examples/seq2seq/__init__.py mutates sys.path (#7194)

examples/seq2seq/__init__.py

@@ -0,0 +1,5 @@
+import os
+import sys
+
+
+sys.path.insert(1, os.path.dirname(os.path.realpath(__file__)))

examples/seq2seq/distillation.py

@@ -10,28 +10,12 @@ import torch
 from torch import nn
 from torch.nn import functional as F
 
-from lightning_base import generic_train
-from transformers import AutoModelForSeq2SeqLM, MBartTokenizer, T5Config, T5ForConditionalGeneration
-from transformers.modeling_bart import shift_tokens_right
-
-
-try:
-    from .finetune import SummarizationModule, TranslationModule
-    from .finetune import main as ft_main
-    from .initialization_utils import copy_layers, init_student
-    from .utils import (
-        any_requires_grad,
-        assert_all_frozen,
-        calculate_bleu,
-        freeze_params,
-        label_smoothed_nll_loss,
-        pickle_load,
-        use_task_specific_params,
-    )
-except ImportError:
 from finetune import SummarizationModule, TranslationModule
 from finetune import main as ft_main
 from initialization_utils import copy_layers, init_student
+from lightning_base import generic_train
+from transformers import AutoModelForSeq2SeqLM, MBartTokenizer, T5Config, T5ForConditionalGeneration
+from transformers.modeling_bart import shift_tokens_right
 from utils import (
     any_requires_grad,
     assert_all_frozen,

examples/seq2seq/finetune.py

@@ -12,32 +12,10 @@ import pytorch_lightning as pl
 import torch
 from torch.utils.data import DataLoader
 
+from callbacks import Seq2SeqLoggingCallback, get_checkpoint_callback, get_early_stopping_callback
 from lightning_base import BaseTransformer, add_generic_args, generic_train
 from transformers import MBartTokenizer, T5ForConditionalGeneration
 from transformers.modeling_bart import shift_tokens_right
-
-
-try:
-    from .callbacks import Seq2SeqLoggingCallback, get_checkpoint_callback, get_early_stopping_callback
-    from .utils import (
-        ROUGE_KEYS,
-        LegacySeq2SeqDataset,
-        Seq2SeqDataset,
-        assert_all_frozen,
-        calculate_bleu,
-        calculate_rouge,
-        flatten_list,
-        freeze_params,
-        get_git_info,
-        label_smoothed_nll_loss,
-        lmap,
-        pickle_save,
-        save_git_info,
-        save_json,
-        use_task_specific_params,
-    )
-except ImportError:
-    from callbacks import Seq2SeqLoggingCallback, get_checkpoint_callback, get_early_stopping_callback
 from utils import (
     ROUGE_KEYS,
     LegacySeq2SeqDataset,
@@ -56,6 +34,7 @@ except ImportError:
     use_task_specific_params,
 )
 
+
 logger = logging.getLogger(__name__)
 
 

examples/seq2seq/run_distributed_eval.py

@@ -11,23 +11,6 @@ from torch.utils.data import DataLoader
 from tqdm import tqdm
 
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
-
-
-logger = getLogger(__name__)
-
-try:
-    from .utils import (
-        Seq2SeqDataset,
-        calculate_bleu,
-        calculate_rouge,
-        lmap,
-        load_json,
-        parse_numeric_n_bool_cl_kwargs,
-        save_json,
-        use_task_specific_params,
-        write_txt_file,
-    )
-except ImportError:
 from utils import (
     Seq2SeqDataset,
     calculate_bleu,
@@ -41,6 +24,9 @@ except ImportError:
 )
 
 
+logger = getLogger(__name__)
+
+
 def eval_data_dir(
     data_dir,
     save_dir: str,

examples/seq2seq/run_eval.py

@@ -11,14 +11,11 @@ import torch
 from tqdm import tqdm
 
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+from utils import calculate_bleu, calculate_rouge, parse_numeric_n_bool_cl_kwargs, use_task_specific_params
 
 
 logger = getLogger(__name__)
 
-try:
-    from .utils import calculate_bleu, calculate_rouge, parse_numeric_n_bool_cl_kwargs, use_task_specific_params
-except ImportError:
-    from utils import calculate_bleu, calculate_rouge, parse_numeric_n_bool_cl_kwargs, use_task_specific_params
 
 DEFAULT_DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 

examples/seq2seq/run_eval_search.py

@@ -4,10 +4,6 @@ import operator
 import sys
 from collections import OrderedDict
 
-
-try:
-    from .run_eval import datetime_now, run_generate
-except ImportError:
 from run_eval import datetime_now, run_generate
 
 

examples/seq2seq/test_bash_script.py

@@ -10,13 +10,12 @@ import pytorch_lightning as pl
 import timeout_decorator
 import torch
 
+from distillation import BartSummarizationDistiller, distill_main
+from finetune import SummarizationModule, main
+from test_seq2seq_examples import CUDA_AVAILABLE, MBART_TINY
 from transformers import BartForConditionalGeneration, MarianMTModel
 from transformers.testing_utils import slow
-
-from .distillation import BartSummarizationDistiller, distill_main
-from .finetune import SummarizationModule, main
-from .test_seq2seq_examples import CUDA_AVAILABLE, MBART_TINY
-from .utils import load_json
+from utils import load_json
 
 
 MODEL_NAME = MBART_TINY

examples/seq2seq/test_seq2seq_examples.py

@@ -12,16 +12,15 @@ import pytorch_lightning as pl
 import torch
 
 import lightning_base
+from convert_pl_checkpoint_to_hf import convert_pl_to_hf
+from distillation import distill_main, evaluate_checkpoint
+from finetune import SummarizationModule, main
+from run_eval import generate_summaries_or_translations, run_generate
+from run_eval_search import run_search
 from transformers import AutoConfig, AutoModelForSeq2SeqLM
 from transformers.hf_api import HfApi
 from transformers.testing_utils import CaptureStderr, CaptureStdout, require_multigpu, require_torch_and_cuda, slow
-
-from .convert_pl_checkpoint_to_hf import convert_pl_to_hf
-from .distillation import distill_main, evaluate_checkpoint
-from .finetune import SummarizationModule, main
-from .run_eval import generate_summaries_or_translations, run_generate
-from .run_eval_search import run_search
-from .utils import label_smoothed_nll_loss, lmap, load_json
+from utils import label_smoothed_nll_loss, lmap, load_json
 
 
 logging.basicConfig(level=logging.DEBUG)