Migrate metric to Evaluate library for tensorflow examples (#18327)
* Migrate metric to Evaluate library in tf examples Currently tensorflow examples use `load_metric` function from Datasets library , commit migrates function call to `load` function to Evaluate library. Fix for #18306 * Migrate metric to Evaluate library in tf examples Currently tensorflow examples use `load_metric` function from Datasets library , commit migrates function call to `load` function to Evaluate library. Fix for #18306 * Migrate `metric` to Evaluate for all tf examples Currently tensorflow examples use `load_metric` function from Datasets library , commit migrates function call to `load` function to Evaluate library.
This commit is contained in:
parent
7b0908769b
commit
a2586795e5
|
@ -1,2 +1,3 @@
|
|||
datasets >= 1.4.0
|
||||
tensorflow >= 2.3.0
|
||||
evaluate >= 0.2.0
|
|
@ -26,8 +26,9 @@ from pathlib import Path
|
|||
from typing import Optional
|
||||
|
||||
import tensorflow as tf
|
||||
from datasets import load_dataset, load_metric
|
||||
from datasets import load_dataset
|
||||
|
||||
import evaluate
|
||||
import transformers
|
||||
from transformers import (
|
||||
AutoConfig,
|
||||
|
@ -600,7 +601,7 @@ def main():
|
|||
references = [{"id": ex["id"], "answers": ex[answer_column_name]} for ex in examples]
|
||||
return EvalPrediction(predictions=formatted_predictions, label_ids=references)
|
||||
|
||||
metric = load_metric("squad_v2" if data_args.version_2_with_negative else "squad")
|
||||
metric = evaluate.load("squad_v2" if data_args.version_2_with_negative else "squad")
|
||||
|
||||
def compute_metrics(p: EvalPrediction):
|
||||
return metric.compute(predictions=p.predictions, references=p.label_ids)
|
||||
|
|
|
@ -0,0 +1,3 @@
|
|||
datasets >= 1.4.0
|
||||
tensorflow >= 2.3.0
|
||||
evaluate >= 0.2.0
|
|
@ -29,9 +29,10 @@ import datasets
|
|||
import nltk # Here to have a nice missing dependency error message early on
|
||||
import numpy as np
|
||||
import tensorflow as tf
|
||||
from datasets import load_dataset, load_metric
|
||||
from datasets import load_dataset
|
||||
from tqdm import tqdm
|
||||
|
||||
import evaluate
|
||||
import transformers
|
||||
from filelock import FileLock
|
||||
from transformers import (
|
||||
|
@ -634,7 +635,7 @@ def main():
|
|||
# endregion
|
||||
|
||||
# region Metric
|
||||
metric = load_metric("rouge")
|
||||
metric = evaluate.load("rouge")
|
||||
# endregion
|
||||
|
||||
# region Training
|
||||
|
|
|
@ -1,4 +1,5 @@
|
|||
datasets >= 1.1.3
|
||||
sentencepiece != 0.1.92
|
||||
protobuf
|
||||
tensorflow >= 2.3
|
||||
tensorflow >= 2.3
|
||||
evaluate >= 0.2.0
|
|
@ -24,8 +24,9 @@ from typing import Optional
|
|||
|
||||
import numpy as np
|
||||
import tensorflow as tf
|
||||
from datasets import load_dataset, load_metric
|
||||
from datasets import load_dataset
|
||||
|
||||
import evaluate
|
||||
import transformers
|
||||
from transformers import (
|
||||
AutoConfig,
|
||||
|
@ -366,7 +367,7 @@ def main():
|
|||
# endregion
|
||||
|
||||
# region Metric function
|
||||
metric = load_metric("glue", data_args.task_name)
|
||||
metric = evaluate.load("glue", data_args.task_name)
|
||||
|
||||
def compute_metrics(preds, label_ids):
|
||||
preds = preds["logits"]
|
||||
|
|
|
@ -0,0 +1,3 @@
|
|||
datasets >= 1.4.0
|
||||
tensorflow >= 2.3.0
|
||||
evaluate >= 0.2.0
|
|
@ -27,8 +27,9 @@ from typing import Optional
|
|||
import datasets
|
||||
import numpy as np
|
||||
import tensorflow as tf
|
||||
from datasets import ClassLabel, load_dataset, load_metric
|
||||
from datasets import ClassLabel, load_dataset
|
||||
|
||||
import evaluate
|
||||
import transformers
|
||||
from transformers import (
|
||||
CONFIG_MAPPING,
|
||||
|
@ -478,7 +479,7 @@ def main():
|
|||
# endregion
|
||||
|
||||
# Metrics
|
||||
metric = load_metric("seqeval")
|
||||
metric = evaluate.load("seqeval")
|
||||
|
||||
def get_labels(y_pred, y_true):
|
||||
# Transform predictions and references tensos to numpy arrays
|
||||
|
|
|
@ -0,0 +1,3 @@
|
|||
datasets >= 1.4.0
|
||||
tensorflow >= 2.3.0
|
||||
evaluate >= 0.2.0
|
|
@ -28,9 +28,10 @@ from typing import Optional
|
|||
import datasets
|
||||
import numpy as np
|
||||
import tensorflow as tf
|
||||
from datasets import load_dataset, load_metric
|
||||
from datasets import load_dataset
|
||||
from tqdm import tqdm
|
||||
|
||||
import evaluate
|
||||
import transformers
|
||||
from transformers import (
|
||||
AutoConfig,
|
||||
|
@ -590,7 +591,7 @@ def main():
|
|||
# endregion
|
||||
|
||||
# region Metric and postprocessing
|
||||
metric = load_metric("sacrebleu")
|
||||
metric = evaluate.load("sacrebleu")
|
||||
|
||||
def postprocess_text(preds, labels):
|
||||
preds = [pred.strip() for pred in preds]
|
||||
|
|
Loading…
Reference in New Issue