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Replace HDF5 with TF format

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Aurélien Geron 2022-09-12 11:47:36 +12:00
parent ace7a972b9
commit 7a551f5fb1
2 changed files with 10 additions and 10 deletions
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4
15_processing_sequences_using_rnns_and_cnns.ipynb
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@ -3988,7 +3988,7 @@
} }
], ],
"source": [ "source": [
"model.save(\"my_sketchrnn\")" "model.save(\"my_sketchrnn\", save_format=\"tf\")"
] ]
}, },
{ {
@ -4638,7 +4638,7 @@
} }
], ],
"source": [ "source": [
"model.save(\"my_bach_model.h5\")\n", "model.save(\"my_bach_model\", save_format=\"tf\")\n",
"model.evaluate(test_set)" "model.evaluate(test_set)"
] ]
}, },

16
19_training_and_deploying_at_scale.ipynb
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@ -229,7 +229,7 @@
"model_name = \"my_mnist_model\"\n", "model_name = \"my_mnist_model\"\n",
"model_version = \"0001\"\n", "model_version = \"0001\"\n",
"model_path = Path(model_name) / model_version\n", "model_path = Path(model_name) / model_version\n",
"model.save(model_path)" "model.save(model_path, save_format=\"tf\")"
] ]
}, },
{ {
@ -706,7 +706,7 @@
"source": [ "source": [
"model_version = \"0002\"\n", "model_version = \"0002\"\n",
"model_path = Path(model_name) / model_version\n", "model_path = Path(model_name) / model_version\n",
"model.save(model_path)" "model.save(model_path, save_format=\"tf\")"
] ]
}, },
{ {
@ -1830,7 +1830,7 @@
"source": [ "source": [
"# extra code – shows that saving a model does not preserve its distribution\n", "# extra code – shows that saving a model does not preserve its distribution\n",
"# strategy\n", "# strategy\n",
"model.save(\"my_mirrored_model\")\n", "model.save(\"my_mirrored_model\", save_format=\"tf\")\n",
"model = tf.keras.models.load_model(\"my_mirrored_model\")\n", "model = tf.keras.models.load_model(\"my_mirrored_model\")\n",
"type(model.weights[0])" "type(model.weights[0])"
] ]
@ -2151,10 +2151,10 @@
"model.fit(X_train, y_train, validation_data=(X_valid, y_valid), epochs=10)\n", "model.fit(X_train, y_train, validation_data=(X_valid, y_valid), epochs=10)\n",
"\n", "\n",
"if resolver.task_id == 0: # the chief saves the model to the right location\n", "if resolver.task_id == 0: # the chief saves the model to the right location\n",
" model.save(\"my_mnist_multiworker_model\")\n", " model.save(\"my_mnist_multiworker_model\", save_format=\"tf\")\n",
"else:\n", "else:\n",
" tmpdir = tempfile.mkdtemp() # other workers save to a temporary directory\n", " tmpdir = tempfile.mkdtemp() # other workers save to a temporary directory\n",
" model.save(tmpdir)\n", " model.save(tmpdir, save_format=\"tf\")\n",
" tf.io.gfile.rmtree(tmpdir) # and we can delete this directory at the end!" " tf.io.gfile.rmtree(tmpdir) # and we can delete this directory at the end!"
] ]
}, },
@ -2319,7 +2319,7 @@
"\n", "\n",
"model.fit(X_train, y_train, validation_data=(X_valid, y_valid), epochs=10,\n", "model.fit(X_train, y_train, validation_data=(X_valid, y_valid), epochs=10,\n",
" callbacks=callbacks)\n", " callbacks=callbacks)\n",
"model.save(model_dir)" "model.save(model_dir, save_format=\"tf\")"
] ]
}, },
{ {
@ -2471,7 +2471,7 @@
"model = build_model(args)\n", "model = build_model(args)\n",
"history = model.fit(X_train, y_train, validation_data=(X_valid, y_valid),\n", "history = model.fit(X_train, y_train, validation_data=(X_valid, y_valid),\n",
" epochs=10, callbacks=callbacks)\n", " epochs=10, callbacks=callbacks)\n",
"model.save(model_dir) # extra code\n", "model.save(model_dir, save_format=\"tf\") # extra code\n",
"\n", "\n",
"import hypertune\n", "import hypertune\n",
"\n", "\n",
@ -2771,7 +2771,7 @@
"if tuner_id == \"chief\":\n", "if tuner_id == \"chief\":\n",
" best_hp = hyperband_tuner.get_best_hyperparameters()[0]\n", " best_hp = hyperband_tuner.get_best_hyperparameters()[0]\n",
" best_model = hyperband_tuner.hypermodel.build(best_hp)\n", " best_model = hyperband_tuner.hypermodel.build(best_hp)\n",
" best_model.save(os.getenv(\"AIP_MODEL_DIR\"))" " best_model.save(os.getenv(\"AIP_MODEL_DIR\"), save_format=\"tf\")"
] ]
}, },
{ {