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Add an --export_quantize flag to control TFLite export quantization

This commit is contained in:
Reuben Morais 2021-08-06 16:52:55 +02:00
parent c3cc7aae2e
commit 3cff3dd0de
2 changed files with 9 additions and 2 deletions
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5
training/coqui_stt_training/train.py
View File

@ -1116,7 +1116,10 @@ def export():
input_tensors=inputs.values(), input_tensors=inputs.values(),
output_tensors=outputs.values(), output_tensors=outputs.values(),
) )
converter.optimizations = [tf.lite.Optimize.DEFAULT]
if Config.export_quantize:
converter.optimizations = [tf.lite.Optimize.DEFAULT]
# AudioSpectrogram and Mfcc ops are custom but have built-in kernels in TFLite # AudioSpectrogram and Mfcc ops are custom but have built-in kernels in TFLite
converter.allow_custom_ops = True converter.allow_custom_ops = True
tflite_model = converter.convert() tflite_model = converter.convert()

6
training/coqui_stt_training/util/config.py
View File

@ -22,7 +22,7 @@ class _ConfigSingleton:
_config = None _config = None
def __getattr__(self, name): def __getattr__(self, name):
if not _ConfigSingleton._config: if _ConfigSingleton._config is None:
raise RuntimeError("Global configuration not yet initialized.") raise RuntimeError("Global configuration not yet initialized.")
if not hasattr(_ConfigSingleton._config, name): if not hasattr(_ConfigSingleton._config, name):
raise RuntimeError( raise RuntimeError(
@ -478,6 +478,10 @@ class _SttConfig(Coqpit):
export_tflite: bool = field( export_tflite: bool = field(
default=False, metadata=dict(help="export a graph ready for TF Lite engine") default=False, metadata=dict(help="export a graph ready for TF Lite engine")
) )
export_quantize: bool = field(
default=True,
metadata=dict(help="export a quantized model (optimized for size)"),
)
n_steps: int = field( n_steps: int = field(
default=16, default=16,
metadata=dict( metadata=dict(