From 2868fe3df4e92a6ae3e327faf6e57ea492e04124 Mon Sep 17 00:00:00 2001
From: 志浩 <neo.dzh@alibaba-inc.com>
Date: 星期四, 16 三月 2023 19:24:21 +0800
Subject: [PATCH] Merge branch 'main' into dev_dzh
---
funasr/export/models/encoder/conformer_encoder.py | 105 ++++++++++++++++++++++++++++++++++++++++++++++++++++
1 files changed, 105 insertions(+), 0 deletions(-)
diff --git a/funasr/export/models/encoder/conformer_encoder.py b/funasr/export/models/encoder/conformer_encoder.py
new file mode 100644
index 0000000..0a35653
--- /dev/null
+++ b/funasr/export/models/encoder/conformer_encoder.py
@@ -0,0 +1,105 @@
+import torch
+import torch.nn as nn
+
+from funasr.export.utils.torch_function import MakePadMask
+from funasr.export.utils.torch_function import sequence_mask
+from funasr.modules.attention import MultiHeadedAttentionSANM
+from funasr.export.models.modules.multihead_att import MultiHeadedAttentionSANM as MultiHeadedAttentionSANM_export
+from funasr.export.models.modules.encoder_layer import EncoderLayerSANM as EncoderLayerSANM_export
+from funasr.export.models.modules.encoder_layer import EncoderLayerConformer as EncoderLayerConformer_export
+from funasr.modules.positionwise_feed_forward import PositionwiseFeedForward
+from funasr.export.models.modules.feedforward import PositionwiseFeedForward as PositionwiseFeedForward_export
+from funasr.export.models.encoder.sanm_encoder import SANMEncoder
+from funasr.modules.attention import RelPositionMultiHeadedAttention
+# from funasr.export.models.modules.multihead_att import RelPositionMultiHeadedAttention as RelPositionMultiHeadedAttention_export
+from funasr.export.models.modules.multihead_att import OnnxRelPosMultiHeadedAttention as RelPositionMultiHeadedAttention_export
+
+
+class ConformerEncoder(nn.Module):
+ def __init__(
+ self,
+ model,
+ max_seq_len=512,
+ feats_dim=560,
+ model_name='encoder',
+ onnx: bool = True,
+ ):
+ super().__init__()
+ self.embed = model.embed
+ self.model = model
+ self.feats_dim = feats_dim
+ self._output_size = model._output_size
+
+ if onnx:
+ self.make_pad_mask = MakePadMask(max_seq_len, flip=False)
+ else:
+ self.make_pad_mask = sequence_mask(max_seq_len, flip=False)
+
+ for i, d in enumerate(self.model.encoders):
+ if isinstance(d.self_attn, MultiHeadedAttentionSANM):
+ d.self_attn = MultiHeadedAttentionSANM_export(d.self_attn)
+ if isinstance(d.self_attn, RelPositionMultiHeadedAttention):
+ d.self_attn = RelPositionMultiHeadedAttention_export(d.self_attn)
+ if isinstance(d.feed_forward, PositionwiseFeedForward):
+ d.feed_forward = PositionwiseFeedForward_export(d.feed_forward)
+ self.model.encoders[i] = EncoderLayerConformer_export(d)
+
+ self.model_name = model_name
+ self.num_heads = model.encoders[0].self_attn.h
+ self.hidden_size = model.encoders[0].self_attn.linear_out.out_features
+
+
+ def prepare_mask(self, mask):
+ if len(mask.shape) == 2:
+ mask = 1 - mask[:, None, None, :]
+ elif len(mask.shape) == 3:
+ mask = 1 - mask[:, None, :]
+
+ return mask * -10000.0
+
+ def forward(self,
+ speech: torch.Tensor,
+ speech_lengths: torch.Tensor,
+ ):
+ mask = self.make_pad_mask(speech_lengths)
+ mask = self.prepare_mask(mask)
+ if self.embed is None:
+ xs_pad = speech
+ else:
+ xs_pad = self.embed(speech)
+
+ encoder_outs = self.model.encoders(xs_pad, mask)
+ xs_pad, masks = encoder_outs[0], encoder_outs[1]
+
+ if isinstance(xs_pad, tuple):
+ xs_pad = xs_pad[0]
+ xs_pad = self.model.after_norm(xs_pad)
+
+ return xs_pad, speech_lengths
+
+ def get_output_size(self):
+ return self.model.encoders[0].size
+
+ def get_dummy_inputs(self):
+ feats = torch.randn(1, 100, self.feats_dim)
+ return (feats)
+
+ def get_input_names(self):
+ return ['feats']
+
+ def get_output_names(self):
+ return ['encoder_out', 'encoder_out_lens', 'predictor_weight']
+
+ def get_dynamic_axes(self):
+ return {
+ 'feats': {
+ 1: 'feats_length'
+ },
+ 'encoder_out': {
+ 1: 'enc_out_length'
+ },
+ 'predictor_weight':{
+ 1: 'pre_out_length'
+ }
+
+ }
--
Gitblit v1.9.1