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Question

I’m training latent diffusion with audio encoding of shape batch 16 * channel 256 * n_frame 501 * n_frequency 6.

Traceback (most recent call last):
  File "/home/szding/.pycharm_helpers/pydev/pydevd.py", line 2236, in <module>
    main()
  File "/home/szding/.pycharm_helpers/pydev/pydevd.py", line 2218, in main
    globals = debugger.run(setup['file'], None, None, is_module)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.pycharm_helpers/pydev/pydevd.py", line 1528, in run
    return self._exec(is_module, entry_point_fn, module_name, file, globals, locals)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.pycharm_helpers/pydev/pydevd.py", line 1535, in _exec
    pydev_imports.execfile(file, globals, locals)  # execute the script
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.pycharm_helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"n", file, 'exec'), glob, loc)
  File "/home/szding/v2sa/v2sa/trainer/trainer_ldm.py", line 232, in <module>
    main(config_yaml, arguments.exp_group_name, arguments.exp_name)
  File "/home/szding/v2sa/v2sa/trainer/trainer_ldm.py", line 211, in main
    trainer.fit(model, datamodule, ckpt_path=last_ckpt)
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 544, in fit
    call._call_and_handle_interrupt(
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/trainer/call.py", line 44, in _call_and_handle_interrupt
    return trainer_fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 580, in _fit_impl
    self._run(model, ckpt_path=ckpt_path)
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 987, in _run
    results = self._run_stage()
              ^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/trainer/trainer.py", line 1033, in _run_stage
    self.fit_loop.run()
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/loops/fit_loop.py", line 205, in run
    self.advance()
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/loops/fit_loop.py", line 363, in advance
    self.epoch_loop.run(self._data_fetcher)
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/loops/training_epoch_loop.py", line 140, in run
    self.advance(data_fetcher)
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/loops/training_epoch_loop.py", line 250, in advance
    batch_output = self.automatic_optimization.run(trainer.optimizers[0], batch_idx, kwargs)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 190, in run
    self._optimizer_step(batch_idx, closure)
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 268, in _optimizer_step
    call._call_lightning_module_hook(
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/trainer/call.py", line 157, in _call_lightning_module_hook
    output = fn(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/core/module.py", line 1303, in optimizer_step
    optimizer.step(closure=optimizer_closure)
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/core/optimizer.py", line 152, in step
    step_output = self._strategy.optimizer_step(self._optimizer, closure, **kwargs)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/strategies/strategy.py", line 239, in optimizer_step
    return self.precision_plugin.optimizer_step(optimizer, model=model, closure=closure, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/plugins/precision/precision.py", line 122, in optimizer_step
    return optimizer.step(closure=closure, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/optim/optimizer.py", line 391, in wrapper
    out = func(*args, **kwargs)
          ^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/optim/optimizer.py", line 76, in _use_grad
    ret = func(self, *args, **kwargs)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/optim/adamw.py", line 165, in step
    loss = closure()
           ^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/plugins/precision/precision.py", line 108, in _wrap_closure
    closure_result = closure()
                     ^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 144, in __call__
    self._result = self.closure(*args, **kwargs)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 129, in closure
    step_output = self._step_fn()
                  ^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/loops/optimization/automatic.py", line 318, in _training_step
    training_step_output = call._call_strategy_hook(trainer, "training_step", *kwargs.values())
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/trainer/call.py", line 309, in _call_strategy_hook
    output = fn(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/pytorch_lightning/strategies/strategy.py", line 391, in training_step
    return self.lightning_module.training_step(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/v2sa/v2sa/models/ldm/ldm.py", line 588, in training_step
    loss, loss_dict = self.shared_step(batch)
                      ^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/v2sa/v2sa/models/ldm/ldm.py", line 1262, in shared_step
    loss, loss_dict = self(x, codes, self.filter_useful_cond_dict(c))
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/v2sa/v2sa/models/ldm/ldm.py", line 1299, in forward
    loss, loss_dict = self.p_losses(x, codes, c, t, *args, **kwargs)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/v2sa/v2sa/models/ldm/ldm.py", line 1322, in p_losses
    model_output = self.apply_model(x_noisy, t, cond)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/v2sa/v2sa/models/ldm/ldm.py", line 1312, in apply_model
    x_recon = self.model(x_noisy, t, cond_dict=cond)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/v2sa/v2sa/models/ldm/ldm.py", line 1971, in forward
    out = self.diffusion_model(
          ^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/.conda/envs/v2sa/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/szding/v2sa/v2sa/models/ldm/modules/openai_unetmodel.py", line 880, in forward
    h = th.cat([h, concate_tensor], dim=1)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 252 but got size 251 for tensor number 1 in the list.

I checked the shape of h and concate_tensor:

The shape of UNet input is torch.Size([16, 256, 501, 6])
torch.Size([16, 640, 63, 1]) torch.Size([16, 640, 63, 1])
torch.Size([16, 640, 63, 1]) torch.Size([16, 640, 63, 1])
torch.Size([16, 384, 63, 1]) torch.Size([16, 640, 63, 1])
torch.Size([16, 384, 126, 2]) torch.Size([16, 640, 126, 2])
torch.Size([16, 384, 126, 2]) torch.Size([16, 384, 126, 2])
torch.Size([16, 256, 126, 2]) torch.Size([16, 384, 126, 2])
torch.Size([16, 256, 251, 3]) torch.Size([16, 384, 252, 4])

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Danh mục

latent diffusion – Unet: Sizes of tensors must match except in dimension 1