Create test_irs.py to detect changes in tiny-model IRs

.gitattributes

@@ -0,0 +1,2 @@
+tests/openvino/reference_irs/**/*.bin filter=lfs diff=lfs merge=lfs -text
+tests/openvino/reference_irs/**/*.xml filter=lfs diff=lfs merge=lfs -text

.github/workflows/test_openvino.yml

@@ -39,15 +39,23 @@ jobs:
             "*diffusion*",
             "*quantization*",
             "*transformation*",
+            "*irs*",
           ]
         transformers-version: ["4.57.6", "latest"]
+        exclude:
+          - test-pattern: "*irs*"
+            transformers-version: "4.57.6"
 
     runs-on: ubuntu-22.04
 
     steps:
       - name: Checkout code
         uses: actions/checkout@v7.0.1
 
+      - name: Pull Git LFS files for IR tests
+        if: ${{ matrix.test-pattern == '*irs*' }}
+        run: git lfs pull
+
       - name: Setup Python
         uses: actions/setup-python@v7
         with:

tests/openvino/reference_irs/tiny-random-flux/metadata.json

@@ -0,0 +1,16 @@
+{
+  "model_id": "optimum-intel-internal-testing/tiny-random-flux",
+  "model_class": "OVDiffusionPipeline",
+  "transformers_version": "5.5.4",
+  "optimum_intel_version": "2.1.0.dev0+fd94990",
+  "openvino_version": "2026.2.1-21919-ede283a88e3-releases/2026/2",
+  "generated_date": "2026-08-03",
+  "notes": "FLUX diffusion pipeline - multiple IR components",
+  "components": [
+    "text_encoder",
+    "text_encoder_2",
+    "transformer",
+    "vae_decoder",
+    "vae_encoder"
+  ]
+}

tests/openvino/reference_irs/tiny-random-flux/model_index.json

@@ -0,0 +1,41 @@
+{
+  "_class_name": "FluxPipeline",
+  "_diffusers_version": "0.39.0",
+  "_name_or_path": "optimum-intel-internal-testing/tiny-random-flux",
+  "feature_extractor": [
+    null,
+    null
+  ],
+  "image_encoder": [
+    null,
+    null
+  ],
+  "scheduler": [
+    "diffusers",
+    "FlowMatchEulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "text_encoder_2": [
+    "transformers",
+    "T5EncoderModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "tokenizer_2": [
+    "transformers",
+    "T5Tokenizer"
+  ],
+  "transformer": [
+    "diffusers",
+    "FluxTransformer2DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

tests/openvino/reference_irs/tiny-random-flux/scheduler/scheduler_config.json

@@ -0,0 +1,18 @@
+{
+  "_class_name": "FlowMatchEulerDiscreteScheduler",
+  "_diffusers_version": "0.39.0",
+  "base_image_seq_len": 256,
+  "base_shift": 0.5,
+  "invert_sigmas": false,
+  "max_image_seq_len": 4096,
+  "max_shift": 1.15,
+  "num_train_timesteps": 1000,
+  "shift": 1.0,
+  "shift_terminal": null,
+  "stochastic_sampling": false,
+  "time_shift_type": "exponential",
+  "use_beta_sigmas": false,
+  "use_dynamic_shifting": false,
+  "use_exponential_sigmas": false,
+  "use_karras_sigmas": false
+}

tests/openvino/reference_irs/tiny-random-flux/text_encoder/config.json

@@ -0,0 +1,23 @@
+{
+  "architectures": [
+    "CLIPTextModel"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_size": 32,
+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 37,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 77,
+  "model_type": "clip_text_model",
+  "num_attention_heads": 4,
+  "num_hidden_layers": 5,
+  "pad_token_id": 1,
+  "projection_dim": 32,
+  "transformers_version": "5.5.4",
+  "vocab_size": 1000
+}

tests/openvino/reference_irs/tiny-random-flux/text_encoder_2/config.json

@@ -0,0 +1,34 @@
+{
+  "architectures": [
+    "T5Model"
+  ],
+  "bos_token_id": 0,
+  "classifier_dropout": 0.0,
+  "d_ff": 37,
+  "d_kv": 8,
+  "d_model": 32,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "relu",
+  "dropout_rate": 0.1,
+  "dtype": "float32",
+  "eos_token_id": 1,
+  "feed_forward_proj": "relu",
+  "gradient_checkpointing": false,
+  "initializer_factor": 0.002,
+  "is_decoder": false,
+  "is_encoder_decoder": false,
+  "is_gated_act": false,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "num_decoder_layers": 5,
+  "num_heads": 4,
+  "num_layers": 5,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 8,
+  "scale_decoder_outputs": true,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.5.4",
+  "use_cache": false,
+  "vocab_size": 32128
+}