Upload config.py

config.py

@@ -0,0 +1,517 @@
+class Config(object):
+    def __init__(self, config_dict: dict):
+        for key, val in config_dict.items():
+            if val is not None:
+                self.__setattr__(key, val)
+
+    def copy(self, new_config_dict={}):
+        ret = Config(vars(self))
+        for key, val in new_config_dict.items():
+            if val is not None:
+                ret.__setattr__(key, val)
+        return ret
+
+    def replace(self, new_config_dict):
+        if isinstance(new_config_dict, Config):
+            new_config_dict = vars(new_config_dict)
+
+        for key, val in new_config_dict.items():
+            if val is not None:
+                self.__setattr__(key, val)
+
+    def print(self):
+        for k, v in vars(self).items():
+            print(k, '=', v)
+
+    # def parser_val(self, val):
+    #     if isinstance(val, dict):
+    #         return Config(val)
+    #     elif isinstance(val, list):
+    #         for i in range(len(val)):
+    #             if val is not None:
+    #                 val[i] = self.parser_val(val[i])
+    #         return val
+    #     else:
+    #         return val
+
+    def __str__(self):
+        return str(vars(self))
+
+
+base_config = Config({
+    "project": "speaker_verification",
+    "name": "VGGVox",
+    "save_dir": "train_models/",
+    "resume": "",
+
+    # Training and test data
+    "dataset": Config({
+            "name": "voxceleb2_wav",
+            "train_list": "data/train_list.txt",
+            "test_list": "data/veri_list.txt",
+            "train_path": "data/voxceleb2",
+            "test_path": "data/voxceleb1",
+            "musan_path": "data/musan_split",  # 噪声文件
+            "rir_path": "data/RIRS_NOISES/simulated_rirs",  # 混响文件
+        }),
+
+
+    # Data loader
+    "max_frames": 300,  # 训练时帧长
+    "eval_frames": 300,
+    "batch_size": 64,
+    "max_seg_per_spk": 500,  # 每个说话人最大的语音段数
+    "nDataLoaderThread": 16,  # 多线程加载
+    "augment": True,  # 是否数据增强
+    "seed": 10,
+    "segment": 1,
+
+    # Training details
+    "test_interval": 1,  # 测试间隔
+    "max_epoch": 500,
+
+    # Model definition
+    "n_mels": 40,
+    "log_input": False,
+    "model": "Vgg",
+    "encoder_type": "SAP",
+    "nOut": 512,
+
+    # Loss functions
+    "loss": "SoftmaxProto",  # lossfunction function
+    "hard_prob": 0.5,
+    "hard_rank": 10,
+    "margin": 0.2,
+    "scale": 30,
+    "nPerSpeaker": 2,  # 同一段语音取多少组
+    "nClasses": 5994,
+
+    # Optimizer
+    "optimizer": "adam",
+    "scheduler": "steplr",
+    "lr": 0.001,
+    "lr_decay": 0.95,
+    "weight_decay": 0,
+
+    # Evaluation parameters
+    "dcf_p_target": 0.05,
+    "dcf_c_miss": 1,
+    "dcf_c_fa": 1,
+
+    # eval
+    "eval": False,
+})
+
+cfg = base_config
+
+vgg_cfg = Config({
+    "name": "vgg_spectrogram",
+    "model": "vgg",
+    "batch_size": 64,
+    "nPerSpeaker": 2,
+})
+
+Unet_cfg = Config({
+    "name": "Unet",
+    "model": "UNetVgg",
+    "batch_size": 48,
+    "nPerSpeaker": 2,
+    "loss": "Unetloss"
+})
+
+UnetMask_cfg = Config({
+    "name": "UnetMask",
+    "model": "UNetVggMask",
+    "batch_size": 16,
+    "nPerSpeaker": 2,
+    "segment": 3,
+    "loss": "UnetMaskloss"
+})
+
+ECAPA_TDNN_cfg = Config({
+    "name": "ECAPA_TDNNm",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmaxProto",
+    "batch_size": 180,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+})
+
+ECAPA_TDNNm_cfg = Config({
+    "name": "ECAPA_TDNNm",
+    "model": "ECAPA_TDNN",
+    "batch_size": 180,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+})
+
+ECAPA_TDNN1024_cfg = Config({
+    "name": "ECAPA_TDNN1024",
+    "model": "ECAPA_TDNN",
+    "batch_size": 80,
+    "nPerSpeaker": 2,
+    "channels": 1024,
+    "nOut": 192,
+})
+
+ECAPA_TDNN_ks5_cfg = Config({
+    "name": "ECAPA_TDNN_ks5",
+    "model": "ECAPA_TDNN_ks5",
+    "batch_size": 180,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+})
+
+ECAPA_TDNN_L2_cfg = Config({
+    "name": "ECAPA_TDNN_L2_pre",
+    "model": "ECAPA_TDNN_L2",
+    "batch_size": 180,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+    "resume": "train_models/speaker_verification_ECAPA_TDNN/20210725/epoch:47,EER:2.5981,MinDCF:0.1912"
+})
+
+ECAPA_TDNN_br_cfg = Config({
+    "name": "ECAPA_TDNN_br",
+    "model": "ECAPA_TDNN_br",
+    "batch_size": 180,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+})
+
+ECAPATDNN_cfg = Config({
+    "name": "ECAPATDNN",
+    "model": "ECAPATDNN",
+    "batch_size": 110,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+    "input_size": 80,
+})
+
+HRNet_cfg = Config({
+    "name": "hrnet",
+    "model": "hrnet",
+    "max_frames": 224,
+    "eval_frames": 224,
+    "batch_size": 48,
+    "nPerSpeaker": 2,
+    "nOut": 1024,
+    "input_size": 224*224,
+
+    "model_cfg": Config({
+        "hrnet_name": "w48",
+        "STAGE1": {
+            "NUM_MODULES": 1,
+            "NUM_BRANCHES": 1,
+            "BLOCK": "BOTTLENECK",
+            "NUM_BLOCKS": [4],
+            "NUM_CHANNELS": [64],
+            "FUSE_METHOD": "SUM"
+        },
+        "STAGE2": {
+            "NUM_MODULES": 1,
+            "NUM_BRANCHES": 2,
+            "BLOCK": "BASIC",
+            "NUM_BLOCKS": [4, 4],
+            "NUM_CHANNELS": [18, 36],
+            "FUSE_METHOD": "SUM"
+        },
+        "STAGE3": {
+            "NUM_MODULES": 4,
+            "NUM_BRANCHES": 3,
+            "BLOCK": "BASIC",
+            "NUM_BLOCKS": [4, 4, 4],
+            "NUM_CHANNELS": [18, 36, 72],
+            "FUSE_METHOD": "SUM"
+        },
+        "STAGE4": {
+            "NUM_MODULES": 3,
+            "NUM_BRANCHES": 4,
+            "BLOCK": "BASIC",
+            "NUM_BLOCKS": [4, 4, 4, 4],
+            "NUM_CHANNELS": [18, 36, 72, 144],
+            "FUSE_METHOD": "SUM"
+        },
+    }),
+
+})
+
+VGG_TDNN_cfg = Config({
+    "name": "Vggtdnn1",
+    "model": "Vggtdnn",
+    "batch_size": 256,
+    "nOut": 512,
+    "nDataLoaderThread": 16,
+})
+
+ResNetSE34V2_cfg = Config({
+    "name": "ResNetSE34V2",
+    "model": "ResNetSE34V2",
+    "batch_size": 128,
+    "nOut": 512,
+    "nDataLoaderThread": 16,
+})
+
+HRTDNN_cfg = Config({
+    "name": "hrtdnn",
+    "model": "hrtdnn",
+    "max_frames": 300,
+    "eval_frames": 300,
+    "batch_size": 96,
+    "nPerSpeaker": 2,
+    "nOut": 256,
+
+    "model_cfg": Config({
+        "hrnet_name": "hrtdnn",
+        "STAGE1": {
+            "NUM_BRANCHES": 1,
+            "BLOCK": 'TDNNBlock',
+            "NUM_CHANNELS": [128],
+            "FUSE_METHOD": "SUM"
+        },
+        "STAGE2": {
+            "NUM_BRANCHES": 2,
+            "BLOCK": 'TDNNBlock',
+            "NUM_CHANNELS": [128, 512],
+            "FUSE_METHOD": "SUM"
+        },
+        "STAGE3": {
+            "NUM_BRANCHES": 3,
+            "BLOCK": 'TDNNBlock',
+            "NUM_CHANNELS": [128, 512, 1024],
+            "FUSE_METHOD": "SUM"
+        },
+
+    }),
+
+})
+
+ResTDNN_cfg = Config({
+    "name": "ResTDNN",
+    "model": "ResTDNN",
+    "batch_size": 110,
+    "nOut": 256,
+    "nDataLoaderThread": 16,
+})
+
+TDNN_VGG_cfg = Config({
+    "name": "TDNN_VGG",
+    "model": "TDNN_VGG",
+    "batch_size": 64,
+    "nOut": 256,
+    "nDataLoaderThread": 16,
+})
+
+ResNet_TDNN_cfg = Config({
+    "name": "ResNet_TDNN",
+    "model": "ResNet_TDNN",
+    "batch_size": 96,
+    "nOut": 192,
+    "nDataLoaderThread": 16,
+})
+
+ResNet_TDNNa_cfg = Config({
+    "name": "ResNet_TDNNa",
+    "model": "ResNet_TDNN",
+    "batch_size": 96,
+    "nOut": 192,
+    "nDataLoaderThread": 16,
+})
+
+ResNet_TDNNaam_cfg = Config({
+    "name": "ResNet_TDNNaam",
+    "model": "ResNet_TDNN",
+    "loss": "AamSoftmaxProto",
+    "margin": 0.2,
+    "scale": 30,
+    "batch_size": 96,
+    "nOut": 192,
+    "nDataLoaderThread": 16,
+    "augment": True,
+})
+
+TDNN_ResNet_cfg = Config({
+    "name": "TDNN_ResNet",
+    "model": "TDNN_ResNet",
+    "batch_size": 48,
+    "nOut": 256,
+    "nDataLoaderThread": 16,
+})
+
+hr_tdnn_cfg = Config({
+    "name": "hr_tdnn",
+    "model": "hr_tdnn",
+    "batch_size": 46,
+    "nOut": 192,
+    "nDataLoaderThread": 16,
+})
+
+
+ECAPA_TDNNma_cfg = Config({
+    "name": "ECAPA_TDNNma",
+    "model": "ECAPA_TDNN",
+    "batch_size": 180,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+    "augment": True,
+})
+
+ECAPA_TDNNaam_cfg = Config({
+    "name": "ECAPA_TDNNaam",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmax",
+    "batch_size": 360,
+    "nPerSpeaker": 1,
+    "nOut": 192,
+    "augment": True,
+})
+
+ECAPA_TDNNaam1_cfg = Config({
+    "name": "ECAPA_TDNNaam1",
+    "model": "ECAPA_TDNN",
+    "loss": "AdditiveAngularMargin",
+    "batch_size": 360,
+    "nPerSpeaker": 1,
+    "nOut": 192,
+    "augment": True,
+})
+
+ECAPA_TDNNaam2_cfg = Config({
+    "name": "ECAPA_TDNNaam2",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmax",
+    "margin": 0.2,
+    "scale": 30,
+    "batch_size": 360,
+    "nPerSpeaker": 1,
+    "nOut": 192,
+    "augment": True,
+
+})
+
+ECAPA_TDNNaam3_cfg = Config({
+    "name": "ECAPA_TDNNaam3",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmax",
+    "margin": 0.1,
+    "scale": 30,
+    "batch_size": 360,
+    "nPerSpeaker": 1,
+    "nOut": 192,
+    "augment": True,
+
+})
+
+ECAPA_TDNN_aamproto_cfg = Config({
+    "name": "ECAPA_TDNN_aamproto",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmaxProto",
+    "batch_size": 180,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+    "augment": True,
+})
+
+ECAPA_TDNN_aamproto1_cfg = Config({
+    "name": "ECAPA_TDNN_aamproto1",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmaxProto",
+    "margin": 0.2,
+    "scale": 30,
+    "batch_size": 180,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+    "augment": True,
+})
+
+ECAPA_TDNN0_cfg = Config({
+    "name": "ECAPA_TDNN-1lr0.001",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmax",
+    "batch_size": 360,
+    "nOut": 192,
+    "nPerSpeaker": 1,
+    "resume": "train_models/speaker_verification_ECAPA_TDNN0/20210928/epoch:25,EER:2.4125,MinDCF:0.1537",
+})
+
+SwinTransformer_cfg = Config({
+    "name": "SwinTransformer",
+    "model": "SwinTransformer",
+    "loss": "SoftmaxProto",
+    "max_frames": 224,
+    "eval_frames": 224,
+    "n_mels": 224,
+    "batch_size": 90,
+    "nPerSpeaker": 2,
+    "nOut": 192,
+    "augment": True,
+    "lr": 5e-5,
+})
+
+ECAPA_TDNN_aampre_cfg = Config({
+    "name": "ECAPA_TDNN_aampre",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmaxProto",
+    "batch_size": 180,
+    "nOut": 192,
+    "nPerSpeaker": 2,
+    "resume": "train_models/speaker_verification_ECAPA_TDNNma/20210908/epoch:67,EER:2.3224,MinDCF:0.1658",
+})
+
+# 更换dataloader
+ECAPA_TDNN_data_cfg = Config({
+    "name": "ECAPA_TDNN_data",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmax",
+    "batch_size": 360,
+    "nPerSpeaker": 1,
+    "nOut": 192,
+    "augment": True,
+
+})
+
+# 标准的ECAPA_TDNN 学习率CyclicLR
+ECAPA_TDNNaam_cyclr_cfg = Config({
+    "name": "ECAPA_TDNNaam_cyclr",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmax",
+    "margin": 0.2,
+    "scale": 30,
+    "batch_size": 360,
+    "nPerSpeaker": 1,
+    "nOut": 192,
+    "augment": True,
+
+})
+
+# 跟换数据加载的ResNet_TDNN只用softmax
+ResNet_TDNNaam_data_cfg = Config({
+    "name": "ResNet_TDNNaam_data",
+    "model": "ResNet_TDNN",
+    "loss": "AamSoftmax",
+    "margin": 0.2,
+    "scale": 30,
+    "batch_size": 192,
+    "nOut": 192,
+    "nDataLoaderThread": 16,
+    "nPerSpeaker": 1,
+    "augment": True,
+})
+
+# 更换dataloader, 和cyclical lr
+ECAPA_TDNN_dataClr_cfg = Config({
+    "name": "ECAPA_TDNN_dataClr",
+    "model": "ECAPA_TDNN",
+    "loss": "AamSoftmax",
+    "batch_size": 360,
+    "nPerSpeaker": 1,
+    "nOut": 192,
+    "augment": True,
+})
+
+def set_cfg(config_name: str):
+    """ Sets the active configs. Works even if cfg is already imported! """
+    global cfg
+    # Note this is not just an eval because I'm lazy, but also because it can
+    # be used like ssd300_config.copy({'max_size': 400}) for extreme fine-tuning
+    cfg.replace(eval(config_name))