test inference

tests/test_inference.py

@@ -0,0 +1,26 @@
+import pytest
+import torch
+import numpy as np
+
+from enhancer.inference import Inference
+
+
+@pytest.mark.parametrize("audio",["tests/data/vctk/clean_testset_wav/p257_166.wav",torch.rand(1,2,48000)])
+def test_read_input(audio):
+
+    read_audio = Inference.read_input(audio,48000,16000)
+    assert isinstance(read_audio,torch.Tensor)
+    assert read_audio.shape[0] == 1
+
+def test_batchify():
+    rand = torch.rand(1,1000)
+    batched_rand = Inference.batchify(rand, window_size = 100, step_size=100)
+    assert batched_rand.shape[0] == 12
+
+def test_aggregate():
+    rand = torch.rand(12,1,100)
+    agg_rand = Inference.aggreagate(data=rand,window_size=100,total_frames=1000,step_size=100)
+    assert agg_rand.shape[-1] == 1000
+
+
+