Add owner and group field to forge properties

forge/test/conftest.py

@@ -174,7 +174,7 @@ def record_forge_property(record_property):
 
     This fixture:
       1. Instantiates a ForgePropertyStore.
-      2. Adds a default property ("tags.frontend": "tt-forge-fe").
+      2. Adds a default property ("owner": "tt-forge-fe").
       3. Yields the store for use in tests.
       4. After the test, fetches execution phase and stage, updates the store,
          and then records each top-level property using the provided record_property function.
@@ -183,7 +183,7 @@ def record_forge_property(record_property):
     forge_property_store = ForgePropertyStore()
 
     # Add a default property.
-    forge_property_store.add("tags.frontend", "tt-forge-fe")
+    forge_property_store.add("owner", "tt-forge-fe")
 
     # Provide the store to the test function.
     yield forge_property_store

forge/test/models/pytorch/audio/stereo/test_stereo.py

@@ -34,6 +34,7 @@ def test_stereo(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     framework_model, processor = load_model(variant)

forge/test/models/pytorch/audio/whisper/test_whisper.py

@@ -40,6 +40,7 @@ def test_whisper(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load model (with tokenizer and feature extractor)

forge/test/models/pytorch/audio/whisper/test_whisper_large_v3.py

@@ -52,6 +52,7 @@ def test_whisper_large_v3_speech_translation(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     processor = WhisperProcessor.from_pretrained(variant)

forge/test/models/pytorch/multimodal/clip/test_clip.py

@@ -28,6 +28,7 @@ def test_clip_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load processor and model from HuggingFace

forge/test/models/pytorch/multimodal/deepseek_math/test_deepseek_math.py

@@ -35,6 +35,7 @@ def test_deepseek_inference(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     model_name = f"deepseek-ai/{variant}"

forge/test/models/pytorch/multimodal/llava/test_llava.py

@@ -50,6 +50,7 @@ def test_llava(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     framework_model, processor = load_model(variant)

forge/test/models/pytorch/multimodal/stable_diffusion/test_stable_diffusion.py

@@ -19,6 +19,7 @@ def test_stable_diffusion_pytorch(record_forge_property, variant):
     module_name = build_module_name(framework=Framework.PYTORCH, model="stable_diffusion", variant=variant)
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     batch_size = 1

forge/test/models/pytorch/multimodal/stable_diffusion/test_stable_diffusion_xl.py

@@ -44,6 +44,7 @@ def test_stable_diffusion_generation(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load the pipeline and set it to use the CPU

forge/test/models/pytorch/multimodal/vilt/test_vilt.py

@@ -65,6 +65,7 @@ def test_vilt_question_answering_hf_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     framework_model, inputs, model = generate_model_vilt_question_answering_hf_pytorch(variant)
@@ -122,6 +123,7 @@ def test_vilt_maskedlm_hf_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     framework_model, inputs, _ = generate_model_vilt_maskedlm_hf_pytorch(variant)

forge/test/models/pytorch/text/albert/test_albert.py

@@ -51,6 +51,7 @@ def test_albert_masked_lm_pytorch(record_forge_property, size, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     model_ckpt = f"albert-{size}-{variant}"
@@ -123,6 +124,7 @@ def test_albert_token_classification_pytorch(record_forge_property, size, varian
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # NOTE: These model variants are pre-trined only. They need to be fine-tuned
@@ -181,6 +183,7 @@ def test_albert_question_answering_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load Albert tokenizer and model from HuggingFace
@@ -217,6 +220,7 @@ def test_albert_sequence_classification_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load Albert tokenizer and model from HuggingFace

forge/test/models/pytorch/text/bart/test_bart.py

@@ -37,6 +37,7 @@ def test_pt_bart_classifier(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     model = download_model(BartForSequenceClassification.from_pretrained, variant, torchscript=True)

forge/test/models/pytorch/text/bert/test_bert.py

@@ -28,6 +28,7 @@ def test_bert_masked_lm_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load Bert tokenizer and model from HuggingFace
@@ -112,6 +113,7 @@ def test_bert_question_answering_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     framework_model, inputs, tokenizer = generate_model_bert_qa_hf_pytorch(variant)
@@ -174,6 +176,7 @@ def test_bert_sequence_classification_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     framework_model, inputs, _ = generate_model_bert_seqcls_hf_pytorch(variant)
@@ -226,6 +229,7 @@ def test_bert_token_classification_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     framework_model, inputs, _ = generate_model_bert_tkcls_hf_pytorch(variant)

forge/test/models/pytorch/text/bloom/test_bloom.py

@@ -37,6 +37,7 @@ def test_bloom(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load tokenizer and model from HuggingFace

forge/test/models/pytorch/text/codegen/test_codegen.py

@@ -32,6 +32,7 @@ def test_codegen(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load model (with tokenizer)

forge/test/models/pytorch/text/distilbert/test_distilbert.py

@@ -31,6 +31,7 @@ def test_distilbert_masked_lm_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load DistilBert tokenizer and model from HuggingFace
@@ -73,6 +74,7 @@ def test_distilbert_question_answering_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load Bert tokenizer and model from HuggingFace
@@ -125,6 +127,7 @@ def test_distilbert_sequence_classification_pytorch(record_forge_property, varia
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load DistilBert tokenizer and model from HuggingFace
@@ -167,6 +170,7 @@ def test_distilbert_token_classification_pytorch(record_forge_property, variant)
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load DistilBERT tokenizer and model from HuggingFace

forge/test/models/pytorch/text/dpr/test_dpr.py

@@ -42,6 +42,7 @@ def test_dpr_context_encoder_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load Bert tokenizer and model from HuggingFace
@@ -96,6 +97,7 @@ def test_dpr_question_encoder_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load Bert tokenizer and model from HuggingFace
@@ -155,6 +157,7 @@ def test_dpr_reader_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load Bert tokenizer and model from HuggingFace

forge/test/models/pytorch/text/falcon/test_falcon.py

@@ -22,6 +22,7 @@ def test_falcon(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     tokenizer = AutoTokenizer.from_pretrained(variant)
@@ -69,6 +70,7 @@ def test_falcon_3(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     tokenizer = AutoTokenizer.from_pretrained(variant)

forge/test/models/pytorch/text/fuyu/test_fuyu_8b.py

@@ -33,6 +33,7 @@ def test_fuyu8b(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     config = FuyuConfig.from_pretrained(variant)

forge/test/models/pytorch/text/gemma/test_gemma_2b.py

@@ -32,6 +32,7 @@ def test_gemma_2b(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Random see for reproducibility

forge/test/models/pytorch/text/gpt2/test_gpt2.py

@@ -36,6 +36,7 @@ def test_gpt2_text_gen(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load tokenizer and model from HuggingFace
@@ -75,6 +76,7 @@ def test_gpt2_sequence_classification(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load tokenizer and model from HuggingFace

forge/test/models/pytorch/text/gptneo/test_gptneo.py

@@ -35,6 +35,7 @@ def test_gptneo_causal_lm(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Set random seed for repeatability
@@ -101,6 +102,7 @@ def test_gptneo_sequence_classification(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load tokenizer and model from HuggingFace

forge/test/models/pytorch/text/llama/test_llama3.py

@@ -141,6 +141,7 @@ def test_llama3_causal_lm(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load model (with tokenizer)
@@ -201,6 +202,7 @@ def test_llama3_sequence_classification(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load model (with tokenizer)

forge/test/models/pytorch/text/mamba/test_mamba.py

@@ -45,6 +45,7 @@ def test_mamba(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load tokenizer and model from HuggingFace

forge/test/models/pytorch/text/mistral/test_mistral.py

@@ -24,6 +24,7 @@ def test_mistral(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     configuration = MistralConfig()

forge/test/models/pytorch/text/nanogpt/test_nanogpt.py

@@ -36,6 +36,7 @@ def test_nanogpt_text_generation(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load the model

forge/test/models/pytorch/text/opt/test_opt.py

@@ -31,6 +31,7 @@ def test_opt_causal_lm(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load tokenizer and model from HuggingFace
@@ -81,6 +82,7 @@ def test_opt_qa(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load tokenizer and model from HuggingFace
@@ -131,6 +133,7 @@ def test_opt_sequence_classification(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load tokenizer and model from HuggingFace

forge/test/models/pytorch/text/perceiverio/test_perceiverio.py

@@ -28,6 +28,7 @@ def test_perceiverio_masked_lm_pytorch(record_forge_property, variant):
     )
 
     # Record Forge Property
+    record_forge_property("group", "generality")
     record_forge_property("tags.model_name", module_name)
 
     # Load model and tokenizer