Description
I installed web-stable-diffusion according to the official documentation, but it couldn't run. It seemed to be caused by changes in relax.
/web-stable-diffusion# python3 build.py --target cuda
Loading pipeline components...: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:00<00:00, 17.38it/s]
/root/anaconda3/envs/mlc/lib/python3.9/site-packages/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py:181: FutureWarning: The configuration file of this scheduler: LCMScheduler {
"_class_name": "LCMScheduler",
"_diffusers_version": "0.24.0",
"beta_end": 0.012,
"beta_schedule": "scaled_linear",
"beta_start": 0.00085,
"clip_sample": false,
"clip_sample_range": 1.0,
"dynamic_thresholding_ratio": 0.995,
"num_train_timesteps": 1000,
"original_inference_steps": 50,
"prediction_type": "epsilon",
"rescale_betas_zero_snr": false,
"sample_max_value": 1.0,
"set_alpha_to_one": true,
"steps_offset": 0,
"thresholding": false,
"timestep_scaling": 10.0,
"timestep_spacing": "leading",
"trained_betas": null
}
is outdated. steps_offset should be set to 1 instead of 0. Please make sure to update the config accordingly as leaving steps_offset might led to incorrect results in future versions. If you have downloaded this checkpoint from the Hugging Face Hub, it would be very nice if you could open a Pull request for the scheduler/scheduler_config.json file
deprecate("steps_offset!=1", "1.0.0", deprecation_message, standard_warn=False)
Traceback (most recent call last):
File "/root/zrx/web-stable-diffusion/build.py", line 158, in
mod, params = trace_models(torch_dev_key)
File "/root/zrx/web-stable-diffusion/build.py", line 81, in trace_models
clip = trace.clip_to_text_embeddings(pipe)
File "/root/zrx/web-stable-diffusion/web_stable_diffusion/trace/model_trace.py", line 27, in clip_to_text_embeddings
mod = dynamo_capture_subgraphs(
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/tvm/relax/frontend/torch/dynamo.py", line 198, in dynamo_capture_subgraphs
compiled_model(*params, **kwargs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/eval_frame.py", line 328, in _fn
return fn(*args, **kwargs)
File "/root/zrx/web-stable-diffusion/web_stable_diffusion/trace/model_trace.py", line 20, in forward
text_embeddings = self.clip(text_input_ids)[0]
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/transformers/models/clip/modeling_clip.py", line 800, in forward
return self.text_model(
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/transformers/models/clip/modeling_clip.py", line 697, in forward
causal_attention_mask = _create_4d_causal_attention_mask(
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/eval_frame.py", line 490, in catch_errors
return callback(frame, cache_entry, hooks, frame_state)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 641, in _convert_frame
result = inner_convert(frame, cache_size, hooks, frame_state)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 133, in _fn
return fn(*args, **kwargs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 389, in _convert_frame_assert
return _compile(
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 569, in _compile
guarded_code = compile_inner(code, one_graph, hooks, transform)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/utils.py", line 189, in time_wrapper
r = func(*args, **kwargs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 491, in compile_inner
out_code = transform_code_object(code, transform)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/bytecode_transformation.py", line 1028, in transform_code_object
transformations(instructions, code_options)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 458, in transform
tracer.run()
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 2069, in run
super().run()
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 719, in run
and self.step()
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 683, in step
getattr(self, inst.opname)(inst)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 2157, in RETURN_VALUE
self.output.compile_subgraph(
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/output_graph.py", line 857, in compile_subgraph
self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root)
File "/root/anaconda3/envs/mlc/lib/python3.9/contextlib.py", line 79, in inner
return func(*args, **kwds)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/output_graph.py", line 957, in compile_and_call_fx_graph
compiled_fn = self.call_user_compiler(gm)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/utils.py", line 189, in time_wrapper
r = func(*args, **kwargs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/_dynamo/output_graph.py", line 1024, in call_user_compiler
raise BackendCompilerFailed(self.compiler_fn, e).with_traceback(
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/dynamo/output_graph.py", line 1009, in call_user_compiler
compiled_fn = compiler_fn(gm, self.example_inputs())
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/dynamo/repro/after_dynamo.py", line 117, in debug_wrapper
compiled_gm = compiler_fn(gm, example_inputs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/torch/init.py", line 1607, in call
return self.compiler_fn(model, inputs, **self.kwargs)
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/tvm/relax/frontend/torch/dynamo.py", line 184, in capture
mod = from_fx(
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/tvm/relax/frontend/torch/fx_translator.py", line 1635, in from_fx
return TorchFXImporter().from_fx(
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/tvm/relax/frontend/torch/fx_translator.py", line 1522, in from_fx
self.env[node] = self.convert_mapfunc_name
File "/root/anaconda3/envs/mlc/lib/python3.9/site-packages/tvm/relax/frontend/torch/fx_translator.py", line 1291, in _getitem
raise ValueError("Multiple tensors as index not yet supported")
torch._dynamo.exc.BackendCompilerFailed: backend='_capture' raised:
ValueError: Multiple tensors as index not yet supported
Set TORCH_LOGS="+dynamo" and TORCHDYNAMO_VERBOSE=1 for more information
You can suppress this exception and fall back to eager by setting:
import torch._dynamo
torch._dynamo.config.suppress_errors = True
[12:20:18] /workspace/tvm/src/relax/ir/block_builder.cc:64: Warning: BlockBuilder destroyed with remaining blocks!