diff --git a/airio/examples/inspect.ipynb b/airio/examples/inspect.ipynb index cc4ea85..b031bec 100644 --- a/airio/examples/inspect.ipynb +++ b/airio/examples/inspect.ipynb @@ -79,7 +79,7 @@ }, "outputs": [], "source": [ - "def _imdb_preprocessor(raw_example: Dict[str, bytes]) -\u003e Dict[str, str]:\n", + "def _imdb_preprocessor(raw_example: Dict[str, bytes]) -> Dict[str, str]:\n", " final_example = {\"inputs\": \"imdb \" + raw_example[\"text\"].decode(\"utf-8\")}\n", " raw_label = str(raw_example[\"label\"])\n", " if raw_label == \"0\":\n", @@ -259,7 +259,7 @@ " print(f\" {k}: {v}\")\n", " print(f\" -------------------------\")\n", " count += 1\n", - " if count \u003e= airio.dataset_providers.DEFAULT_NUM_RECORDS_TO_INSPECT:\n", + " if count >= airio.dataset_providers.DEFAULT_NUM_RECORDS_TO_INSPECT:\n", " break" ] }, diff --git a/airio/examples/quickstart.ipynb b/airio/examples/quickstart.ipynb index 6c967f6..a1cfe50 100644 --- a/airio/examples/quickstart.ipynb +++ b/airio/examples/quickstart.ipynb @@ -81,7 +81,7 @@ }, "outputs": [], "source": [ - "def _imdb_preprocessor(raw_example: Dict[str, bytes]) -\u003e Dict[str, str]:\n", + "def _imdb_preprocessor(raw_example: Dict[str, bytes]) -> Dict[str, str]:\n", " final_example = {\"inputs\": \"imdb \" + raw_example[\"text\"].decode(\"utf-8\")}\n", " raw_label = str(raw_example[\"label\"])\n", " if raw_label == \"0\":\n", @@ -167,7 +167,7 @@ " print(f\" {k}: {v}\")\n", " print(f\" -------------------------\")\n", " count += 1\n", - " if count \u003e= airio.dataset_providers.DEFAULT_NUM_RECORDS_TO_INSPECT:\n", + " if count >= airio.dataset_providers.DEFAULT_NUM_RECORDS_TO_INSPECT:\n", " break" ] } diff --git a/airio/examples/train_wmt.ipynb b/airio/examples/train_wmt.ipynb index 8ca0ad0..3611715 100644 --- a/airio/examples/train_wmt.ipynb +++ b/airio/examples/train_wmt.ipynb @@ -90,7 +90,7 @@ }, "outputs": [], "source": [ - "def get_t5_model(**config_overrides) -\u003e models.EncoderDecoderModel:\n", + "def get_t5_model(**config_overrides) -> models.EncoderDecoderModel:\n", " \"\"\"Returns a small T5 1.1 model.\"\"\"\n", " tiny_config = network.T5Config(\n", " vocab_size=32128,\n",