fix arm pipelines call

Author: eaidova

notebooks/llm-agent-react/llm-agent-react-langchain.ipynb

@@ -486,6 +486,11 @@
     "import openvino.properties.hint as hints\n",
     "import openvino.properties.streams as streams\n",
     "\n",
+    "import torch\n",
+    "\n",
+    "if hasattr(torch, \"mps\") and torch.mps.is_available:\n",
+    "    torch.mps.is_available = lambda: False\n",
+    "\n",
     "\n",
     "class StopSequenceCriteria(StoppingCriteria):\n",
     "    \"\"\"\n",

notebooks/multimodal-rag/multimodal-rag-llamaindex.ipynb

@@ -605,6 +605,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import torch\n",
+    "\n",
+    "if hasattr(torch, \"mps\") and torch.mps.is_available:\n",
+    "    torch.mps.is_available = lambda: False\n",
+    "\n",
     "from llama_index.core.indices import MultiModalVectorStoreIndex\n",
     "from llama_index.vector_stores.qdrant import QdrantVectorStore\n",
     "from llama_index.core import StorageContext, Settings\n",

notebooks/whisper-asr-genai/whisper-asr-genai.ipynb

@@ -243,6 +243,7 @@
    "source": [
     "from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq, pipeline\n",
     "from transformers.utils import logging\n",
+    "import torch\n",
     "\n",
     "processor = AutoProcessor.from_pretrained(model_id.value)\n",
     "\n",
@@ -253,7 +254,7 @@
     "    model=pt_model,\n",
     "    tokenizer=processor.tokenizer,\n",
     "    feature_extractor=processor.feature_extractor,\n",
-    "    device=\"cpu\",\n",
+    "    device=torch.device(\"cpu\"),\n",
     ")"
    ]
   },
@@ -1017,7 +1018,9 @@
     "      model=ov_model,\n",
     "      chunk_length_s=30,\n",
     "      tokenizer=ov_processor.tokenizer,\n",
-    "      feature_extractor=ov_processor.feature_extractor)\n",
+    "      feature_extractor=ov_processor.feature_extractor,\n",
+    "      device=torch.device(\"cpu\")\n",
+    "      )\n",
     "    try:\n",
     "        calibration_dataset = dataset = load_dataset(\"openslr/librispeech_asr\", \"clean\", split=\"validation\", streaming=True, trust_remote_code=True)\n",
     "        for sample in tqdm(islice(calibration_dataset, calibration_dataset_size), desc=\"Collecting calibration data\",\n",

notebooks/whisper-subtitles-generation/whisper-subtitles-generation.ipynb

@@ -763,7 +763,7 @@
     "      model=ov_model,\n",
     "      chunk_length_s=30,\n",
     "      tokenizer=processor.tokenizer,\n",
-    "      feature_extractor=processor.feature_extractor)\n",
+    "      feature_extractor=processor.feature_extractor, devide=torch.device(\"cpu\"))\n",
     "    try:\n",
     "        calibration_dataset = dataset = load_dataset(\"openslr/librispeech_asr\", \"clean\", split=\"validation\", streaming=True, trust_remote_code=True)\n",
     "        for sample in tqdm(islice(calibration_dataset, calibration_dataset_size), desc=\"Collecting calibration data\",\n",