some updates

Author: divamgupta

backends/model_converter/tdict.py

@@ -124,6 +124,8 @@ def init_read(self):
  weights_json_start = extra_head[4]
  weights_json_l = extra_head[5] - extra_head[4]
 
+ self.ctdict_version = int(extra_head[3])
+
  self.in_file.seek(weights_json_start)
  self.keys_info = json.loads( self.in_file.read(weights_json_l).decode('ascii') )
 

backends/stable_diffusion/.gitingore

@@ -0,0 +1,170 @@
+build
+build/
+build/*
+
+dist
+dist/
+dist/*
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+# Usually these files are written by a python script from a template
+# before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+# For a library or package, you might want to ignore these files since the code is
+# intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+# However, in case of collaboration, if having platform-specific dependencies or dependencies
+# having no cross-platform support, pipenv may install dependencies that don't work, or not
+# install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+# This is especially recommended for binary packages to ensure reproducibility, and is more
+# commonly ignored for libraries.
+# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+# in version control.
+# https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+# and can be added to the global gitignore or merged into this file. For a more nuclear
+# option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+

backends/stable_diffusion/clip_tokenizer/__init__.py

@@ -16,13 +16,15 @@ def default_bpe():
  p = os.path.join(
  os.path.dirname(os.path.abspath(__file__)), "bpe_simple_vocab_16e6.txt.gz"
  )
+ # print("checking " , p )
  if os.path.exists(p):
  return p
  else:
  p2 = os.path.join(
- os.path.dirname(os.path.abspath(__file__)), ".." , ".." ,"bpe_simple_vocab_16e6.txt.gz"
+ os.path.dirname(os.path.abspath(__file__)), ".." ,"bpe_simple_vocab_16e6.txt.gz"
  )
  p2 = os.path.abspath(p2)
+ # print("checking " , p2 )
  if os.path.exists(p2):
  return p2
  assert False

backends/stable_diffusion/diffusionbee_backend.py

@@ -1,4 +1,4 @@
-print("backend")
+print("starting backend")
 
 from stdin_input import is_avail, get_input
 import argparse
@@ -12,18 +12,35 @@
 import math
 import time
 import traceback
-from stable_diffusion import StableDiffusion
 import os
+from pathlib import Path
+import importlib
+
 # b2py t2im {"prompt": "sun glasses" , "W":640 , "H" : 640 , "num_imgs" : 10 , "input_image":"/Users/divamgupta/Downloads/inn.png" , "mask_image" : "/Users/divamgupta/Downloads/maa.png" , "is_inpaint":true }
 
+if not ( getattr(sys, 'frozen', False) and hasattr(sys, '_MEIPASS')):
+ print("Adding sys paths")
+ dir_path = os.path.dirname(os.path.realpath(__file__))
+ sys.path.append(os.path.join(dir_path , "../model_converter"))
+
+ model_interface_path = os.environ.get('MODEL_INTERFACE_PATH') or "../stable_diffusion_tf_models"
+ sys.path.append( os.path.join(dir_path , model_interface_path) )
+else:
+ print("not adding sys paths")
+
 
-dir_path = os.path.dirname(os.path.realpath(__file__))
-sys.path.append(os.path.join(dir_path , "../model_converter"))
 from convert_model import convert_model
+from stable_diffusion import StableDiffusion
+
+# get the model interface form the environ
+USE_DUMMY_INTERFACE = False
+if USE_DUMMY_INTERFACE :
+ from fake_interface import ModelInterface
+else:
+ from interface import ModelInterface
+
 
 
-from pathlib import Path
-import os
 
 home_path = Path.home()
 
@@ -68,13 +85,20 @@ def download_weights():
  is_downloaded = False
  for _ in range(10):
  try:
- print("sdbk mltl Downloading Model 1/2")
-
- p_14 = "/Users/divamgupta/Downloads/sd-v1-4.tdict"
 
- print("sdbk mltl Downloading Model 2/2")
+ p_14 = ProgressBarDownloader(title="Downloading Model 1/2").download(
+ url="https://huggingface.co/divamgupta/stable_diffusion_mps/resolve/main/sd-v1-4_fp16.tdict",
+ md5_checksum="9f1fc1e94821d000b811e3bb6e7686b2",
+ verify_ssl=False,
+ extract_zip=False,
+ )
 
- p_14_np = "/Users/divamgupta/Downloads/sd-v1-5-inpainting.tdict"
+ p_14_np = ProgressBarDownloader(title="Downloading Model 2/2").download(
+ url="https://huggingface.co/divamgupta/stable_diffusion_mps/resolve/main/sd-v1-5-inpainting_fp16.tdict",
+ md5_checksum="68303f49cca00968c39abddc20b622a6",
+ verify_ssl=False,
+ extract_zip=False,
+ )
 
  is_downloaded = True
  break
@@ -169,7 +193,7 @@ def callback(state="" , progress=-1):
  if "__stop__" in get_input():
  return "stop"
 
- generator = StableDiffusion( p_14 , model_name="sd_1x", callback=callback)
+ generator = StableDiffusion( ModelInterface , p_14 , model_name="sd_1x", callback=callback)
 
 
  default_d = { "W" : 512 , "H" : 512, "num_imgs":1 , "ddim_steps" : 25 ,

backends/stable_diffusion/schedulers/scheduling_lms_discrete.py

@@ -18,7 +18,6 @@
 from typing import Optional, Tuple, Union
 
 import numpy as np
-import torch
 
 from scipy import integrate
 
@@ -141,9 +140,9 @@ def set_timesteps(self, num_inference_steps: int):
 
  def step(
  self,
- model_output: Union[torch.FloatTensor, np.ndarray],
+ model_output: Union[ np.ndarray],
  timestep: int,
- sample: Union[torch.FloatTensor, np.ndarray],
+ sample: Union[ np.ndarray],
  seed=None,
  order: int = 4,
  return_dict: bool = True,
@@ -190,10 +189,10 @@ def step(
 
  def add_noise(
  self,
- original_samples: Union[torch.FloatTensor, np.ndarray],
- noise: Union[torch.FloatTensor, np.ndarray],
- timesteps: Union[torch.IntTensor, np.ndarray],
- ) -> Union[torch.FloatTensor, np.ndarray]:
+ original_samples: Union[ np.ndarray],
+ noise: Union[ np.ndarray],
+ timesteps: Union[np.ndarray],
+ ) -> Union[ np.ndarray]:
  sigmas = self.match_shape(self.sigmas[timesteps], noise)
  noisy_samples = original_samples + noise * sigmas
 

backends/stable_diffusion/stable_diffusion.py

@@ -11,38 +11,15 @@
 import io
 from dataclasses import dataclass
 import os 
-import importlib
 import sys 
 
 MAX_TEXT_LEN = 77
 
-USE_DUMMY_INTERFACE = False
 
 dir_path = os.path.dirname(os.path.realpath(__file__))
 
-sys.path.append(os.path.join(dir_path , "../model_converter"))
 from tdict import TDict
 
-# get the model interface form the environ
-if not USE_DUMMY_INTERFACE :
- model_interface_path = os.environ.get('MODEL_INTERFACE_PATH') or "../stable_diffusion_tf_models"
-
- print("model_interface_path", model_interface_path )
-
- if model_interface_path[-1] == "/":
- model_interface_path = model_interface_path[:-1]
-
- module_name = model_interface_path.split("/")[-1]
- module_path = "/".join(model_interface_path.split("/")[:-1])
-
- 
- sys.path.append( os.path.join(dir_path , module_path) )
-
-
- ModelInterface = importlib.import_module( module_name + ".interface").ModelInterface
-else:
- from fake_interface import ModelInterface
-
 from schedulers.scheduling_ddim import DDIMScheduler
 from schedulers.scheduling_lms_discrete import LMSDiscreteScheduler
 from schedulers.scheduling_pndm import PNDMScheduler
@@ -145,8 +122,9 @@ def dummy_callback(state="" , progress=-1):
  pass
 
 class StableDiffusion:
- def __init__(self , tdict_path , model_name="sd_1x", callback=None ):
+ def __init__(self , ModelInterfaceClass ,  tdict_path , model_name="sd_1x", callback=None ):
 
+ self.ModelInterfaceClass = ModelInterfaceClass
 
  if callback is None:
  callback = dummy_callback
@@ -158,9 +136,9 @@ def __init__(self , tdict_path , model_name="sd_1x", callback=None ):
 
  self.current_model_name = model_name 
  self.current_tdict_path = tdict_path
- self.current_dtype = ModelInterface.default_float_type
+ self.current_dtype = self.ModelInterfaceClass.default_float_type
 
- self.model = ModelInterface( TDict(self.current_tdict_path ), dtype=self.current_dtype, model_name=self.current_model_name )
+ self.model = self.ModelInterfaceClass( TDict(self.current_tdict_path ), dtype=self.current_dtype, model_name=self.current_model_name )
 
 
  def prepare_model_interface(self , sd_run=None ):
@@ -177,7 +155,7 @@ def prepare_model_interface(self , sd_run=None ):
  print("Creating model interface")
  assert tdict_path is not None
  self.model.destroy()
- self.model = ModelInterface(TDict(tdict_path ) , dtype=dtype, model_name=model_name )
+ self.model = self.ModelInterfaceClass(TDict(tdict_path ) , dtype=dtype, model_name=model_name )
  self.current_tdict_path = tdict_path
  self.current_dtype = dtype
  self.current_model_name = model_name

backends/stable_diffusion_tf_models/__init__.py

@@ -1,7 +1,7 @@
 import tensorflow as tf
-from .group_norm import GroupNormalization
+from group_norm import GroupNormalization
 
-from .layers import apply_seq, PaddedConv2D
+from layers import apply_seq, PaddedConv2D
 
 
 class AttentionBlock(tf.keras.layers.Layer):