From 628abfe644488c5f16f9b59d27fb7c9bca8f0d9f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Eren=20G=C3=B6lge?= <egolge@coqui.ai>
Date: Tue, 27 Apr 2021 14:35:39 +0200
Subject: [PATCH] remove test

---
 tests/test_speakers_manager.py | 50 ----------------------------------
 1 file changed, 50 deletions(-)
 delete mode 100644 tests/test_speakers_manager.py

diff --git a/tests/test_speakers_manager.py b/tests/test_speakers_manager.py
deleted file mode 100644
index b98f990c..00000000
--- a/tests/test_speakers_manager.py
+++ /dev/null
@@ -1,50 +0,0 @@
-import os
-import unittest
-
-import numpy as np
-
-from tests import get_tests_input_path
-from TTS.tts.utils.speakers import SpeakerManager
-from TTS.utils.audio import AudioProcessor
-from TTS.utils.io import load_config
-
-encoder_config_path = os.path.join(get_tests_input_path(), "test_speaker_encoder_config.json")
-encoder_model_path = os.path.join(get_tests_input_path(), "dummy_speaker_encoder.pth.tar")
-sample_wav_path = os.path.join(get_tests_input_path(), "../data/ljspeech/wavs/LJ001-0001.wav")
-x_vectors_file_path = os.path.join(get_tests_input_path(), "../data/dummy_speakers.json")
-
-
-class SpeakerManagerTest(unittest.TestCase):
-    """Test SpeakerManager for loading embedding files and computing x_vectors from waveforms"""
-
-    @staticmethod
-    def test_speaker_embedding():
-        # load config
-        config = load_config(encoder_config_path)
-        config["audio"]["resample"] = True
-
-        # load audio processor and speaker encoder
-        ap = AudioProcessor(**config.audio)
-        manager = SpeakerManager(encoder_model_path=encoder_model_path, encoder_config_path=encoder_config_path)
-
-        # load a sample audio and compute embedding
-        waveform = ap.load_wav(sample_wav_path)
-        mel = ap.melspectrogram(waveform)
-        x_vector = manager.compute_x_vector(mel.T)
-        assert x_vector.shape[1] == 256
-
-    @staticmethod
-    def test_speakers_file_processing():
-        manager = SpeakerManager(x_vectors_file_path=x_vectors_file_path)
-        print(manager.num_speakers)
-        print(manager.x_vector_dim)
-        print(manager.clip_ids)
-        x_vector = manager.get_x_vector_by_clip(manager.clip_ids[0])
-        assert len(x_vector) == 256
-        x_vectors = manager.get_x_vectors_by_speaker(manager.speaker_ids[0])
-        assert len(x_vectors[0]) == 256
-        x_vector1 = manager.get_mean_x_vector(manager.speaker_ids[0], num_samples=2, randomize=True)
-        assert len(x_vector1) == 256
-        x_vector2 = manager.get_mean_x_vector(manager.speaker_ids[0], num_samples=2, randomize=False)
-        assert len(x_vector2) == 256
-        assert np.sum(np.array(x_vector1) - np.array(x_vector2)) != 0