diff --git a/paddlespeech/s2t/models/u2/u2.py b/paddlespeech/s2t/models/u2/u2.py index 813e1e52..8a984949 100644 --- a/paddlespeech/s2t/models/u2/u2.py +++ b/paddlespeech/s2t/models/u2/u2.py @@ -605,8 +605,8 @@ class U2BaseModel(ASRInterface, nn.Layer): xs: paddle.Tensor, offset: int, required_cache_size: int, - att_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) - cnn_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]) ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor]: """ Export interface for c++ call, give input chunk xs, and return output from time 0 to current chunk. diff --git a/paddlespeech/s2t/modules/attention.py b/paddlespeech/s2t/modules/attention.py index 92990048..2d236743 100644 --- a/paddlespeech/s2t/modules/attention.py +++ b/paddlespeech/s2t/modules/attention.py @@ -86,7 +86,7 @@ class MultiHeadedAttention(nn.Layer): self, value: 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: """Compute attention context vector. Args: @@ -127,15 +127,14 @@ class MultiHeadedAttention(nn.Layer): return self.linear_out(x) # (batch, time1, d_model) - def forward( - self, - query: paddle.Tensor, - key: paddle.Tensor, - value: paddle.Tensor, - mask: paddle.Tensor, # paddle.ones([0,0,0], dtype=paddle.bool) - pos_emb: paddle.Tensor, # paddle.empty([0]) - cache: paddle.Tensor # paddle.zeros([0,0,0,0]) - ) -> Tuple[paddle.Tensor, paddle.Tensor]: + def forward(self, + query: paddle.Tensor, + key: paddle.Tensor, + value: paddle.Tensor, + mask: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool), + pos_emb: paddle.Tensor=paddle.empty([0]), + cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0]) + ) -> Tuple[paddle.Tensor, paddle.Tensor]: """Compute scaled dot product attention. Args: query (paddle.Tensor): Query tensor (#batch, time1, size). @@ -244,15 +243,14 @@ class RelPositionMultiHeadedAttention(MultiHeadedAttention): return x - def forward( - self, - query: paddle.Tensor, - key: paddle.Tensor, - value: paddle.Tensor, - mask: paddle.Tensor, # paddle.ones([0,0,0], dtype=paddle.bool) - pos_emb: paddle.Tensor, # paddle.empty([0]) - cache: paddle.Tensor # paddle.zeros([0,0,0,0]) - ) -> Tuple[paddle.Tensor, paddle.Tensor]: + def forward(self, + query: paddle.Tensor, + key: paddle.Tensor, + value: paddle.Tensor, + mask: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool), + pos_emb: paddle.Tensor=paddle.empty([0]), + cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0]) + ) -> Tuple[paddle.Tensor, paddle.Tensor]: """Compute 'Scaled Dot Product Attention' with rel. positional encoding. Args: query (paddle.Tensor): Query tensor (#batch, time1, size). diff --git a/paddlespeech/s2t/modules/conformer_convolution.py b/paddlespeech/s2t/modules/conformer_convolution.py index b35fea5b..be605654 100644 --- a/paddlespeech/s2t/modules/conformer_convolution.py +++ b/paddlespeech/s2t/modules/conformer_convolution.py @@ -108,8 +108,8 @@ class ConvolutionModule(nn.Layer): def forward( self, x: paddle.Tensor, - mask_pad: paddle.Tensor, # paddle.ones([0,0,0], dtype=paddle.bool) - cache: paddle.Tensor # paddle.zeros([0,0,0,0]) + mask_pad: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool), + cache: paddle.Tensor=paddle.zeros([0, 0, 0, 0]) ) -> Tuple[paddle.Tensor, paddle.Tensor]: """Compute convolution module. Args: diff --git a/paddlespeech/s2t/modules/decoder_layer.py b/paddlespeech/s2t/modules/decoder_layer.py index c8843b72..37b124e8 100644 --- a/paddlespeech/s2t/modules/decoder_layer.py +++ b/paddlespeech/s2t/modules/decoder_layer.py @@ -121,16 +121,11 @@ class DecoderLayer(nn.Layer): if self.concat_after: tgt_concat = paddle.cat( - (tgt_q, self.self_attn(tgt_q, tgt, tgt, tgt_q_mask, - paddle.empty([0]), - paddle.zeros([0, 0, 0, 0]))[0]), - dim=-1) + (tgt_q, self.self_attn(tgt_q, tgt, tgt, tgt_q_mask)[0]), dim=-1) x = residual + self.concat_linear1(tgt_concat) else: x = residual + self.dropout( - self.self_attn(tgt_q, tgt, tgt, tgt_q_mask, - paddle.empty([0]), paddle.zeros([0, 0, 0, 0]))[ - 0]) + self.self_attn(tgt_q, tgt, tgt, tgt_q_mask)[0]) if not self.normalize_before: x = self.norm1(x) @@ -139,15 +134,11 @@ class DecoderLayer(nn.Layer): x = self.norm2(x) if self.concat_after: x_concat = paddle.cat( - (x, self.src_attn(x, memory, memory, memory_mask, - paddle.empty([0]), - paddle.zeros([0, 0, 0, 0]))[0]), - dim=-1) + (x, self.src_attn(x, memory, memory, memory_mask)[0]), dim=-1) x = residual + self.concat_linear2(x_concat) else: x = residual + self.dropout( - self.src_attn(x, memory, memory, memory_mask, - paddle.empty([0]), paddle.zeros([0, 0, 0, 0]))[0]) + self.src_attn(x, memory, memory, memory_mask)[0]) if not self.normalize_before: x = self.norm2(x) diff --git a/paddlespeech/s2t/modules/encoder.py b/paddlespeech/s2t/modules/encoder.py index cf4e32fa..2f4ad1b2 100644 --- a/paddlespeech/s2t/modules/encoder.py +++ b/paddlespeech/s2t/modules/encoder.py @@ -175,9 +175,7 @@ class BaseEncoder(nn.Layer): decoding_chunk_size, self.static_chunk_size, num_decoding_left_chunks) for layer in self.encoders: - xs, chunk_masks, _, _ = layer(xs, chunk_masks, pos_emb, mask_pad, - paddle.zeros([0, 0, 0, 0]), - paddle.zeros([0, 0, 0, 0])) + xs, chunk_masks, _, _ = layer(xs, chunk_masks, pos_emb, mask_pad) if self.normalize_before: xs = self.after_norm(xs) # Here we assume the mask is not changed in encoder layers, so just @@ -190,9 +188,9 @@ class BaseEncoder(nn.Layer): xs: paddle.Tensor, offset: int, required_cache_size: int, - att_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_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) ) -> Tuple[paddle.Tensor, paddle.Tensor, paddle.Tensor]: """ Forward just one chunk Args: @@ -255,7 +253,6 @@ class BaseEncoder(nn.Layer): xs, att_mask, 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, cnn_cache=cnn_cache[i:i + 1] if paddle.shape(cnn_cache)[0] > 0 else cnn_cache, ) @@ -328,8 +325,7 @@ class BaseEncoder(nn.Layer): chunk_xs = xs[:, cur:end, :] (y, att_cache, cnn_cache) = self.forward_chunk( - chunk_xs, offset, required_cache_size, att_cache, cnn_cache, - paddle.ones([0, 0, 0], dtype=paddle.bool)) + chunk_xs, offset, required_cache_size, att_cache, cnn_cache) outputs.append(y) offset += y.shape[1] diff --git a/paddlespeech/s2t/modules/encoder_layer.py b/paddlespeech/s2t/modules/encoder_layer.py index 4555b535..dac62bce 100644 --- a/paddlespeech/s2t/modules/encoder_layer.py +++ b/paddlespeech/s2t/modules/encoder_layer.py @@ -76,10 +76,9 @@ class TransformerEncoderLayer(nn.Layer): x: paddle.Tensor, mask: paddle.Tensor, pos_emb: paddle.Tensor, - mask_pad: paddle. - Tensor, # paddle.ones([0, 0, 0], dtype=paddle.bool) - att_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) - cnn_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) + mask_pad: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool), + att_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]: """Compute encoded features. Args: @@ -106,8 +105,7 @@ class TransformerEncoderLayer(nn.Layer): if self.normalize_before: x = self.norm1(x) - x_att, new_att_cache = self.self_attn( - x, x, x, mask, paddle.empty([0]), cache=att_cache) + x_att, new_att_cache = self.self_attn(x, x, x, mask, cache=att_cache) if self.concat_after: x_concat = paddle.concat((x, x_att), axis=-1) @@ -195,9 +193,9 @@ class ConformerEncoderLayer(nn.Layer): x: paddle.Tensor, mask: paddle.Tensor, pos_emb: paddle.Tensor, - mask_pad: paddle.Tensor, #paddle.ones([0, 0, 0],dtype=paddle.bool) - att_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) - cnn_cache: paddle.Tensor, # paddle.zeros([0, 0, 0, 0]) + mask_pad: paddle.Tensor=paddle.ones([0, 0, 0], dtype=paddle.bool), + att_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]: """Compute encoded features. Args: diff --git a/paddlespeech/s2t/training/trainer.py b/paddlespeech/s2t/training/trainer.py index a7eb9892..4a69d78a 100644 --- a/paddlespeech/s2t/training/trainer.py +++ b/paddlespeech/s2t/training/trainer.py @@ -19,6 +19,10 @@ from pathlib import Path import paddle 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 paddlespeech.s2t.training.reporter import ObsScope @@ -122,9 +126,6 @@ class Trainer(): else: raise Exception("invalid device") - if self.parallel: - self.init_parallel() - self.checkpoint = Checkpoint( kbest_n=self.config.checkpoint.kbest_n, latest_n=self.config.checkpoint.latest_n) @@ -173,11 +174,6 @@ class Trainer(): """ return self.args.ngpu > 1 - def init_parallel(self): - """Init environment for multiprocess training. - """ - dist.init_parallel_env() - @mp_tools.rank_zero_only def save(self, tag=None, infos: dict=None): """Save checkpoint (model parameters and optimizer states). diff --git a/paddlespeech/server/engine/asr/online/python/asr_engine.py b/paddlespeech/server/engine/asr/online/python/asr_engine.py index 87d88ee6..5782d703 100644 --- a/paddlespeech/server/engine/asr/online/python/asr_engine.py +++ b/paddlespeech/server/engine/asr/online/python/asr_engine.py @@ -480,8 +480,7 @@ class PaddleASRConnectionHanddler: self.offset, required_cache_size, att_cache=self.att_cache, - cnn_cache=self.cnn_cache, - att_mask=paddle.ones([0, 0, 0], dtype=paddle.bool)) + cnn_cache=self.cnn_cache) outputs.append(y) # update the global offset, in decoding frame unit