abormal behavior

[dentistfrankchen]

I followed and copied the code on your main page, however it did not behave normally:
ValueError Traceback (most recent call last)
Cell In[5], line 4
1 from stable_diffusion_tf.stable_diffusion import StableDiffusion
2 from PIL import Image
----> 4 generator = StableDiffusion()

File ~/anaconda3/envs/art_intel/lib/python3.9/site-packages/stable_diffusion_tf/stable_diffusion.py:24, in StableDiffusion.init(self, img_height, img_width, jit_compile, download_weights)
21 self.img_width = img_width
22 self.tokenizer = SimpleTokenizer()
---> 24 text_encoder, diffusion_model, decoder, encoder = get_models(img_height, img_width, download_weights=download_weights)
25 self.text_encoder = text_encoder
26 self.diffusion_model = diffusion_model

File ~/anaconda3/envs/art_intel/lib/python3.9/site-packages/stable_diffusion_tf/stable_diffusion.py:238, in get_models(img_height, img_width, download_weights)
235 latent = keras.layers.Input((n_h, n_w, 4))
236 unet = UNetModel()
237 diffusion_model = keras.models.Model(
--> 238 [latent, t_emb, context], unet([latent, t_emb, context])
239 )
241 # Create decoder
242 latent = keras.layers.Input((n_h, n_w, 4))

File ~/anaconda3/envs/art_intel/lib/python3.9/site-packages/keras/utils/traceback_utils.py:70, in filter_traceback..error_handler(*args, **kwargs)
67 filtered_tb = _process_traceback_frames(e.traceback)
68 # To get the full stack trace, call:
69 # tf.debugging.disable_traceback_filtering()
---> 70 raise e.with_traceback(filtered_tb) from None
71 finally:
72 del filtered_tb

File /tmp/autograph_generated_file2lo7vt15.py:84, in outer_factory..inner_factory..tf__call(self, inputs)
82 layer = ag.Undefined('layer')
83 b = ag__.Undefined('b')
---> 84 ag__.for_stmt(ag__.ld(self).input_blocks, None, loop_body_1, get_state_3, set_state_3, ('x',), {'iterate_names': 'b'})
86 def get_state_4():
87 return (x,)

File /tmp/autograph_generated_file2lo7vt15.py:80, in outer_factory..inner_factory..tf__call..loop_body_1(itr_1)
78 layer = itr
79 x = ag.converted_call(ag__.ld(apply), (ag__.ld(x), ag__.ld(layer)), None, fscope)
---> 80 ag__.for_stmt(ag__.ld(b), None, loop_body, get_state_2, set_state_2, ('x',), {'iterate_names': 'layer'})
81 ag__.converted_call(ag__.ld(saved_inputs).append, (ag__.ld(x),), None, fscope)

File /tmp/autograph_generated_file2lo7vt15.py:79, in outer_factory..inner_factory..tf__call..loop_body_1..loop_body(itr)
77 nonlocal x
78 layer = itr
---> 79 x = ag.converted_call(ag__.ld(apply), (ag__.ld(x), ag__.ld(layer)), None, fscope)

File /tmp/autograph_generated_file2lo7vt15.py:48, in outer_factory..inner_factory..tf__call..apply(x, layer)
46 x = ag.converted_call(ag__.ld(layer), (ag__.ld(x),), None, fscope_1)
47 ag__.if_stmt(ag__.converted_call(ag__.ld(isinstance), (ag__.ld(layer), ag__.ld(SpatialTransformer)), None, fscope_1), if_body, else_body, get_state, set_state, ('x',), 1)
---> 48 ag__.if_stmt(ag__.converted_call(ag__.ld(isinstance), (ag__.ld(layer), ag__.ld(ResBlock)), None, fscope_1), if_body_1, else_body_1, get_state_1, set_state_1, ('x',), 1)
49 try:
50 do_return_1 = True

File /tmp/autograph_generated_file2lo7vt15.py:28, in outer_factory..inner_factory..tf__call..apply..if_body_1()
26 def if_body_1():
27 nonlocal x
---> 28 x = ag.converted_call(ag__.ld(layer), ([ag__.ld(x), ag__.ld(emb)],), None, fscope_1)

File /tmp/autograph_generated_filem_kzpxnn.py:11, in outer_factory..inner_factory..tf__call(self, inputs)
9 retval = ag_.UndefinedReturnValue()
10 (x, emb) = ag__.ld(inputs)
---> 11 h = ag__.converted_call(ag__.ld(apply_seq), (ag__.ld(x), ag__.ld(self).in_layers), None, fscope)
12 emb_out = ag__.converted_call(ag__.ld(apply_seq), (ag__.ld(emb), ag__.ld(self).emb_layers), None, fscope)
13 h = ag__.ld(h) + ag__.ld(emb_out)[:, None, None]

File /tmp/autograph_generated_file612zmgqy.py:23, in outer_factory..inner_factory..tf__apply_seq(x, layers)
21 x = ag.converted_call(ag__.ld(l), (ag__.ld(x),), None, fscope)
22 l = ag__.Undefined('l')
---> 23 ag__.for_stmt(ag__.ld(layers), None, loop_body, get_state, set_state, ('x',), {'iterate_names': 'l'})
24 try:
25 do_return = True

File /tmp/autograph_generated_file612zmgqy.py:21, in outer_factory..inner_factory..tf__apply_seq..loop_body(itr)
19 nonlocal x
20 l = itr
---> 21 x = ag.converted_call(ag__.ld(l), (ag__.ld(x),), None, fscope)

File ~/anaconda3/envs/art_intel/lib/python3.9/site-packages/tensorflow_addons/layers/normalizations.py:110, in GroupNormalization.build(self, input_shape)
108 self._check_if_input_shape_is_none(input_shape)
109 self._set_number_of_groups_for_instance_norm(input_shape)
--> 110 self._check_size_of_dimensions(input_shape)
111 self._create_input_spec(input_shape)
113 self._add_gamma_weight(input_shape)

File ~/anaconda3/envs/art_intel/lib/python3.9/site-packages/tensorflow_addons/layers/normalizations.py:227, in GroupNormalization._check_size_of_dimensions(self, input_shape)
225 dim = input_shape[self.axis]
226 if dim < self.groups:
--> 227 raise ValueError(
228 "Number of groups (" + str(self.groups) + ") cannot be "
229 "more than the number of channels (" + str(dim) + ")."
230 )
232 if dim % self.groups != 0:
233 raise ValueError(
234 "Number of groups (" + str(self.groups) + ") must be a "
235 "multiple of the number of channels (" + str(dim) + ")."
236 )

ValueError: Exception encountered when calling layer "u_net_model_1" (type UNetModel).

in user code:

File "/home/ec2-user/anaconda3/envs/art_intel/lib/python3.9/site-packages/stable_diffusion_tf/diffusion_model.py", line 199, in apply  *
    x = layer([x, emb])
File "/home/ec2-user/anaconda3/envs/art_intel/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler  **
    raise e.with_traceback(filtered_tb) from None
File "/tmp/__autograph_generated_filem_kzpxnn.py", line 11, in tf__call
    h = ag__.converted_call(ag__.ld(apply_seq), (ag__.ld(x), ag__.ld(self).in_layers), None, fscope)
File "/tmp/__autograph_generated_file612zmgqy.py", line 23, in tf__apply_seq

ag__.for_stmt(ag__.ld(layers), None, loop_body, get_state, set_state, ('x',), {'iterate_names': 'l'})
File "/tmp/autograph_generated_file612zmgqy.py", line 21, in loop_body
x = ag.converted_call(ag__.ld(l), (ag__.ld(x),), None, fscope)
File "/home/ec2-user/anaconda3/envs/art_intel/lib/python3.9/site-packages/tensorflow_addons/layers/normalizations.py", line 110, in build
self._check_size_of_dimensions(input_shape)
File "/home/ec2-user/anaconda3/envs/art_intel/lib/python3.9/site-packages/tensorflow_addons/layers/normalizations.py", line 227, in _check_size_of_dimensions
raise ValueError(

ValueError: Exception encountered when calling layer "res_block_22" "                 f"(type ResBlock).

in user code:

    File "/home/ec2-user/anaconda3/envs/art_intel/lib/python3.9/site-packages/stable_diffusion_tf/diffusion_model.py", line 31, in call  *
        h = apply_seq(x, self.in_layers)
    File "/home/ec2-user/anaconda3/envs/art_intel/lib/python3.9/site-packages/stable_diffusion_tf/layers.py", line 41, in apply_seq  *
        x = l(x)
    File "/home/ec2-user/anaconda3/envs/art_intel/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler  **
        raise e.with_traceback(filtered_tb) from None
    File "/home/ec2-user/anaconda3/envs/art_intel/lib/python3.9/site-packages/tensorflow_addons/layers/normalizations.py", line 110, in build
        self._check_size_of_dimensions(input_shape)
    File "/home/ec2-user/anaconda3/envs/art_intel/lib/python3.9/site-packages/tensorflow_addons/layers/normalizations.py", line 227, in _check_size_of_dimensions
        raise ValueError(

    ValueError: Number of groups (32) cannot be more than the number of channels (4).


Call arguments received by layer "res_block_22" "                 f"(type ResBlock):
  • inputs=['tf.Tensor(shape=(None, 320, 125, 4), dtype=float32)', 'tf.Tensor(shape=(None, 1280), dtype=float32)']

Call arguments received by layer "u_net_model_1" (type UNetModel):
• inputs=['tf.Tensor(shape=(None, 125, 125, 4), dtype=float32)', 'tf.Tensor(shape=(None, 320), dtype=float32)', 'tf.Tensor(shape=(None, 77, 768), dtype=float32)']

[WSINTRA]

What size did you try to make the image?

…

On May 1, 2023, at 09:22, dentistfrankchen ***@***.***> wrote: self._check_size_of_dimensions(input_shape

[dentistfrankchen]

@WSINTRA
A 512x512 image.
I have already tried the code on the main page and added img_height=..., img_width=..., but that did not work. I still got the same error.