Added test for AutoModelForCTC class.

Signed-off-by: Tanisha Chawada <[email protected]>

Author: tchawada

tests/transformers/models/test_audio_embedding_models.py

@@ -7,13 +7,15 @@
 
 import os
 from typing import List, Optional
+
 import numpy as np
 import onnx
 import onnxruntime
 import pytest
 import torch
 from datasets import load_dataset
 from transformers import AutoModelForCTC, AutoProcessor
+
 from QEfficient.transformers.models.modeling_auto import QEFFAutoModelForCTC
 from QEfficient.transformers.quantizers.auto import replace_transformers_quantizers
 from QEfficient.utils import hf_download
@@ -147,18 +149,16 @@ def check_CTC_pytorch_vs_kv_vs_ort_vs_ai100(
     data = ds[0]["audio"]["array"]
     data = torch.tensor(data).unsqueeze(0).numpy()
     sample_rate = ds[0]["audio"]["sampling_rate"]
-    pytorch_tokens=run_CTC_pytorch_hf(model_hf, processor, data, sample_rate)
+    pytorch_tokens = run_CTC_pytorch_hf(model_hf, processor, data, sample_rate)
     predicted_ids = torch.argmax(pytorch_tokens, dim=-1)
     pytorch_output = processor.batch_decode(predicted_ids)
-    
+
     qeff_model = QEFFAutoModelForCTC(model_hf, pretrained_model_name_or_path=model_name)
     qeff_model.export()
-    ort_tokens=run_CTC_ort(qeff_model.onnx_path, qeff_model.model.config, processor, data, sample_rate)
+    ort_tokens = run_CTC_ort(qeff_model.onnx_path, qeff_model.model.config, processor, data, sample_rate)
     predicted_ids = torch.argmax(ort_tokens, dim=-1)
     ort_output = processor.batch_decode(predicted_ids)
-    assert (pytorch_output == ort_output), (
-        "Tokens don't match for pytorch output and ORT output."
-    )
+    assert pytorch_output == ort_output, "Tokens don't match for pytorch output and ORT output."
     if not get_available_device_id():
         pytest.skip("No available devices to run model on Cloud AI 100")
     qeff_model.compile(
@@ -168,11 +168,8 @@ def check_CTC_pytorch_vs_kv_vs_ort_vs_ai100(
         qnn_config=qnn_config,
     )
     cloud_ai_100_output = qeff_model.generate(processor, data)
-    assert (pytorch_output == cloud_ai_100_output), (
-        "Tokens don't match for pytorch output and Cloud AI 100 output."
-    )
+    assert pytorch_output == cloud_ai_100_output, "Tokens don't match for pytorch output and Cloud AI 100 output."
     assert os.path.isfile(os.path.join(os.path.dirname(qeff_model.qpc_path), "qconfig.json"))
-    
 
 
 @pytest.mark.on_qaic