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tensorflow/cc/saved_model/image_format/README.md
If you are a TensorFlow Python user, you can try this format by setting the `experimental_image_format` option: ``` tf.savedmodel.save( model, path, options=tf.saved_model.SaveOptions(experimental_image_format=True) ) ``` When this option is enabled, exported SavedModels with proto size > 2GB will automatically save with the new format (`.cpb` instead of `.pb`). <!-- **Compatibility** -->
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Aug 29 22:11:19 UTC 2023 - 674 bytes - Viewed (0) -
tensorflow/cc/saved_model/testdata/generate_chunked_models.py
root.get_c = def_function.function(lambda: root.c) signatures = root.get_c.get_concrete_function() save.save(root, non_chunked_dir, signatures=signatures, options=save_options.SaveOptions(experimental_image_format=False)) def generate_chunked_model(non_chunked_dir: str, chunked_dir: str): saved_model = loader_impl.parse_saved_model(non_chunked_dir)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 08 21:43:11 UTC 2023 - 2.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/debuginfo/saved_model_error.py
"""Save a saved model with unsupported ops, and then load and convert it.""" # saved the model test_model = TestModule() saved_model_path = '/tmp/test.saved_model' save_options = tf.saved_model.SaveOptions(save_debug_info=True) tf.saved_model.save(test_model, saved_model_path, options=save_options) # load the model and convert converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_path)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 28 21:37:05 UTC 2021 - 2.8K bytes - Viewed (0) -
tensorflow/cc/saved_model/testdata/generate_saved_models.py
if not module_ctor: print("Expected ModuleName to be one of:", MODULE_CTORS.keys()) return 2 os.makedirs(export_path) tf_module = module_ctor() if version == 2: options = save_options.SaveOptions(save_debug_info=True) saved_model.save(tf_module, export_path, options=options) else: builder = saved_model.builder.SavedModelBuilder(export_path) builder.add_meta_graph_and_variables(tf_module, ["serve"])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Sep 18 18:06:18 UTC 2023 - 4.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/common.py
if FLAGS.save_model_path: save_model_path = FLAGS.save_model_path else: save_model_path = tempfile.mkdtemp(suffix='.saved_model') save_options = tf.saved_model.SaveOptions(save_debug_info=show_debug_info) tf.saved_model.save( create_module_fn(), save_model_path, options=save_options ) logging.info('Saved model to: %s', save_model_path)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 02 23:49:27 UTC 2023 - 4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
out = activation_fn(out) return {'output': out} model = ConvModel() save_options = None if has_func_alias: save_options = tensorflow.saved_model.SaveOptions( function_aliases={FUNC_ALIAS: model.conv2d} ) saved_model_save.save( model, saved_model_path, signatures=model.conv2d.get_concrete_function(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 18.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
input_shape=(1, 3, 4, 3), filter_shape=(2, 3, 3, 2) ) signatures = { 'serving_default': model.conv.get_concrete_function(), } save_opts = save_options.SaveOptions( function_aliases={'conv_func': model.conv} ) saved_model_save.save( model, self._input_saved_model_path, signatures, save_opts )
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 235.6K bytes - Viewed (0) -
RELEASE.md
* `tf.train.CheckpointOptions` * Added `experimental_skip_slot_variables` (a boolean option) to skip restoring of optimizer slot variables in a checkpoint. * `tf.saved_model.SaveOptions` * `SaveOptions` now takes a new argument called `experimental_debug_stripper`. When enabled, this strips the debug nodes from both the node defs and the function defs of the graph. Note that
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0)