use explicit relative imports

egs/gigaspeech/ASR/conformer_ctc/conformer.py

@@ -21,7 +21,8 @@ from typing import Optional, Tuple, Union
 
 import torch
 from torch import Tensor, nn
-from transformer import Supervisions, Transformer, encoder_padding_mask
+
+from .transformer import Supervisions, Transformer, encoder_padding_mask
 
 
 class Conformer(Transformer):

egs/gigaspeech/ASR/conformer_ctc/decode.py

@@ -27,9 +27,6 @@ import k2
 import sentencepiece as spm
 import torch
 import torch.nn as nn
-from asr_datamodule import GigaSpeechAsrDataModule
-from conformer import Conformer
-from gigaspeech_scoring import asr_text_post_processing
 
 from icefall.bpe_graph_compiler import BpeCtcTrainingGraphCompiler
 from icefall.checkpoint import average_checkpoints, load_checkpoint
@@ -52,6 +49,10 @@ from icefall.utils import (
     write_error_stats,
 )
 
+from .asr_datamodule import GigaSpeechAsrDataModule
+from .conformer import Conformer
+from .gigaspeech_scoring import asr_text_post_processing
+
 
 def get_parser():
     parser = argparse.ArgumentParser(

egs/gigaspeech/ASR/conformer_ctc/train.py

@@ -34,7 +34,6 @@ from torch import Tensor
 from torch.nn.parallel import DistributedDataParallel as DDP
 from torch.nn.utils import clip_grad_norm_
 from torch.utils.tensorboard import SummaryWriter
-from transformer import Noam
 
 from icefall.bpe_graph_compiler import BpeCtcTrainingGraphCompiler
 from icefall.checkpoint import load_checkpoint
@@ -50,6 +49,8 @@ from icefall.utils import (
     str2bool,
 )
 
+from .transformer import Noam
+
 
 def get_parser():
     parser = argparse.ArgumentParser(

egs/gigaspeech/ASR/conformer_ctc/transformer.py

@@ -19,10 +19,11 @@ from typing import Dict, List, Optional, Tuple, Union
 
 import torch
 import torch.nn as nn
-from label_smoothing import LabelSmoothingLoss
-from subsampling import Conv2dSubsampling, VggSubsampling
 from torch.nn.utils.rnn import pad_sequence
 
+from .label_smoothing import LabelSmoothingLoss
+from .subsampling import Conv2dSubsampling, VggSubsampling
+
 # Note: TorchScript requires Dict/List/etc. to be fully typed.
 Supervisions = Dict[str, torch.Tensor]
 

egs/gigaspeech/ASR/pruned_transducer_stateless2/decode.py

@@ -66,16 +66,14 @@ import k2
 import sentencepiece as spm
 import torch
 import torch.nn as nn
-from asr_datamodule import GigaSpeechAsrDataModule
-from beam_search import (
+from .asr_datamodule import GigaSpeechAsrDataModule
+from .beam_search import (
     beam_search,
     fast_beam_search_one_best,
     greedy_search,
     greedy_search_batch,
     modified_beam_search,
 )
-from .gigaspeech_scoring import asr_text_post_processing
-from .train import get_params, get_transducer_model
 
 from icefall.checkpoint import average_checkpoints, find_checkpoints, load_checkpoint
 from icefall.utils import (
@@ -85,6 +83,9 @@ from icefall.utils import (
     write_error_stats,
 )
 
+from .gigaspeech_scoring import asr_text_post_processing
+from .train import get_params, get_transducer_model
+
 
 def get_parser():
     parser = argparse.ArgumentParser(

egs/gigaspeech/ASR/pruned_transducer_stateless2/export.py

@@ -49,7 +49,7 @@ from pathlib import Path
 
 import sentencepiece as spm
 import torch
-from train import get_params, get_transducer_model
+from .train import get_params, get_transducer_model
 
 from icefall.checkpoint import average_checkpoints, find_checkpoints, load_checkpoint
 from icefall.utils import str2bool

egs/gigaspeech/ASR/pruned_transducer_stateless2/train.py

@@ -56,14 +56,14 @@ import sentencepiece as spm
 import torch
 import torch.multiprocessing as mp
 import torch.nn as nn
-from asr_datamodule import GigaSpeechAsrDataModule
-from conformer import Conformer
-from decoder import Decoder
-from joiner import Joiner
+from .asr_datamodule import GigaSpeechAsrDataModule
+from .conformer import Conformer
+from .decoder import Decoder
+from .joiner import Joiner
 from lhotse.dataset.sampling.base import CutSampler
 from lhotse.utils import fix_random_seed
-from model import Transducer
-from optim import Eden, Eve
+from .model import Transducer
+from .optim import Eden, Eve
 from torch import Tensor
 from torch.cuda.amp import GradScaler
 from torch.nn.parallel import DistributedDataParallel as DDP

egs/librispeech/ASR/local/convert_transcript_words_to_tokens.py

@@ -36,7 +36,7 @@ import argparse
 from pathlib import Path
 from typing import Dict, List
 
-from generate_unique_lexicon import filter_multiple_pronunications
+from .generate_unique_lexicon import filter_multiple_pronunications
 
 from icefall.lexicon import read_lexicon
 

egs/librispeech/ASR/local/prepare_lang_bpe.py

@@ -41,7 +41,7 @@ from typing import Dict, List, Tuple
 import k2
 import sentencepiece as spm
 import torch
-from prepare_lang import (
+from .prepare_lang import (
     Lexicon,
     add_disambig_symbols,
     add_self_loops,

egs/librispeech/ASR/pruned_transducer_stateless2/beam_search.py

@@ -21,7 +21,7 @@ from typing import Dict, List, Optional
 import k2
 import sentencepiece as spm
 import torch
-from model import Transducer
+from .model import Transducer
 
 from icefall.decode import Nbest, one_best_decoding
 from icefall.utils import add_eos, add_sos, get_texts

egs/librispeech/ASR/pruned_transducer_stateless2/conformer.py

@@ -21,8 +21,8 @@ import warnings
 from typing import List, Optional, Tuple
 
 import torch
-from encoder_interface import EncoderInterface
-from scaling import (
+from .encoder_interface import EncoderInterface
+from .scaling import (
     ActivationBalancer,
     BasicNorm,
     DoubleSwish,

egs/librispeech/ASR/pruned_transducer_stateless2/decoder.py

@@ -17,7 +17,7 @@
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from scaling import ScaledConv1d, ScaledEmbedding
+from .scaling import ScaledConv1d, ScaledEmbedding
 
 
 class Decoder(nn.Module):

egs/librispeech/ASR/pruned_transducer_stateless2/joiner.py

@@ -16,7 +16,7 @@
 
 import torch
 import torch.nn as nn
-from scaling import ScaledLinear
+from .scaling import ScaledLinear
 
 
 class Joiner(nn.Module):

egs/librispeech/ASR/pruned_transducer_stateless2/model.py

@@ -18,8 +18,8 @@
 import k2
 import torch
 import torch.nn as nn
-from encoder_interface import EncoderInterface
-from scaling import ScaledLinear
+from .encoder_interface import EncoderInterface
+from .scaling import ScaledLinear
 
 from icefall.utils import add_sos