tf_upgrade_v2.py --infile foo.py --outfile bar.py
  tf_upgrade_v2.py --infile foo.ipynb --outfile bar.ipynb
  tf_upgrade_v2.py --intree ~/code/old --outtree ~/code/new

options:
  -h, --help            show this help message and exit
  --infile INPUT_FILE   If converting a single file, the name of the file to
                        convert
  --outfile OUTPUT_FILE
                        If converting a single file, the output filename.
  --intree INPUT_TREE   If converting a whole tree of files, the directory to
                        read from (relative or absolute).
  --outtree OUTPUT_TREE
                        If converting a whole tree of files, the output
                        directory (relative or absolute).
  --copyotherfiles COPY_OTHER_FILES
                        If converting a whole tree of files, whether to copy
                        the other files.
  --inplace             If converting a set of files, whether to allow the
                        conversion to be performed on the input files.
  --no_import_rename    Not to rename import to compat.v2 explicitly.
  --no_upgrade_compat_v1_import
                        If specified, don't upgrade explicit imports of
                        `tensorflow.compat.v1 as tf` to the v2 APIs.
                        Otherwise, explicit imports of the form
                        `tensorflow.compat.v1 as tf` will be upgraded.
  --reportfile REPORT_FILENAME
                        The name of the file where the report log is
                        stored.(default: report.txt)
  --mode {DEFAULT,SAFETY}
                        Upgrade script mode. Supported modes: DEFAULT: Perform
                        only straightforward conversions to upgrade to 2.0. In
                        more difficult cases, switch to use compat.v1. SAFETY:
                        Keep 1.* code intact and import compat.v1 module.
  --print_all           Print full log to stdout instead of just printing
                        errors
2024-12-14 03:02:59.475439: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE3 SSE4.1 SSE4.2 AVX AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
usage: tflite_convert [-h] --output_file OUTPUT_FILE
                      [--saved_model_dir SAVED_MODEL_DIR | --keras_model_file KERAS_MODEL_FILE]
                      [--saved_model_tag_set SAVED_MODEL_TAG_SET]
                      [--saved_model_signature_key SAVED_MODEL_SIGNATURE_KEY]
                      [--enable_v1_converter]
                      [--experimental_new_converter [EXPERIMENTAL_NEW_CONVERTER]]
                      [--experimental_new_quantizer [EXPERIMENTAL_NEW_QUANTIZER]]

Command line tool to run TensorFlow Lite Converter.

options:
  -h, --help            show this help message and exit
  --output_file OUTPUT_FILE
                        Full filepath of the output file.
  --saved_model_dir SAVED_MODEL_DIR
                        Full path of the directory containing the SavedModel.
  --keras_model_file KERAS_MODEL_FILE
                        Full filepath of HDF5 file containing tf.Keras model.
  --saved_model_tag_set SAVED_MODEL_TAG_SET
                        Comma-separated set of tags identifying the
                        MetaGraphDef within the SavedModel to analyze. All
                        tags must be present. In order to pass in an empty tag
                        set, pass in "". (default "serve")
  --saved_model_signature_key SAVED_MODEL_SIGNATURE_KEY
                        Key identifying the SignatureDef containing inputs and
                        outputs. (default DEFAULT_SERVING_SIGNATURE_DEF_KEY)
  --enable_v1_converter
                        Enables the TensorFlow V1 converter in 2.0
  --experimental_new_converter [EXPERIMENTAL_NEW_CONVERTER]
                        Experimental flag, subject to change. Enables MLIR-
                        based conversion instead of TOCO conversion. (default
                        True)
  --experimental_new_quantizer [EXPERIMENTAL_NEW_QUANTIZER]
                        Experimental flag, subject to change. Enables MLIR-
                        based quantizer instead of flatbuffer conversion.
                        (default True)
2024-12-14 03:03:01.581797: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE3 SSE4.1 SSE4.2 AVX AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
usage: toco [-h] --output_file OUTPUT_FILE
            [--saved_model_dir SAVED_MODEL_DIR | --keras_model_file KERAS_MODEL_FILE]
            [--saved_model_tag_set SAVED_MODEL_TAG_SET]
            [--saved_model_signature_key SAVED_MODEL_SIGNATURE_KEY]
            [--enable_v1_converter]
            [--experimental_new_converter [EXPERIMENTAL_NEW_CONVERTER]]
            [--experimental_new_quantizer [EXPERIMENTAL_NEW_QUANTIZER]]

Command line tool to run TensorFlow Lite Converter.

options:
  -h, --help            show this help message and exit
  --output_file OUTPUT_FILE
                        Full filepath of the output file.
  --saved_model_dir SAVED_MODEL_DIR
                        Full path of the directory containing the SavedModel.
  --keras_model_file KERAS_MODEL_FILE
                        Full filepath of HDF5 file containing tf.Keras model.
  --saved_model_tag_set SAVED_MODEL_TAG_SET
                        Comma-separated set of tags identifying the
                        MetaGraphDef within the SavedModel to analyze. All
                        tags must be present. In order to pass in an empty tag
                        set, pass in "". (default "serve")
  --saved_model_signature_key SAVED_MODEL_SIGNATURE_KEY
                        Key identifying the SignatureDef containing inputs and
                        outputs. (default DEFAULT_SERVING_SIGNATURE_DEF_KEY)
  --enable_v1_converter
                        Enables the TensorFlow V1 converter in 2.0
  --experimental_new_converter [EXPERIMENTAL_NEW_CONVERTER]
                        Experimental flag, subject to change. Enables MLIR-
                        based conversion instead of TOCO conversion. (default
                        True)
  --experimental_new_quantizer [EXPERIMENTAL_NEW_QUANTIZER]
                        Experimental flag, subject to change. Enables MLIR-
                        based quantizer instead of flatbuffer conversion.
                        (default True)
2024-12-14 03:03:03.678434: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE3 SSE4.1 SSE4.2 AVX AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
usage: toco_from_protos [-h]
                        model_proto_file toco_proto_file model_input_file
                        model_output_file

Invoke toco using protos as input.

positional arguments:
  model_proto_file   File containing serialized proto that describes the
                     model.
  toco_proto_file    File containing serialized proto describing how TOCO
                     should run.
  model_input_file   Input model is read from this file.
  model_output_file  Result of applying TOCO conversion is written here.

options:
  -h, --help         show this help message and exit
running test pipeline for subpackage tensorflow-dev
building test workspace in: '/tmp/melange-guest-1240239911-tensorflow-dev' with apko
2024/12/14 03:03:05 [DEBUG] GET https://apk.cgr.dev/wolfi-presubmit/87427d269d6a3d9314e07bd6eb852ad9c17c9a86/apk-configuration
2024/12/14 03:03:05 [DEBUG] GET https://packages.wolfi.dev/os/apk-configuration
setting apk repositories: [https://apk.cgr.dev/wolfi-presubmit/87427d269d6a3d9314e07bd6eb852ad9c17c9a86 https://packages.wolfi.dev/os]
image configuration:
  contents:
    build repositories: []
    runtime repositories: []
    keyring:      []
    packages:     [tensorflow-dev pkgconf]
installing ca-certificates-bundle (20241010-r2)
installing wolfi-baselayout (20230201-r15)
installing glibc (2.40-r3)
installing ld-linux (2.40-r3)
installing libgcc (14.2.0-r6)
installing glibc-locale-posix (2.40-r3)
installing pkgconf (2.3.0-r1)
installing icu-data-full (75.1-r5)
installing libstdc++ (14.2.0-r6)
installing icu-libs (75.1-r5)
installing giflib (5.2.2-r4)
installing libjpeg-turbo (3.1.0-r0)
installing zlib (1.3.1-r4)
installing libpng (1.6.44-r3)
installing libcrypto3 (3.4.0-r4)
installing libssl3 (3.4.0-r4)
installing libunistring (1.3-r1)
installing libidn2 (2.3.7-r3)
installing libpsl (0.21.5-r4)
installing libbrotlicommon1 (1.1.0-r4)
installing libbrotlidec1 (1.1.0-r4)
installing krb5-conf (1.0-r3)
installing libverto (0.3.2-r4)
installing keyutils-libs (1.6.3-r5)
installing libcom_err (1.47.1-r1)
installing krb5-libs (1.21.3-r2)
installing ncurses-terminfo-base (6.5_p20241006-r4)
installing ncurses (6.5_p20241006-r4)
installing readline (8.2.13-r1)
installing sqlite-libs (3.47.2-r0)
installing libxcrypt (4.4.36-r8)
installing libcrypt1 (2.40-r3)
installing heimdal-libs (7.8.0-r7)
installing gdbm (1.24-r1)
installing cyrus-sasl (2.1.28-r5)
installing libevent (2.1.12-r6)
installing libldap (2.6.9-r0)
installing libnghttp2-14 (1.64.0-r1)
installing libcurl-openssl4 (8.11.1-r0)
installing tensorflow-core (2.18.0-r4)
installing tensorflow-dev (2.18.0-r4)
installing wolfi-keys (1-r8)
installing apk-tools (2.14.4-r1)
installing busybox (1.37.0-r0)
installing wolfi-base (1-r6)
built image layer tarball as /tmp/apko-temp-1433478881/apko-x86_64.tar.gz
using /tmp/apko-temp-1433478881/apko-x86_64.tar.gz for image layer
OCI layer digest: sha256:c315b1f283e0a21b7bdf53e174817b46613e1fa31ae4852de91e0c67d478ea64
OCI layer diffID: sha256:5d7bd7e733f162d239f9df385f72893340ccb6e3b46676dd2403f59746a6b307
saving OCI image locally: apko.local/cache:9206ab4cb5eaf12bf5b6c5fa6ce88b3d75a1206b3084de81de368ed5de2a088a

experimental_new_quantizer [EXPERIMENTAL_NEW_QUANTIZER]
                        Experimental flag, subject to change. Enables MLIR-
                        based quantizer instead of flatbuffer conversion.
                        (default True)
usage: toco_from_protos [-h]
                        model_proto_file toco_proto_file model_input_file
                        model_output_file

Invoke toco using protos as input.

positional arguments:
  model_proto_file   File containing serialized proto that describes the
                     model.
  toco_proto_file    File containing serialized proto describing how TOCO
                     should run.
  model_input_file   Input model is read from this file.
  model_output_file  Result of applying TOCO conversion is written here.

options:
  -h, --help         show this help message and exit
running test pipeline for subpackage tensorflow-dev
building test workspace in: '/tmp/melange-guest-1535563660-tensorflow-dev' with apko
2024/12/14 03:01:25 [DEBUG] GET https://apk.cgr.dev/wolfi-presubmit/87427d269d6a3d9314e07bd6eb852ad9c17c9a86/apk-configuration
2024/12/14 03:01:26 [DEBUG] GET https://packages.wolfi.dev/os/apk-configuration
setting apk repositories: [https://apk.cgr.dev/wolfi-presubmit/87427d269d6a3d9314e07bd6eb852ad9c17c9a86 https://packages.wolfi.dev/os]
image configuration:
  contents:
    build repositories: []
    runtime repositories: []
    keyring:      []
    packages:     [tensorflow-dev pkgconf]
installing ca-certificates-bundle (20241010-r2)
installing wolfi-baselayout (20230201-r15)
installing glibc (2.40-r3)
installing libgcc (14.2.0-r6)
installing ld-linux (2.40-r3)
installing glibc-locale-posix (2.40-r3)
installing pkgconf (2.3.0-r1)
installing icu-data-full (75.1-r5)
installing libstdc++ (14.2.0-r6)
installing icu-libs (75.1-r5)
installing giflib (5.2.2-r4)
installing libjpeg-turbo (3.1.0-r0)
installing zlib (1.3.1-r4)
installing libpng (1.6.44-r3)
installing libcrypto3 (3.4.0-r4)
installing libssl3 (3.4.0-r4)
installing libunistring (1.3-r1)
installing libidn2 (2.3.7-r3)
installing libpsl (0.21.5-r4)
installing libbrotlicommon1 (1.1.0-r4)
installing libbrotlidec1 (1.1.0-r4)
installing krb5-conf (1.0-r3)
installing libverto (0.3.2-r4)
installing keyutils-libs (1.6.3-r5)
installing libcom_err (1.47.1-r1)
installing krb5-libs (1.21.3-r2)
installing ncurses-terminfo-base (6.5_p20241006-r4)
installing ncurses (6.5_p20241006-r4)
installing readline (8.2.13-r1)
installing sqlite-libs (3.47.2-r0)
installing libxcrypt (4.4.36-r8)
installing libcrypt1 (2.40-r3)
installing heimdal-libs (7.8.0-r7)
installing gdbm (1.24-r1)
installing cyrus-sasl (2.1.28-r5)
installing libevent (2.1.12-r6)
installing libldap (2.6.9-r0)
installing libnghttp2-14 (1.64.0-r1)
installing libcurl-openssl4 (8.11.1-r0)
installing tensorflow-core (2.18.0-r4)
installing tensorflow-dev (2.18.0-r4)
installing wolfi-keys (1-r8)
installing apk-tools (2.14.4-r1)
installing busybox (1.37.0-r0)
installing wolfi-base (1-r6)
built image layer tarball as /tmp/apko-temp-663162370/apko-aarch64.tar.gz
using /tmp/apko-temp-663162370/apko-aarch64.tar.gz for image layer
OCI layer digest: sha256:dc985e9bb8c124a498ac81d6ec917d84740a0d991e6aa03bf4ca3a023433d572
OCI layer diffID: sha256:6904e6934032b3f1cdf16b412d739ccc3fe5ed9fdecb3b3600083b9733fb6558
saving OCI image locally: apko.local/cache:cc802870416f82be6effc6808829ef6d1ed0de761893649efd5ab19267666260
skipping local domain tagging apko.local/cache:cc802870416f82be6effc6808829ef6d1ed0de761893649efd5ab19267666260 as index.docker.io/library/melange:latest
ImgRef = apko.local/cache:cc802870416f82be6effc6808829ef6d1ed0de761893649efd5ab19267666260
time="2024-12-14T03:01:39.563531299Z" level=info msg="connecting to shim b2d769017b3ab1d7a0506af17ff97d6e8d62e224f7def1101c14b78faee342ab" address="unix:///run/containerd/s/3346646dd725f40d4a86122aff10e972199023f9dbc6abe6ce13bcd07ca9bb3a" namespace=moby protocol=ttrpc version=3
running step "test/pkgconf"
running step "pkgconf build dependency check"
2.18.0
WARNING: opening from cache https://apk.cgr.dev/wolfi-presubmit/87427d269d6a3d9314e07bd6eb852ad9c17c9a86: No such file or directory
WARNING: opening from cache https://packages.wolfi.dev/os: No such file or directory
-ltensorflow -ltensorflow_framework
-I/usr/include/tensorflow
2.18.0
-ltensorflow_cc -ltensorflow_framework
-I/usr/include/tensorflow
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