From 4ace5a95b052d338947fc88809a440ccd55cf6b4 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 16 十一月 2023 16:39:52 +0800
Subject: [PATCH] funasr pages
---
funasr/export/export_model.py | 59 ++++++++++++++++++++++++++++++++---------------------------
1 files changed, 32 insertions(+), 27 deletions(-)
diff --git a/funasr/export/export_model.py b/funasr/export/export_model.py
index f31f960..6ab9408 100644
--- a/funasr/export/export_model.py
+++ b/funasr/export/export_model.py
@@ -1,14 +1,11 @@
-import json
-from typing import Union, Dict
-from pathlib import Path
-
import os
-import logging
import torch
-
-from funasr.export.models import get_model
-import numpy as np
import random
+import logging
+import numpy as np
+from pathlib import Path
+from typing import Union, Dict, List
+from funasr.export.models import get_model
from funasr.utils.types import str2bool, str2triple_str
# torch_version = float(".".join(torch.__version__.split(".")[:2]))
# assert torch_version > 1.9
@@ -59,14 +56,22 @@
model,
self.export_config,
)
- model.eval()
- # self._export_onnx(model, verbose, export_dir)
- if self.onnx:
- self._export_onnx(model, verbose, export_dir)
+ if isinstance(model, List):
+ for m in model:
+ m.eval()
+ if self.onnx:
+ self._export_onnx(m, verbose, export_dir)
+ else:
+ self._export_torchscripts(m, verbose, export_dir)
+ print("output dir: {}".format(export_dir))
else:
- self._export_torchscripts(model, verbose, export_dir)
-
- print("output dir: {}".format(export_dir))
+ model.eval()
+ # self._export_onnx(model, verbose, export_dir)
+ if self.onnx:
+ self._export_onnx(model, verbose, export_dir)
+ else:
+ self._export_torchscripts(model, verbose, export_dir)
+ print("output dir: {}".format(export_dir))
def _torch_quantize(self, model):
@@ -230,17 +235,17 @@
# model_script = torch.jit.script(model)
model_script = model #torch.jit.trace(model)
model_path = os.path.join(path, f'{model.model_name}.onnx')
- if not os.path.exists(model_path):
- torch.onnx.export(
- model_script,
- dummy_input,
- model_path,
- verbose=verbose,
- opset_version=14,
- input_names=model.get_input_names(),
- output_names=model.get_output_names(),
- dynamic_axes=model.get_dynamic_axes()
- )
+ # if not os.path.exists(model_path):
+ torch.onnx.export(
+ model_script,
+ dummy_input,
+ model_path,
+ verbose=verbose,
+ opset_version=14,
+ input_names=model.get_input_names(),
+ output_names=model.get_output_names(),
+ dynamic_axes=model.get_dynamic_axes()
+ )
if self.quant:
from onnxruntime.quantization import QuantType, quantize_dynamic
@@ -249,7 +254,7 @@
if not os.path.exists(quant_model_path):
onnx_model = onnx.load(model_path)
nodes = [n.name for n in onnx_model.graph.node]
- nodes_to_exclude = [m for m in nodes if 'output' in m]
+ nodes_to_exclude = [m for m in nodes if 'output' in m or 'bias_encoder' in m or 'bias_decoder' in m]
quantize_dynamic(
model_input=model_path,
model_output=quant_model_path,
--
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