Fixed bugs #857 #860 #861 and #863

Dockerfile

@@ -1,4 +1,4 @@
-FROM nvidia/cuda:12.2.0-base-ubuntu22.04
+FROM nvidia/cuda:12.9.1-base-ubuntu24.04
 
 COPY . /app
 
@@ -26,9 +26,11 @@ RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -
 # --login option used to source bashrc (thus activating conda env) at every RUN statement
 SHELL ["/bin/bash", "--login", "-c"]
 
-RUN conda create --name tortoise python=3.9 numba inflect -y \
+RUN conda tos accept \
+    && conda create --name tortoise python=3.13.5 numba inflect -y \ 
     && conda activate tortoise \
-    && conda install --yes pytorch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 pytorch-cuda=12.1 -c pytorch -c nvidia \
-    && conda install --yes transformers=4.31.0 \
+    && conda install --yes conda-forge::pytorch==2.7.1 conda-forge::torchaudio=2.7.1 pytorch-cuda -c pytorch -c nvidia \
+    && conda install --yes conda-forge::torchvision=0.22.0 \
+    && conda install --yes conda-forge::transformers=4.53.3 \
     && cd /app \
     && python setup.py install

requirements.txt

@@ -1,12 +1,12 @@
 tqdm
 rotary_embedding_torch
-transformers==4.31.0
+transformers==4.53.3
 tokenizers
 inflect
 progressbar
 einops==0.4.1
 unidecode
-scipy
+scipy=1.16.1
 librosa==0.9.1
 ffmpeg
 numpy

setup.py

@@ -27,9 +27,9 @@ setuptools.setup(
         'unidecode',
         'scipy',
         'librosa',
-        'transformers==4.31.0',
-        'tokenizers==0.14.0',
-        'scipy==1.13.1'
+        'transformers==4.53.3',
+        'tokenizers',
+        'scipy==1.16.1'
         # 'deepspeed==0.8.3',
     ],
     classifiers=[
@@ -37,5 +37,5 @@ setuptools.setup(
         "License :: OSI Approved :: Apache Software License",
         "Operating System :: OS Independent",
     ],
-    python_requires=">=3.6",
+    python_requires=">=3.13",
 )

tortoise/models/autoregressive.py

@@ -3,7 +3,7 @@ import functools
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from transformers import GPT2Config, GPT2PreTrainedModel, LogitsProcessorList
+from transformers import GPT2Config, GPT2PreTrainedModel, LogitsProcessorList, GenerationMixin
 from transformers.modeling_outputs import CausalLMOutputWithCrossAttentions
 from transformers.utils.model_parallel_utils import get_device_map, assert_device_map
 from tortoise.models.arch_util import AttentionBlock
@@ -32,7 +32,7 @@ class ResBlock(nn.Module):
         return F.relu(self.net(x) + x)
 
 
-class GPT2InferenceModel(GPT2PreTrainedModel):
+class GPT2InferenceModel(GPT2PreTrainedModel, GenerationMixin):
     def __init__(self, config, gpt, text_pos_emb, embeddings, norm, linear, kv_cache=False):
         super().__init__(config)
         self.transformer = gpt

tortoise/utils/typical_sampling.py

@@ -1,8 +1,8 @@
 import torch
-from transformers import LogitsWarper
+from transformers import LogitsProcessor
 
 
-class TypicalLogitsWarper(LogitsWarper):
+class TypicalLogitsWarper(LogitsProcessor):
     def __init__(self, mass: float = 0.9, filter_value: float = -float("Inf"), min_tokens_to_keep: int = 1):
         self.filter_value = filter_value
         self.mass = mass