adjust licenses and naming

README.md

@@ -154,22 +154,22 @@ pip install intel_extension_for_pytorch -f https://software.intel.com/ipex-whl-s
 To sample from the _SD2.1-v_ model with TorchScript+IPEX optimizations, run the following. Remember to specify desired number of instances you want to run the program on ([more](https://github.com/intel/intel-extension-for-pytorch/blob/master/intel_extension_for_pytorch/cpu/launch.py#L48)).
 
 ```
-MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000 python -m intel_extension_for_pytorch.cpu.launch --ninstance <number of an instance> --enable_jemalloc scripts/txt2img.py --prompt \"a corgi is playing guitar, oil on canvas\" --ckpt <path/to/768model.ckpt/> --config configs/stable-diffusion/ipex/v2-inference-v-fp32.yaml --H 768 --W 768 --precision full --device cpu --torchscript --ipex
+MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000 python -m intel_extension_for_pytorch.cpu.launch --ninstance <number of an instance> --enable_jemalloc scripts/txt2img.py --prompt \"a corgi is playing guitar, oil on canvas\" --ckpt <path/to/768model.ckpt/> --config configs/stable-diffusion/intel/v2-inference-v-fp32.yaml --H 768 --W 768 --precision full --device cpu --torchscript --ipex
 ```
 
 To sample from the base model with IPEX optimizations, use
 
 ```
-MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000 python -m intel_extension_for_pytorch.cpu.launch --ninstance <number of an instance> --enable_jemalloc scripts/txt2img.py --prompt \"a corgi is playing guitar, oil on canvas\" --ckpt <path/to/model.ckpt/> --config configs/stable-diffusion/ipex/v2-inference-fp32.yaml --n_samples 1 --n_iter 4 --precision full --device cpu --torchscript --ipex
+MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000 python -m intel_extension_for_pytorch.cpu.launch --ninstance <number of an instance> --enable_jemalloc scripts/txt2img.py --prompt \"a corgi is playing guitar, oil on canvas\" --ckpt <path/to/model.ckpt/> --config configs/stable-diffusion/intel/v2-inference-fp32.yaml --n_samples 1 --n_iter 4 --precision full --device cpu --torchscript --ipex
 ```
 
 If you're using a CPU that supports `bfloat16`, consider sample from the model with bfloat16 enabled for a performance boost, like so
 
 ```bash
 # SD2.1-v
-MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000 python -m intel_extension_for_pytorch.cpu.launch --ninstance <number of an instance> --enable_jemalloc scripts/txt2img.py --prompt \"a corgi is playing guitar, oil on canvas\" --ckpt <path/to/768model.ckpt/> --config configs/stable-diffusion/ipex/v2-inference-v-bf16.yaml --H 768 --W 768 --precision full --device cpu --torchscript --ipex --bf16
+MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000 python -m intel_extension_for_pytorch.cpu.launch --ninstance <number of an instance> --enable_jemalloc scripts/txt2img.py --prompt \"a corgi is playing guitar, oil on canvas\" --ckpt <path/to/768model.ckpt/> --config configs/stable-diffusion/intel/v2-inference-v-bf16.yaml --H 768 --W 768 --precision full --device cpu --torchscript --ipex --bf16
 # SD2.1-base
-MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000 python -m intel_extension_for_pytorch.cpu.launch --ninstance <number of an instance> --enable_jemalloc scripts/txt2img.py --prompt \"a corgi is playing guitar, oil on canvas\" --ckpt <path/to/model.ckpt/> --config configs/stable-diffusion/ipex/v2-inference-bf16.yaml --precision full --device cpu --torchscript --ipex --bf16
+MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:9000000000,muzzy_decay_ms:9000000000 python -m intel_extension_for_pytorch.cpu.launch --ninstance <number of an instance> --enable_jemalloc scripts/txt2img.py --prompt \"a corgi is playing guitar, oil on canvas\" --ckpt <path/to/model.ckpt/> --config configs/stable-diffusion/intel/v2-inference-bf16.yaml --precision full --device cpu --torchscript --ipex --bf16
 ```
 
 ### Image Modification with Stable Diffusion

ldm/models/diffusion/ddim.py

@@ -1,6 +1,3 @@
-# Copyright (C) 2022 Intel Corporation
-# SPDX-License-Identifier: MIT
-
 """SAMPLING ONLY."""
 
 import torch

ldm/models/diffusion/ddpm.py

@@ -1,6 +1,3 @@
-# Copyright (C) 2022 Intel Corporation
-# SPDX-License-Identifier: MIT
-
 """
 wild mixture of
 https://github.com/lucidrains/denoising-diffusion-pytorch/blob/7706bdfc6f527f58d33f84b7b522e61e6e3164b3/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py

ldm/models/diffusion/dpm_solver/sampler.py

@@ -1,6 +1,3 @@
-# Copyright (C) 2022 Intel Corporation
-# SPDX-License-Identifier: MIT
-
 """SAMPLING ONLY."""
 import torch
 

ldm/models/diffusion/plms.py

@@ -1,6 +1,3 @@
-# Copyright (C) 2022 Intel Corporation
-# SPDX-License-Identifier: MIT
-
 """SAMPLING ONLY."""
 
 import torch

ldm/modules/diffusionmodules/openaimodel.py

@@ -1,6 +1,3 @@
-# Copyright (C) 2022 Intel Corporation
-# SPDX-License-Identifier: MIT
-
 from abc import abstractmethod
 import math
 

scripts/txt2img.py

@@ -1,6 +1,3 @@
-# Copyright (C) 2022 Intel Corporation
-# SPDX-License-Identifier: MIT
-
 import argparse, os
 import cv2
 import torch
@@ -270,10 +267,10 @@ def main(opt):
  if opt.bf16 and not opt.torchscript and not opt.ipex:
  raise ValueError('Bfloat16 is supported only for torchscript+ipex')
  if opt.bf16 and unet.dtype != torch.bfloat16:
- raise ValueError("Use configs/stable-diffusion/ipex/ configs with bf16 enabled if " +
+ raise ValueError("Use configs/stable-diffusion/intel/ configs with bf16 enabled if " +
  "you'd like to use bfloat16 with CPU.")
  if unet.dtype == torch.float16 and device == torch.device("cpu"):
- raise ValueError("Use configs/stable-diffusion/ipex/ configs for your model if you'd like to run it on CPU.")
+ raise ValueError("Use configs/stable-diffusion/intel/ configs for your model if you'd like to run it on CPU.")
 
  if opt.ipex:
  import intel_extension_for_pytorch as ipex
@@ -292,7 +289,7 @@ def main(opt):
  # get UNET scripted
  if unet.use_checkpoint:
  raise ValueError("Gradient checkpoint won't work with tracing. " +
- "Use configs/stable-diffusion/ipex/ configs for your model or disable checkpoint in your config.")
+ "Use configs/stable-diffusion/intel/ configs for your model or disable checkpoint in your config.")
 
  img_in = torch.ones(2, 4, 96, 96, dtype=torch.float32)
  t_in = torch.ones(2, dtype=torch.int64)