Fix TPU (torch_xla) compatibility Error about tensor repeat func along with empty dim.

[JerryWu-code]

What does this PR do?

In ‎src/diffusers/models/transformers/transformer_z_image.py, there exists a image_padding_len for padding image to be multiple of SEQ_MULTI_OF. However, when the image shape is already multiple of SEQ_MULTI_OF, this will create a tensor with zero shape. This triggers INVALID_ARGUMENT: Concatenate expects at least one argument. for torch_xla.device() on TPU. This error currently won't emerge when changing device to cpu or cuda, but is in trouble with xla on TPU.

Fixes #12742 and #12743. And it's a final version of #12743 and built upon it.

Fixes # (issue)

• This PR fixes compatibility of torch.Tensor repeat func error with empty dim for TPU in torch_xla.

Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

This pr:

• Issue finder: @lime-j
• Bug fixer: @lime-j @JerryWu-code
• Review: @yiyixuxu @JerryWu-code
• Test Case: @JerryWu-code

Minimal Test Cases in TPU

You could try this on Colab when changing to TPU backend:

import torch
import torch_xla
import torch_xla.core.xla_model as xm

def test_device(device_name, device):
    """Test repeat(0, 1) behavior"""
    print(f"\n{'='*60}")
    print(f"Device: {device_name} ({device})")
    print('='*60)
    
    tensor = torch.randn(64, 2048).to(device)
    
    # Test 1: repeat(0, 1)
    try:
        result = tensor[-1:].repeat(0, 1)
        print(f"✅ Success repeat(0, 1): {result.shape}")
    except RuntimeError as e:
        print(f"❌ Failed repeat(0, 1): {str(e)[:50]}")
    
    # Test 2: Avoid repeat(0)
    padding_len = 0
    result = tensor if padding_len == 0 else torch.cat([tensor, tensor[-1:].repeat(padding_len, 1)], dim=0)
    print(f"✅ Success fix: {result.shape}")

# (1) Test TPU
torch_xla.experimental.eager_mode(True)
test_device("TPU/XLA", torch_xla.device())

# (2) CUDA/CPU
if torch.cuda.is_available():
    test_device("CUDA", torch.device("cuda:0"))
else:
    test_device("CPU", torch.device("cpu"))

And you would get like:

============================================================
Device: TPU/XLA (xla:0)
============================================================
❌ Failed repeat(0, 1): Concatenate expects at least one argument.
✅ Success fix: torch.Size([64, 2048])

============================================================
Device: CPU (cpu)
============================================================
✅ Success repeat(0, 1): torch.Size([0, 2048])
✅ Success fix: torch.Size([64, 2048])

[yiyixuxu]

thanks!

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