minor refactor

Signed-off-by: manickavela29 <manickavela1998@gmail.com>
This commit is contained in:
manickavela29 2024-06-27 05:32:53 +00:00
parent f657c364af
commit fa235adba2

View File

@ -343,7 +343,6 @@ def export_encoder_model_onnx(
encoder_filename: str,
opset_version: int = 11,
feature_dim: int = 80,
fp16: bool = False,
) -> None:
encoder_model.encoder.__class__.forward = (
encoder_model.encoder.__class__.streaming_forward
@ -489,12 +488,6 @@ def export_encoder_model_onnx(
add_meta_data(filename=encoder_filename, meta_data=meta_data)
if(fp16) :
logging.info("Exporting Encoder model in fp16")
encoder = onnx.load(encoder_filename)
encoder_fp16 = float16.convert_float_to_float16(encoder, keep_io_types=True)
onnx.save(encoder_fp16,encoder_filename)
def export_decoder_model_onnx(
decoder_model: OnnxDecoder,
decoder_filename: str,
@ -741,7 +734,6 @@ def main():
encoder_filename,
opset_version=opset_version,
feature_dim=params.feature_dim,
fp16=params.fp16,
)
logging.info(f"Exported encoder to {encoder_filename}")
@ -766,8 +758,27 @@ def main():
# Generate int8 quantization models
# See https://onnxruntime.ai/docs/performance/model-optimizations/quantization.html#data-type-selection
logging.info("Generate int8 quantization models")
if(params.fp16) :
logging.info("Exporting models in fp16")
encoder = onnx.load(encoder_filename)
encoder_fp16 = float16.convert_float_to_float16(encoder, keep_io_types=True)
encoder_filename_fp16 = params.exp_dir / f"encoder-{suffix}.fp16.onnx"
onnx.save(encoder_fp16,encoder_filename_fp16)
decoder = onnx.load(decoder_filename)
decoder_fp16 = float16.convert_float_to_float16(decoder, keep_io_types=True)
decoder_filename_fp16 = params.exp_dir / f"decoder-{suffix}.fp16.onnx"
onnx.save(decoder_fp16,decoder_filename_fp16)
joiner = onnx.load(joiner_filename)
joiner_fp16 = float16.convert_float_to_float16(joiner, keep_io_types=True)
joiner_filename_fp16 = params.exp_dir / f"joiner-{suffix}.fp16.onnx"
onnx.save(joiner_fp16,joiner_filename_fp16)
logging.info("Generate int8 quantization models")
encoder_filename_int8 = params.exp_dir / f"encoder-{suffix}.int8.onnx"
quantize_dynamic(
model_input=encoder_filename,