add batched speaker encoder inference

TTS/bin/compute_embeddings.py

@@ -2,7 +2,6 @@ import argparse
 import glob
 import os
 
-import numpy as np
 import torch
 from tqdm import tqdm
 

TTS/speaker_encoder/models/resnet.py

@@ -174,15 +174,17 @@ class ResNetSpeakerEncoder(nn.Module):
 
         offsets = np.linspace(0, max_len-num_frames, num=num_eval)
 
-        embeddings = []
+        frames_batch = []
         for offset in offsets:
             offset = int(offset)
             end_offset = int(offset+num_frames)
             frames = x[:, offset:end_offset]
-            embed = self.forward(frames, l2_norm=True)
-            embeddings.append(embed)
+            frames_batch.append(frames)
+
+        frames_batch = torch.cat(frames_batch, dim=0)
+        embeddings = self.forward(frames_batch, l2_norm=True)
 
-        embeddings = torch.stack(embeddings)
         if return_mean:
-            embeddings = torch.mean(embeddings, dim=0)
+            embeddings = torch.mean(embeddings, dim=0, keepdim=True)
+
         return embeddings