[PT FE] Enable PyTorch tests on ARM CPU

.github/dockerfiles/docker_tag

@@ -1 +1 @@
-pr-28972
+pr-29664

.github/dockerfiles/ov_test/ubuntu_20_04_arm64/Dockerfile

@@ -30,6 +30,13 @@ RUN apt-get update && \
         python3.11-venv \
         python3.11-distutils \
         libhdf5-dev \
+        # libGL for PyTorch Models tests
+        ffmpeg  \
+        libsm6  \
+        libxext6 \
+        libgl1 \
+        libgl1-mesa-glx \
+        libglib2.0-0 \
         && \
     rm -rf /var/lib/apt/lists/*
 

.github/workflows/linux_arm64.yml

@@ -239,9 +239,8 @@ jobs:
 
   PyTorch_Models_Tests:
     name: PyTorch Models tests
-    if: ${{ 'false' }} # TODO: Enable once the dependencies are ready for arm (no tensorflow-text available for arm from PyPI)
-    # if: fromJSON(needs.smart_ci.outputs.affected_components).PyTorch_FE.test
-    needs: [ Build, Docker, Smart_CI ]
+    if: fromJSON(needs.smart_ci.outputs.affected_components).PyTorch_FE.test
+    needs: [ Build, Docker, Smart_CI, Openvino_tokenizers ]
     uses: ./.github/workflows/job_pytorch_models_tests.yml
     with:
       runner: 'aks-linux-16-cores-32gb-arm'

tests/model_hub_tests/pytorch/test_aliked.py

@@ -3,6 +3,7 @@
 
 import math
 import os
+import platform
 import subprocess
 import sys
 import tempfile
@@ -120,9 +121,15 @@ def teardown_class(self):
         # remove all downloaded files from cache
         self.repo_dir.cleanup()
 
+    def get_supported_precommit_models():
+        models = []
+        if platform.machine() not in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']:
+            models.extend(['aliked-n16rot'])
+        return models
+
     @pytest.mark.nightly
     @pytest.mark.precommit
-    @pytest.mark.parametrize("name", ['aliked-n16rot'])
+    @pytest.mark.parametrize("name", get_supported_precommit_models())
     def test_convert_model_all_models_default(self, name, ie_device):
         self.run(name, None, ie_device)
 

tests/model_hub_tests/pytorch/test_detectron2.py

@@ -4,6 +4,7 @@
 import os
 import sys
 import subprocess
+import platform
 import pytest
 import torch
 from models_hub_common.utils import get_models_list, compare_two_tensors
@@ -94,6 +95,8 @@ def teardown_class(self):
                              get_models_list(os.path.join(os.path.dirname(__file__), "detectron2_precommit")))
     @pytest.mark.precommit
     def test_detectron2_precommit(self, name, type, mark, reason, ie_device):
+        if platform.machine() in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']:
+            pytest.skip("Detectron2 models are not enabled on ARM")
         self.run(name, None, ie_device)
 
     @pytest.mark.parametrize("name",

tests/model_hub_tests/pytorch/test_easyocr.py

@@ -1,6 +1,7 @@
 # Copyright (C) 2018-2025 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+import platform
 import pytest
 import torch
 
@@ -29,4 +30,6 @@ def load_model(self, model_name, model_link):
     @pytest.mark.nightly
     @pytest.mark.parametrize("name", ["detector", "recognizer"])
     def test_convert_model(self, name, ie_device):
+        if platform.machine() in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']:
+            pytest.skip("EasyOCR models are not enabled on ARM")
         self.run(name, None, ie_device)

tests/model_hub_tests/pytorch/test_hf_transformers.py

@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import os
+import platform
 
 from datasets import Audio, load_dataset
 from huggingface_hub import hf_hub_download, model_info
@@ -525,13 +526,17 @@ def load_model_with_default_class(name, **kwargs):
                                            ])
     @pytest.mark.precommit
     def test_convert_model_precommit(self, name, type, ie_device):
+        if platform.machine() in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']:
+            pytest.skip("hf_transformers models are not enabled on ARM")
         self.run(model_name=name, model_link=type, ie_device=ie_device)
 
     @pytest.mark.parametrize("name,type", [("bert-base-uncased", "bert"),
                                            ("openai/clip-vit-large-patch14", "clip"),
                                            ])
     @pytest.mark.precommit
     def test_convert_model_precommit_export(self, name, type, ie_device):
+        if platform.machine() in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']:
+            pytest.skip("hf_transformers models are not enabled on ARM")
         self.mode = "export"
         self.run(model_name=name, model_link=type, ie_device=ie_device)
 

tests/model_hub_tests/pytorch/test_llm.py

@@ -5,6 +5,7 @@
 import inspect
 
 import numpy as np
+import platform
 import pytest
 import torch
 from transformers import AutoConfig, AutoTokenizer, AutoModelForCausalLM
@@ -237,12 +238,19 @@ def get_pkv(model, tokenizer):
 
         return pkv, for_pkv["attention_mask"]
 
-    @pytest.mark.parametrize("type,name", [
-        ("opt_gptq", "katuni4ka/opt-125m-gptq"),
-        ("llama", "TinyLlama/TinyLlama-1.1B-Chat-v1.0"),
-        ("gpt2", "openai-community/gpt2"),
-        ("llama_awq", "casperhansen/tinyllama-1b-awq")
-    ])
+    def get_supported_precommit_models():
+        models = [
+            ("gpt2", "openai-community/gpt2"),
+        ]
+        if platform.machine() not in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']:
+            models.extend([
+                ("opt_gptq", "katuni4ka/opt-125m-gptq"),
+                ("llama", "TinyLlama/TinyLlama-1.1B-Chat-v1.0"),
+                ("llama_awq", "casperhansen/tinyllama-1b-awq"),
+            ])
+        return models
+
+    @pytest.mark.parametrize("type,name", get_supported_precommit_models())
     @pytest.mark.precommit
     @pytest.mark.nightly
     def test_convert_model_precommit(self, name, type, ie_device):

tests/model_hub_tests/pytorch/test_timm.py

@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import os
+import platform
 
 import pytest
 import timm
@@ -70,13 +71,22 @@ def infer_fw_model(self, model_obj, inputs):
             fw_outputs = [fw_outputs.numpy(force=True)]
         return fw_outputs
 
-    @pytest.mark.parametrize("name", ["mobilevitv2_050.cvnets_in1k",
-                                      "poolformerv2_s12.sail_in1k",
-                                      "vit_base_patch8_224.augreg_in21k",
-                                      "beit_base_patch16_224.in22k_ft_in22k",
-                                      "sequencer2d_l.in1k",
-                                      "gcresnext26ts.ch_in1k",
-                                      "volo_d2_224.sail_in1k"])
+    def get_supported_precommit_models():
+        models = [
+            "mobilevitv2_050.cvnets_in1k",
+            "poolformerv2_s12.sail_in1k",
+            "sequencer2d_l.in1k",
+        ]
+        if platform.machine() not in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']:
+            models.extend([
+                "beit_base_patch16_224.in22k_ft_in22k",
+                "gcresnext26ts.ch_in1k",
+                "vit_base_patch8_224.augreg_in21k",
+                "volo_d2_224.sail_in1k",
+            ])
+        return models
+
+    @pytest.mark.parametrize("name", get_supported_precommit_models())
     @pytest.mark.precommit
     def test_convert_model_precommit(self, name, ie_device):
         self.mode = "trace"

tests/model_hub_tests/pytorch/test_torchvision_models.py

@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import os
+import platform
 import tempfile
 
 import pytest
@@ -98,11 +99,19 @@ def infer_fw_model(self, model_obj, inputs):
             fw_outputs = [fw_outputs.numpy(force=True)]
         return fw_outputs
 
-    @pytest.mark.parametrize("model_name", ["efficientnet_b7",
-                                            "raft_small",
-                                            "swin_v2_s",
-                                            "quantized_mobilenet_v3_large",
-                                            ])
+    def get_supported_precommit_models():
+        models = [
+            "efficientnet_b7",
+        ]
+        if platform.machine() not in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']:
+            models.extend([
+                "raft_small",
+                "swin_v2_s",
+                "quantized_mobilenet_v3_large",
+            ])
+        return models
+
+    @pytest.mark.parametrize("model_name", get_supported_precommit_models())
     @pytest.mark.precommit
     def test_convert_model_precommit(self, model_name, ie_device):
         self.mode = "trace"

tests/model_hub_tests/transformation_tests/test_pa_transformation.py

@@ -112,6 +112,8 @@ def run_pa(tmp_path,
 def test_pa_precommit(tmp_path, model_name, model_link, mark, reason, ie_device):
     assert mark is None or mark == 'skip' or mark == 'xfail', \
         "Incorrect test case: {}, {}".format(model_name, model_link)
+    if platform.machine() in ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']:
+        pytest.skip("PagedAttention tests are not enabled on ARM")
     if mark == 'skip':
         pytest.skip(reason)
     elif mark == 'xfail':