AssertionError in following command "python synthesize.py --model='Tacotron-2' --mode='live'"? Is it still not supported?

[hxs7709]

The error log is listed below.
Thank you.

[hxs@VM_0_7_centos Tacotron-2-Ray-newclips3-trainmodel-T2]$ python synthesize.py --model='Tacotron-2' --mode='live'
/home/hxs/anaconda3/lib/python3.6/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is
deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
from ._conv import register_converters as _register_converters
Using TensorFlow backend.
synthesize.py:82: UserWarning: Requested a live evaluation with Tacotron-2, Wavenet will not be used!
warn('Requested a live evaluation with Tacotron-2, Wavenet will not be used!')
Running End-to-End TTS Evaluation. Model: Tacotron-2
Synthesizing mel-spectrograms from text..
loaded model at logs-Tacotron-2/taco_pretrained/tacotron_model.ckpt-85000
Hyperparameters:
allow_clipping_in_normalization: True
attention_dim: 128
attention_filters: 32
attention_kernel: (31,)
cbhg_conv_channels: 128
cbhg_highway_units: 128
cbhg_highwaynet_layers: 4
cbhg_kernels: 8
cbhg_pool_size: 2
cbhg_projection: 256
cbhg_projection_kernel_size: 3
cbhg_rnn_units: 128
cin_channels: 80
cleaners: english_cleaners
clip_for_wavenet: True
clip_mels_length: True
cross_entropy_pos_weight: 20
cumulative_weights: True
decoder_layers: 2
decoder_lstm_units: 1024
embedding_dim: 512
enc_conv_channels: 512
enc_conv_kernel_size: (5,)
enc_conv_num_layers: 3
encoder_lstm_units: 256
fmax: 7600
fmin: 55
frame_shift_ms: None
freq_axis_kernel_size: 3
gate_channels: 256
gin_channels: -1
griffin_lim_iters: 60
hop_size: 275
input_type: raw
kernel_size: 3
layers: 20
leaky_alpha: 0.4
log_scale_min: -32.23619130191664
log_scale_min_gauss: -16.11809565095832
mask_decoder: False
mask_encoder: True
max_abs_value: 4.0
max_iters: 2000
max_mel_frames: 1000
max_time_sec: None
max_time_steps: 11000
min_level_db: -100
n_fft: 2048
n_speakers: 5
natural_eval: False
normalize_for_wavenet: True
num_freq: 1025
num_mels: 80
out_channels: 2
outputs_per_step: 1
postnet_channels: 512
postnet_kernel_size: (5,)
postnet_num_layers: 5
power: 1.5
predict_linear: True
preemphasis: 0.97
preemphasize: True
prenet_layers: [256, 256]
quantize_channels: 65536
ref_level_db: 20
rescale: True
rescaling_max: 0.999
residual_channels: 128
sample_rate: 22050
signal_normalization: True
silence_threshold: 2
skip_out_channels: 128
smoothing: False
split_on_cpu: True
stacks: 2
stop_at_any: True
symmetric_mels: True
tacotron_adam_beta1: 0.9
tacotron_adam_beta2: 0.999
tacotron_adam_epsilon: 1e-06
tacotron_batch_size: 32
tacotron_clip_gradients: True
tacotron_data_random_state: 1234
tacotron_decay_learning_rate: True
tacotron_decay_rate: 0.5
tacotron_decay_steps: 50000
tacotron_dropout_rate: 0.5
tacotron_final_learning_rate: 1e-05
tacotron_gpu_start_idx: 0
tacotron_initial_learning_rate: 0.001
tacotron_num_gpus: 1
tacotron_random_seed: 5339
tacotron_reg_weight: 1e-07
tacotron_scale_regularization: False
tacotron_start_decay: 50000
tacotron_swap_with_cpu: False
tacotron_synthesis_batch_size: 1
tacotron_teacher_forcing_decay_alpha: 0.0
tacotron_teacher_forcing_decay_steps: 280000
tacotron_teacher_forcing_final_ratio: 0.0
tacotron_teacher_forcing_init_ratio: 1.0
tacotron_teacher_forcing_mode: constant
tacotron_teacher_forcing_ratio: 1.0
tacotron_teacher_forcing_start_decay: 10000
tacotron_test_batches: None
tacotron_test_size: 0.05
tacotron_zoneout_rate: 0.1
train_with_GTA: False
trim_fft_size: 512
trim_hop_size: 128
trim_silence: True
trim_top_db: 23
upsample_activation: LeakyRelu
upsample_conditional_features: True
upsample_scales: [5, 5, 11]
upsample_type: 1D
use_bias: True
use_lws: False
use_speaker_embedding: True
wavenet_adam_beta1: 0.9
wavenet_adam_beta2: 0.999
wavenet_adam_epsilon: 1e-08
wavenet_batch_size: 8
wavenet_clip_gradients: False
wavenet_data_random_state: 1234
wavenet_decay_rate: 0.5
wavenet_decay_steps: 300000
wavenet_dropout: 0.05
wavenet_ema_decay: 0.9999
wavenet_gpu_start_idx: 0
wavenet_init_scale: 1.0
wavenet_learning_rate: 0.0001
wavenet_lr_schedule: exponential
wavenet_num_gpus: 1
wavenet_random_seed: 5339
wavenet_swap_with_cpu: False
wavenet_synthesis_batch_size: 20
wavenet_test_batches: None
wavenet_test_size: 0.0441
wavenet_warmup: 4000.0
wavenet_weight_normalization: False
win_size: 1100
Constructing model: Tacotron
WARNING:tensorflow:From /home/hxs/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py:430: calling reverse_sequence (from tensorflow.python.ops.array_ops) with
seq_dim is deprecated and will be removed in a future version.
Instructions for updating:
seq_dim is deprecated, use seq_axis instead
WARNING:tensorflow:From /home/hxs/anaconda3/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py:454: calling reverse_sequence (from tensorflow.python.ops.array_ops) with batch_dim is deprecated and will be removed in a future version.
Instructions for updating:
batch_dim is deprecated, use batch_axis instead
initialisation done /gpu:0
Initialized Tacotron model. Dimensions (? = dynamic shape):
Train mode: False
Eval mode: False
GTA mode: False
Synthesis mode: True
Input: (?, ?)
device: 0
embedding: (?, ?, 512)
enc conv out: (?, ?, 512)
encoder out: (?, ?, 512)
decoder out: (?, ?, 80)
residual out: (?, ?, 512)
projected residual out: (?, ?, 80)
mel out: (?, ?, 80)
linear out: (?, ?, 1025)
<stop_token> out: (?, ?)
Tacotron Parameters 29.016 Million.
Loading checkpoint: logs-Tacotron-2/taco_pretrained/tacotron_model.ckpt-85000
Hello, Welcome to the Live testing tool. Please type a message and I will try to read it!
Traceback (most recent call last):
File "synthesize.py", line 100, in
main()
File "synthesize.py", line 94, in main
synthesize(args, hparams, taco_checkpoint, wave_checkpoint, sentences)
File "synthesize.py", line 36, in synthesize
wavenet_in_dir = tacotron_synthesize(args, hparams, taco_checkpoint, sentences)
File "/mnt/data/hxs/Tacotron-2-Ray-newclips3-trainmodel-T2/tacotron/synthesize.py", line 139, in tacotron_synthesize
run_live(args, checkpoint_path, hparams)
File "/mnt/data/hxs/Tacotron-2-Ray-newclips3-trainmodel-T2/tacotron/synthesize.py", line 27, in run_live
generate_fast(synth, greetings)
File "/mnt/data/hxs/Tacotron-2-Ray-newclips3-trainmodel-T2/tacotron/synthesize.py", line 15, in generate_fast
model.synthesize(text, None, None, None, None)
File "/mnt/data/hxs/Tacotron-2-Ray-newclips3-trainmodel-T2/tacotron/synthesizer.py", line 147, in synthesize
assert len(mels) == len(linears) == len(texts)
AssertionError

[gloriouskilka]

This is a fix for this problem #237

[li-xx-5]

hello,have you solve the problem?@hxs7709

[li-xx-5]

hello,i met the same erro ,can you tell me how to solve that?thanks@gloriouskilka

[hxs7709]

Sorry, I do not solve this issue.

[statcom]

This is a fix for this problem #237

No, @gloriouskilka change didn't fix the problem as I just tried the change. I think the error can be avoided by additionally commenting out the line, but not sure if this is a good fix.

assert len(mels) == len(linears) == len(texts)