for p in app_module.decode_predictions(preds)[0]]
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# Test correct label is in top 3 (weak correctness test).
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self.assertIn('African_elephant', names[:3])
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if __name__ == '__main__':
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test.main()
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