Fix CI

Author: javiermtorres

.github/workflows/ci.yml

@@ -60,11 +60,6 @@ jobs:
       - name: Project setup
         uses: ./.github/actions/project-setup
 
-      - name: Install test dependencies
-        run: make setup
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
-
       - name: Install llvm-tools-preview
         run: rustup component add llvm-tools-preview
 
@@ -116,11 +111,6 @@ jobs:
         with:
           toolchain: nightly
 
-      - name: Install test dependencies
-        run: make setup
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
-      
       - run: rustup component add --toolchain nightly-x86_64-unknown-linux-gnu clippy
 
       - name: Run Clippy

scripts/create_dummy_model.py

@@ -38,7 +38,7 @@
 DUMMY_SEQUENCE_CLASSIFIER = "mozilla-ai/test-dummy-sequence-classifier"
 DUMMY_TOKEN_CLASSIFIER = "mozilla-ai/test-dummy-token-classifier"
 DUMMY_SEQUENCE_EMBEDDINGS = "mozilla-ai/test-dummy-sequence-embeddings"
-DUMMY_TOKEN_EMBEDDINGS= "mozilla-ai/test-dummy-token-embeddings"
+DUMMY_TOKEN_EMBEDDINGS = "mozilla-ai/test-dummy-token-embeddings"
 
 SEQUENCE_CLASSIFIER_OUTPUT_DIR = "./models/dummy_electra_sequence_classifier"
 TOKEN_CLASSIFIER_OUTPUT_DIR = "./models/dummy_electra_token_classifier"
@@ -134,7 +134,6 @@ def get_loss_logits(
         labels=None,
         return_dict=None,
     ):
-
         """Forward pass that returns fixed logits for each sequence."""
 
         return_dict = (
@@ -529,9 +528,7 @@ def load_dummy_sequence_classifier(model_dir: str, num_labels: int):
 def load_dummy_sequence_embeddings(model_dir: str):
     """Load a dummy sequence classification model from directory."""
     AutoConfig.register(DUMMY_SEQUENCE_EMBEDDINGS, DummySequenceEmbedConfig)
-    AutoModel.register(
-        DummySequenceEmbedConfig, DummySequenceEmbeddings
-    )
+    AutoModel.register(DummySequenceEmbedConfig, DummySequenceEmbeddings)
     config = AutoConfig.from_pretrained(model_dir)
     model = AutoModel.from_pretrained(model_dir, config=config)
     tokenizer = AutoTokenizer.from_pretrained(model_dir)
@@ -541,7 +538,9 @@ def load_dummy_sequence_embeddings(model_dir: str):
 def load_dummy_token_classifier(model_dir: str, num_labels: int):
     """Load a dummy token classification model from directory."""
     AutoConfig.register(DUMMY_TOKEN_CLASSIFIER, DummyTokenClassConfig)
-    AutoModelForTokenClassification.register(DummyTokenClassConfig, DummyTokenClassifier)
+    AutoModelForTokenClassification.register(
+        DummyTokenClassConfig, DummyTokenClassifier
+    )
     config = AutoConfig.from_pretrained(model_dir, num_labels=num_labels)
     model = AutoModelForTokenClassification.from_pretrained(model_dir, config=config)
     tokenizer = AutoTokenizer.from_pretrained(model_dir)
@@ -753,7 +752,12 @@ def test_dummy_token_embeddings(output_dir: str):
 
 
 # CLI Options
-VALID_MODEL_TYPES = ["sequence_classifier", "token_classifier", "sequence_embeddings", "token_embeddings"]
+VALID_MODEL_TYPES = [
+    "sequence_classifier",
+    "token_classifier",
+    "sequence_embeddings",
+    "token_embeddings",
+]
 
 # Reusable option decorator for model class
 model_type_option = click.option(

scripts/download_test_models.py

@@ -8,10 +8,14 @@
     ORTModelForTokenClassification,
 )
 from create_dummy_model import (
-    DummySequenceConfig,
-    DummyTokenConfig,
-    DUMMY_SEQUENCE_ENCODER,
-    DUMMY_TOKEN_ENCODER,
+    DummySequenceClassConfig,
+    DummyTokenClassConfig,
+    DummySequenceEmbedConfig,
+    DummyTokenEmbedConfig,
+    DUMMY_SEQUENCE_CLASSIFIER,
+    DUMMY_TOKEN_CLASSIFIER,
+    DUMMY_SEQUENCE_EMBEDDINGS,
+    DUMMY_TOKEN_EMBEDDINGS,
 )
 
 MODELS_DIR = "models/"
@@ -50,8 +54,10 @@ def download_export_models(
         ORTModelForTokenClassification,
     )
 
-    AutoConfig.register(DUMMY_SEQUENCE_ENCODER, DummySequenceConfig)
-    AutoConfig.register(DUMMY_TOKEN_ENCODER, DummyTokenConfig)
+    AutoConfig.register(DUMMY_SEQUENCE_CLASSIFIER, DummySequenceClassConfig)
+    AutoConfig.register(DUMMY_TOKEN_CLASSIFIER, DummyTokenClassConfig)
+    AutoConfig.register(DUMMY_SEQUENCE_EMBEDDINGS, DummySequenceEmbedConfig)
+    AutoConfig.register(DUMMY_TOKEN_EMBEDDINGS, DummyTokenEmbedConfig)
     # save dummy models
     download_export_models(
         "mozilla-ai/test-dummy-sequence-encoder",