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tensorflow/api_template.__init__.py
# Lazy-load Keras v2/3. _tf_uses_legacy_keras = ( _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1")) setattr(_current_module, "keras", _KerasLazyLoader(globals())) _module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras") _current_module.__path__ = [_module_dir] + _current_module.__path__ if _tf_uses_legacy_keras:
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ci/official/requirements_updater/BUILD.bazel
extra_args = [ "--allow-unsafe", "-P keras-nightly", "-P tb-nightly", ], requirements_in = "requirements.in", requirements_txt = "requirements_lock_3_9.txt", ) compile_pip_requirements_3_10( name = "requirements_3_10_release", extra_args = [ "--allow-unsafe", "-P keras-nightly", "-P tb-nightly", ],
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ci/official/containers/linux_arm64/devel.usertools/wheel_verification.bats
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tensorflow/api_template_v1.__init__.py
# Lazy-load Keras v1. _tf_uses_legacy_keras = ( _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1")) setattr(_current_module, "keras", _KerasLazyLoader(globals(), mode="v1")) _module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras") _current_module.__path__ = [_module_dir] + _current_module.__path__ if _tf_uses_legacy_keras:
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requirements_lock_3_12.txt
# via # -r requirements.in # keras-nightly idna==3.7 \ --hash=sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc \ --hash=sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0 # via requests jax==0.4.7 \ --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8 # via -r requirements.in keras-nightly==3.0.4.dev2024021403 \
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requirements_lock_3_9.txt
--hash=sha256:f47619d978ab1ae7dfdc4052ea97c636c6263e1f19bd1be0e42c346b98d15ff4 # via # jax # keras-nightly namex==0.0.7 \ --hash=sha256:84ba65bc4d22bd909e3d26bf2ffb4b9529b608cb3f9a4336f776b04204ced69b \ --hash=sha256:8a4f062945f405d77cb66b907f16aa2fd83681945e998be840eb6c4154d40108 # via keras-nightly numpy==1.23.5 ; python_version <= "3.11" \
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requirements_lock_3_10.txt
# via # -r requirements.in # keras-nightly idna==3.7 \ --hash=sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc \ --hash=sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0 # via requests jax==0.4.7 \ --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8 # via -r requirements.in keras-nightly==3.0.4.dev2024021403 \
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RELEASE.md
* Keras 3.0 will be the default Keras version. You may need to update your script to use Keras 3.0. * Please refer to the new Keras documentation for Keras 3.0 (https://keras.io/keras_3). * To continue using Keras 2.0, do the following. * 1. Install tf-keras via pip install tf-keras~=2.16 1. To switch tf.keras to use Keras 2 (tf-keras), set the environment
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ci/official/requirements_updater/requirements.in
typing_extensions == 4.8.0 gast == 0.4.0 termcolor == 2.3.0 wrapt == 1.16.0 tblib == 2.0.0 # Install tensorboard, and keras # Note that here we want the latest version that matches TF major.minor version # Note that we must use nightly here as these are used in nightly jobs # For release jobs, we will pin these on the release branch keras-nightly ~= 3.0.0.dev tb-nightly ~= 2.17.0.a # Test dependencies grpcio >= 1.24.3, < 2.0 portpicker == 1.6.0
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requirements_lock_3_11.txt
# via # -r requirements.in # keras-nightly idna==3.7 \ --hash=sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc \ --hash=sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0 # via requests jax==0.4.7 \ --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8 # via -r requirements.in keras-nightly==3.0.4.dev2024021403 \
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