support proper types on the cpu

app.ipynb

@@ -35,9 +35,13 @@
     "######################################\n",
     "######################################\n",
     "model_name = 'stabilityai/stable-diffusion-2'\n",
-    "revision = 'fp16'\n",
-    "dtype = torch.float16\n",
     "device = ('cpu','cuda')[torch.cuda.is_available()]\n",
+    "if device == 'cuda':\n",
+    "    revision = 'fp16'\n",
+    "    dtype = torch.float16\n",
+    "else:\n",
+    "    revision = 'fp32'\n",
+    "    dtype = torch.float32\n",
     "\n",
     "# model parameters\n",
     "better_vae = ''\n",
@@ -217,7 +221,7 @@
     "    compare_dynamic_guidance,\n",
     "    inputs=\"text\",\n",
     "    outputs=gr.Gallery(),\n",
-    "    title=\"Comparison with dynamic Classifier-free Guidance Comparison\",\n",
+    "    title=\"Comparing image generations with dynamic Classifier-free Guidance\",\n",
     ")\n",
     "iface.launch()\n"
    ]

app.py

@@ -1,11 +1,11 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
 
 # %% auto 0
-__all__ = ['model_name', 'revision', 'dtype', 'device', 'better_vae', 'unet_attn_slice', 'sampler_kls', 'hf_sampler',
-           'model_kwargs', 'num_steps', 'height', 'width', 'k_sampler', 'use_karras_sigmas', 'NEG_PROMPT',
-           'generation_kwargs', 'baseline_g', 'max_val', 'min_val', 'num_warmup_steps', 'warmup_init_val', 'num_cycles',
-           'k_decay', 'DEFAULT_COS_PARAMS', 'static_sched', 'k_sched', 'inv_k_sched', 'scheds', 'iface', 'load_model',
-           'cos_harness', 'compare_dynamic_guidance']
+__all__ = ['model_name', 'device', 'better_vae', 'unet_attn_slice', 'sampler_kls', 'hf_sampler', 'model_kwargs', 'num_steps',
+           'height', 'width', 'k_sampler', 'use_karras_sigmas', 'NEG_PROMPT', 'generation_kwargs', 'baseline_g',
+           'max_val', 'min_val', 'num_warmup_steps', 'warmup_init_val', 'num_cycles', 'k_decay', 'DEFAULT_COS_PARAMS',
+           'static_sched', 'k_sched', 'inv_k_sched', 'scheds', 'iface', 'load_model', 'cos_harness',
+           'compare_dynamic_guidance']
 
 # %% app.ipynb 1
 import gradio as gr
@@ -19,9 +19,13 @@ import nbdev
 ######################################
 ######################################
 model_name = 'stabilityai/stable-diffusion-2'
-revision = 'fp16'
-dtype = torch.float16
 device = ('cpu','cuda')[torch.cuda.is_available()]
+if device == 'cuda':
+    revision = 'fp16'
+    dtype = torch.float16
+else:
+    revision = 'fp32'
+    dtype = torch.float32
 
 # model parameters
 better_vae = ''
@@ -168,7 +172,7 @@ iface = gr.Interface(
     compare_dynamic_guidance,
     inputs="text",
     outputs=gr.Gallery(),
-    title="Comparison with dynamic Classifier-free Guidance Comparison",
+    title="Comparing image generations with dynamic Classifier-free Guidance",
 )
 iface.launch()