msb-public
/
PaddleSpeech
mirror of https://github.com/PaddlePaddle/PaddleSpeech
1
0
Code Issues Projects Releases Wiki Activity

Merge pull request #2372 from Zth9730/fix_dp_init

Browse Source 
[s2t] DataParallel init method changed, fixed conformer could not multi-gpu training and don't affect dy2st
pull/2390/head
Hui Zhang 2 years ago committed by GitHub
parent 02ac117dfb 663e3ab58e
commit 07f566e0a5
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
8 changed files with 42 additions and 64 deletions
Show Stats Download Patch File Download Diff File

4
paddlespeech/s2t/models/u2/u2.py
Unescape View File

@ -605,8 +605,8 @@ class U2BaseModel(ASRInterface, nn.Layer):
xs: paddle.Tensor, xs: paddle.Tensor,
offset: int, offset: int,
required_cache_size: int, required_cache_size: int,
att_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) att_cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0]),
cnn_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) cnn_cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0])
) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor]: ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor]:
""" Export interface for c++ call, give input chunk xs, and return """ Export interface for c++ call, give input chunk xs, and return
output from time 0 to current chunk. output from time 0 to current chunk.

20
paddlespeech/s2t/modules/attention.py
Unescape View File

@ -86,7 +86,7 @@ class MultiHeadedAttention(nn.Layer):
self, self,
value: paddle.Tensor, value: paddle.Tensor,
scores: paddle.Tensor, scores: paddle.Tensor,
mask: paddle.Tensor, # paddle.ones([0, 0, 0], dtype=paddle.bool) mask: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool)
) -> paddle.Tensor: ) -> paddle.Tensor:
"""Compute attention context vector. """Compute attention context vector.
Args: Args:
@ -127,14 +127,13 @@ class MultiHeadedAttention(nn.Layer):
return self.linear_out(x) # (batch, time1, d_model) return self.linear_out(x) # (batch, time1, d_model)
def forward( def forward(self,
self,
query: paddle.Tensor, query: paddle.Tensor,
key: paddle.Tensor, key: paddle.Tensor,
value: paddle.Tensor, value: paddle.Tensor,
mask: paddle.Tensor, # paddle.ones([0,0,0], dtype=paddle.bool) mask: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool),
pos_emb: paddle.Tensor, # paddle.empty([0]) pos_emb: paddle.Tensor=paddle.empty([0]),
cache: paddle.Tensor # paddle.zeros([0,0,0,0]) cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0])
) -> Tuple[paddle.Tensor, paddle.Tensor]: ) -> Tuple[paddle.Tensor, paddle.Tensor]:
"""Compute scaled dot product attention. """Compute scaled dot product attention.
Args: Args:
@ -244,14 +243,13 @@ class RelPositionMultiHeadedAttention(MultiHeadedAttention):
return x return x
def forward( def forward(self,
self,
query: paddle.Tensor, query: paddle.Tensor,
key: paddle.Tensor, key: paddle.Tensor,
value: paddle.Tensor, value: paddle.Tensor,
mask: paddle.Tensor, # paddle.ones([0,0,0], dtype=paddle.bool) mask: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool),
pos_emb: paddle.Tensor, # paddle.empty([0]) pos_emb: paddle.Tensor=paddle.empty([0]),
cache: paddle.Tensor # paddle.zeros([0,0,0,0]) cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0])
) -> Tuple[paddle.Tensor, paddle.Tensor]: ) -> Tuple[paddle.Tensor, paddle.Tensor]:
"""Compute 'Scaled Dot Product Attention' with rel. positional encoding. """Compute 'Scaled Dot Product Attention' with rel. positional encoding.
Args: Args:

4
paddlespeech/s2t/modules/conformer_convolution.py
Unescape View File

@ -108,8 +108,8 @@ class ConvolutionModule(nn.Layer):
def forward( def forward(
self, self,
x: paddle.Tensor, x: paddle.Tensor,
mask_pad: paddle.Tensor, # paddle.ones([0,0,0], dtype=paddle.bool) mask_pad: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool),
cache: paddle.Tensor # paddle.zeros([0,0,0,0]) cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0])
) -> Tuple[paddle.Tensor, paddle.Tensor]: ) -> Tuple[paddle.Tensor, paddle.Tensor]:
"""Compute convolution module. """Compute convolution module.
Args: Args:

17
paddlespeech/s2t/modules/decoder_layer.py
Unescape View File

@ -121,16 +121,11 @@ class DecoderLayer(nn.Layer):
if self.concat_after: if self.concat_after:
tgt_concat = paddle.cat( tgt_concat = paddle.cat(
(tgt_q, self.self_attn(tgt_q, tgt, tgt, tgt_q_mask, (tgt_q, self.self_attn(tgt_q, tgt, tgt, tgt_q_mask)[0]), dim=-1)
paddle.empty([0]),
paddle.zeros([0, 0, 0, 0]))[0]),
dim=-1)
x = residual + self.concat_linear1(tgt_concat) x = residual + self.concat_linear1(tgt_concat)
else: else:
x = residual + self.dropout( x = residual + self.dropout(
self.self_attn(tgt_q, tgt, tgt, tgt_q_mask, self.self_attn(tgt_q, tgt, tgt, tgt_q_mask)[0])
paddle.empty([0]), paddle.zeros([0, 0, 0, 0]))[
0])
if not self.normalize_before: if not self.normalize_before:
x = self.norm1(x) x = self.norm1(x)
@ -139,15 +134,11 @@ class DecoderLayer(nn.Layer):
x = self.norm2(x) x = self.norm2(x)
if self.concat_after: if self.concat_after:
x_concat = paddle.cat( x_concat = paddle.cat(
(x, self.src_attn(x, memory, memory, memory_mask, (x, self.src_attn(x, memory, memory, memory_mask)[0]), dim=-1)
paddle.empty([0]),
paddle.zeros([0, 0, 0, 0]))[0]),
dim=-1)
x = residual + self.concat_linear2(x_concat) x = residual + self.concat_linear2(x_concat)
else: else:
x = residual + self.dropout( x = residual + self.dropout(
self.src_attn(x, memory, memory, memory_mask, self.src_attn(x, memory, memory, memory_mask)[0])
paddle.empty([0]), paddle.zeros([0, 0, 0, 0]))[0])
if not self.normalize_before: if not self.normalize_before:
x = self.norm2(x) x = self.norm2(x)

14
paddlespeech/s2t/modules/encoder.py
Unescape View File

@ -175,9 +175,7 @@ class BaseEncoder(nn.Layer):
decoding_chunk_size, self.static_chunk_size, decoding_chunk_size, self.static_chunk_size,
num_decoding_left_chunks) num_decoding_left_chunks)
for layer in self.encoders: for layer in self.encoders:
xs, chunk_masks, _, _ = layer(xs, chunk_masks, pos_emb, mask_pad, xs, chunk_masks, _, _ = layer(xs, chunk_masks, pos_emb, mask_pad)
paddle.zeros([0, 0, 0, 0]),
paddle.zeros([0, 0, 0, 0]))
if self.normalize_before: if self.normalize_before:
xs = self.after_norm(xs) xs = self.after_norm(xs)
# Here we assume the mask is not changed in encoder layers, so just # Here we assume the mask is not changed in encoder layers, so just
@ -190,9 +188,9 @@ class BaseEncoder(nn.Layer):
xs: paddle.Tensor, xs: paddle.Tensor,
offset: int, offset: int,
required_cache_size: int, required_cache_size: int,
att_cache: paddle.Tensor, # paddle.zeros([0,0,0,0]) att_cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0]),
cnn_cache: paddle.Tensor, # paddle.zeros([0,0,0,0]), cnn_cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0]),
att_mask: paddle.Tensor, # paddle.ones([0,0,0], dtype=paddle.bool) att_mask: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool)
) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor]: ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor]:
""" Forward just one chunk """ Forward just one chunk
Args: Args:
@ -255,7 +253,6 @@ class BaseEncoder(nn.Layer):
xs, xs,
att_mask, att_mask,
pos_emb, pos_emb,
mask_pad=paddle.ones([0, 0, 0], dtype=paddle.bool),
att_cache=att_cache[i:i + 1] if elayers > 0 else att_cache, att_cache=att_cache[i:i + 1] if elayers > 0 else att_cache,
cnn_cache=cnn_cache[i:i + 1] cnn_cache=cnn_cache[i:i + 1]
if paddle.shape(cnn_cache)[0] > 0 else cnn_cache, ) if paddle.shape(cnn_cache)[0] > 0 else cnn_cache, )
@ -328,8 +325,7 @@ class BaseEncoder(nn.Layer):
chunk_xs = xs[:, cur:end, :] chunk_xs = xs[:, cur:end, :]
(y, att_cache, cnn_cache) = self.forward_chunk( (y, att_cache, cnn_cache) = self.forward_chunk(
chunk_xs, offset, required_cache_size, att_cache, cnn_cache, chunk_xs, offset, required_cache_size, att_cache, cnn_cache)
paddle.ones([0, 0, 0], dtype=paddle.bool))
outputs.append(y) outputs.append(y)
offset += y.shape[1] offset += y.shape[1]

16
paddlespeech/s2t/modules/encoder_layer.py
Unescape View File

@ -76,10 +76,9 @@ class TransformerEncoderLayer(nn.Layer):
x: paddle.Tensor, x: paddle.Tensor,
mask: paddle.Tensor, mask: paddle.Tensor,
pos_emb: paddle.Tensor, pos_emb: paddle.Tensor,
mask_pad: paddle. mask_pad: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool),
Tensor, # paddle.ones([0, 0, 0], dtype=paddle.bool) att_cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0]),
att_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) cnn_cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0])
cnn_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0])
) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor, paddle.Tensor]: ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor, paddle.Tensor]:
"""Compute encoded features. """Compute encoded features.
Args: Args:
@ -106,8 +105,7 @@ class TransformerEncoderLayer(nn.Layer):
if self.normalize_before: if self.normalize_before:
x = self.norm1(x) x = self.norm1(x)
x_att, new_att_cache = self.self_attn( x_att, new_att_cache = self.self_attn(x, x, x, mask, cache=att_cache)
x, x, x, mask, paddle.empty([0]), cache=att_cache)
if self.concat_after: if self.concat_after:
x_concat = paddle.concat((x, x_att), axis=-1) x_concat = paddle.concat((x, x_att), axis=-1)
@ -195,9 +193,9 @@ class ConformerEncoderLayer(nn.Layer):
x: paddle.Tensor, x: paddle.Tensor,
mask: paddle.Tensor, mask: paddle.Tensor,
pos_emb: paddle.Tensor, pos_emb: paddle.Tensor,
mask_pad: paddle.Tensor, #paddle.ones([0, 0, 0],dtype=paddle.bool) mask_pad: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool),
att_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) att_cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0]),
cnn_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) cnn_cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0])
) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor, paddle.Tensor]: ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor, paddle.Tensor]:
"""Compute encoded features. """Compute encoded features.
Args: Args:

12
paddlespeech/s2t/training/trainer.py
Unescape View File

@ -19,6 +19,10 @@ from pathlib import Path
import paddle import paddle
from paddle import distributed as dist from paddle import distributed as dist
world_size = dist.get_world_size()
if world_size > 1:
dist.init_parallel_env()
from visualdl import LogWriter from visualdl import LogWriter
from paddlespeech.s2t.training.reporter import ObsScope from paddlespeech.s2t.training.reporter import ObsScope
@ -122,9 +126,6 @@ class Trainer():
else: else:
raise Exception("invalid device") raise Exception("invalid device")
if self.parallel:
self.init_parallel()
self.checkpoint = Checkpoint( self.checkpoint = Checkpoint(
kbest_n=self.config.checkpoint.kbest_n, kbest_n=self.config.checkpoint.kbest_n,
latest_n=self.config.checkpoint.latest_n) latest_n=self.config.checkpoint.latest_n)
@ -173,11 +174,6 @@ class Trainer():
""" """
return self.args.ngpu > 1 return self.args.ngpu > 1
def init_parallel(self):
"""Init environment for multiprocess training.
"""
dist.init_parallel_env()
@mp_tools.rank_zero_only @mp_tools.rank_zero_only
def save(self, tag=None, infos: dict=None): def save(self, tag=None, infos: dict=None):
"""Save checkpoint (model parameters and optimizer states). """Save checkpoint (model parameters and optimizer states).

3
paddlespeech/server/engine/asr/online/python/asr_engine.py
Unescape View File

@ -480,8 +480,7 @@ class PaddleASRConnectionHanddler:
self.offset, self.offset,
required_cache_size, required_cache_size,
att_cache=self.att_cache, att_cache=self.att_cache,
cnn_cache=self.cnn_cache, cnn_cache=self.cnn_cache)
att_mask=paddle.ones([0, 0, 0], dtype=paddle.bool))
outputs.append(y) outputs.append(y)
# update the global offset, in decoding frame unit # update the global offset, in decoding frame unit

Write Preview
Loading…
Cancel
Save