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Adding File naming capability to from_saved_model and from_keras_model. #375

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Merged
merged 16 commits into from
Dec 13, 2019
Merged

Adding File naming capability to from_saved_model and from_keras_model. #375

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f0aedda
Firebase ML Kit Modify Operation Handling to not require a name for D…
ifielker Nov 28, 2019
8939ed6
fixed lint
ifielker Nov 28, 2019
7078cb6
Adding support for TensorFlow 2.x
ifielker Dec 2, 2019
d88a66b
fix typo
ifielker Dec 2, 2019
8b5a6b3
remove extraneous @type from operations
ifielker Dec 2, 2019
7ee369d
send updateMask in query parameter
ifielker Dec 4, 2019
d1a9933
send list filters etc in query parameters
ifielker Dec 4, 2019
68ebe77
fix typo
ifielker Dec 4, 2019
5633b9f
fix typo
ifielker Dec 4, 2019
d715628
fix typo
ifielker Dec 4, 2019
b63a4fe
urlEncode filter string
ifielker Dec 4, 2019
71e6705
adding optional file names to conversion functions (start)
ifielker Dec 5, 2019
6dc6d0d
merged
ifielker Dec 13, 2019
d24e742
adding File naming capability for ModelSource
ifielker Dec 13, 2019
0233bfa
fixed lint
ifielker Dec 13, 2019
7230667
fixed file descriptor leak
ifielker Dec 13, 2019
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20 changes: 12 additions & 8 deletions firebase_admin/ml.py
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Original file line number Diff line number Diff line change
Expand Up @@ -524,11 +524,13 @@ def _tf_convert_from_keras_model(keras_model):
return converter.convert()

@classmethod
def from_saved_model(cls, saved_model_dir, bucket_name=None, app=None):
def from_saved_model(cls, saved_model_dir, model_file_name='firebase_ml_model.tflite',
bucket_name=None, app=None):
"""Creates a Tensor Flow Lite model from the saved model, and uploads the model to GCS.

Args:
saved_model_dir: The saved model directory.
model_file_name: The name that the tflite model will be saved as in Cloud Storage.
bucket_name: The name of an existing bucket. None to use the default bucket configured
in the app.
app: Optional. A Firebase app instance (or None to use the default app)
Expand All @@ -541,16 +543,18 @@ def from_saved_model(cls, saved_model_dir, bucket_name=None, app=None):
"""
TFLiteGCSModelSource._assert_tf_enabled()
tflite_model = TFLiteGCSModelSource._tf_convert_from_saved_model(saved_model_dir)
open('firebase_ml_model.tflite', 'wb').write(tflite_model)
return TFLiteGCSModelSource.from_tflite_model_file(
'firebase_ml_model.tflite', bucket_name, app)
with open(model_file_name, 'wb') as model_file:
model_file.write(tflite_model)
return TFLiteGCSModelSource.from_tflite_model_file(model_file_name, bucket_name, app)

@classmethod
def from_keras_model(cls, keras_model, bucket_name=None, app=None):
def from_keras_model(cls, keras_model, model_file_name='firebase_ml_model.tflite',
bucket_name=None, app=None):
"""Creates a Tensor Flow Lite model from the keras model, and uploads the model to GCS.

Args:
keras_model: A tf.keras model.
model_file_name: The name that the tflite model will be saved as in Cloud Storage.
bucket_name: The name of an existing bucket. None to use the default bucket configured
in the app.
app: Optional. A Firebase app instance (or None to use the default app)
Expand All @@ -563,9 +567,9 @@ def from_keras_model(cls, keras_model, bucket_name=None, app=None):
"""
TFLiteGCSModelSource._assert_tf_enabled()
tflite_model = TFLiteGCSModelSource._tf_convert_from_keras_model(keras_model)
open('firebase_ml_model.tflite', 'wb').write(tflite_model)
return TFLiteGCSModelSource.from_tflite_model_file(
'firebase_ml_model.tflite', bucket_name, app)
with open(model_file_name, 'wb') as model_file:
model_file.write(tflite_model)
return TFLiteGCSModelSource.from_tflite_model_file(model_file_name, bucket_name, app)

@property
def gcs_tflite_uri(self):
Expand Down