[CI] Some improvements to Nightly reports summaries

[DN6]

What does this PR do?

We currently create summary reports for each test module, but the number of pipelines we test in the nightlys has grown considerably. Scrolling through them all is starting to get challenging. This PR introduces an additional step that consolidates the individual reports into a single report with some useful summary information.

A shorter summary report is also sent to the diffusers-ci Slack Channel with a link to the full report in Github Actions.

Example report below

# Diffusers Nightly Test Report
Generated on: 2025-03-28 12:04:31

## Summary
|:---------------|:---------|
| Total Tests    | 2429     |
| Passed         | 2121     |
| Failed         | 11       |
| Skipped        | 293      |
| Success Rate   | 87.32%   |
| Total Duration | 1768.28s |

## Test Suites
| Test Suite                                                  |   Tests |   Passed |   Failed |   Skipped | Success Rate   |   Duration (s) |
|:------------------------------------------------------------|--------:|---------:|---------:|----------:|:---------------|---------------:|
| torch_models_cuda/tests_torch_models_cuda                   |    2016 |     1729 |        6 |       277 | 85.76%         |         576.82 |
| torch_minimum_version_cuda/tests_torch_minimum_version_cuda |     250 |      235 |        3 |        12 | 94.00%         |         498.16 |
| pipeline_cogvideo/tests_pipeline_cogvideo_cuda              |     135 |      129 |        2 |         4 | 95.56%         |         332.4  |
| torch_cuda_gguf_reports/tests_gguf_torch_cuda               |      28 |       28 |        0 |         0 | 100.00%        |         360.9  |

## Slowest Tests
|   Rank | Test                                                                                                                     |   Duration (s) | Test Suite                                                  |
|-------:|:-------------------------------------------------------------------------------------------------------------------------|---------------:|:------------------------------------------------------------|
|      1 | tests/pipelines/test_pipelines_auto.py::AutoPipelineIntegrationTest::test_from_pipe_consistent                           |         156.63 | torch_minimum_version_cuda/tests_torch_minimum_version_cuda |
|      2 | tests/pipelines/cogvideo/test_cogvideox_image2video.py::CogVideoXImageToVideoPipelineIntegrationTests::test_cogvideox    |         139.11 | pipeline_cogvideo/tests_pipeline_cogvideo_cuda              |
|      3 | tests/pipelines/cogvideo/test_cogvideox.py::CogVideoXPipelineIntegrationTests::test_cogvideox                            |         106.64 | pipeline_cogvideo/tests_pipeline_cogvideo_cuda              |
|      4 | tests/quantization/gguf/test_gguf.py::SD35MediumGGUFSingleFileTests::test_pipeline_inference                             |          81.41 | torch_cuda_gguf_reports/tests_gguf_torch_cuda               |
|      5 | tests/pipelines/test_pipelines.py::PipelineNightlyTests::test_ddpm_ddim_equality_batched                                 |          80.82 | torch_minimum_version_cuda/tests_torch_minimum_version_cuda |
|      6 | tests/quantization/gguf/test_gguf.py::SD35LargeGGUFSingleFileTests::test_pipeline_inference                              |          76.58 | torch_cuda_gguf_reports/tests_gguf_torch_cuda               |
|      7 | tests/quantization/gguf/test_gguf.py::FluxGGUFSingleFileTests::test_pipeline_inference                                   |          54.15 | torch_cuda_gguf_reports/tests_gguf_torch_cuda               |
|      8 | tests/pipelines/test_pipelines.py::PipelineSlowTests::test_weighted_prompts_compel                                       |          40.98 | torch_minimum_version_cuda/tests_torch_minimum_version_cuda |
|      9 | tests/models/autoencoders/test_models_consistency_decoder_vae.py::ConsistencyDecoderVAEIntegrationTests::test_vae_tiling |          34.08 | torch_models_cuda/tests_torch_models_cuda                   |
|     10 | tests/pipelines/test_pipelines_auto.py::AutoPipelineIntegrationTest::test_controlnet                                     |          30.95 | torch_minimum_version_cuda/tests_torch_minimum_version_cuda |

## Failures
### AutoPipelineIntegrationTest
tests/pipelines/test_pipelines_auto.py::AutoPipelineIntegrationTest::test_from_pipe_consistent - ValueError: You are trying to load model files of the `variant=fp16`, but no such modeling files are available.
tests/pipelines/test_pipelines_auto.py::AutoPipelineIntegrationTest::test_pipe_auto - ValueError: You are trying to load model files of the `variant=fp16`, but no such modeling files are available.

### AutoencoderOobleckIntegrationTests
tests/models/autoencoders/test_models_autoencoder_oobleck.py::AutoencoderOobleckIntegrationTests::test_stable_diffusion_0 - ImportError: Numba needs NumPy 2.1 or less. Got NumPy 2.2.
tests/models/autoencoders/test_models_autoencoder_oobleck.py::AutoencoderOobleckIntegrationTests::test_stable_diffusion_1 - ImportError: Numba needs NumPy 2.1 or less. Got NumPy 2.2.
tests/models/autoencoders/test_models_autoencoder_oobleck.py::AutoencoderOobleckIntegrationTests::test_stable_diffusion_encode_decode_0 - ImportError: Numba needs NumPy 2.1 or less. Got NumPy 2.2.
tests/models/autoencoders/test_models_autoencoder_oobleck.py::AutoencoderOobleckIntegrationTests::test_stable_diffusion_encode_decode_1 - ImportError: Numba needs NumPy 2.1 or less. Got NumPy 2.2.
tests/models/autoencoders/test_models_autoencoder_oobleck.py::AutoencoderOobleckIntegrationTests::test_stable_diffusion_mode - ImportError: Numba needs NumPy 2.1 or less. Got NumPy 2.2.

Fixes # (issue)

Before submitting

• This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
• Did you read the contributor guideline?
• Did you read our philosophy doc (important for complex PRs)?
• Was this discussed/approved via a GitHub issue or the forum? Please add a link to it if that's the case.
• Did you make sure to update the documentation with your changes? Here are the
  documentation guidelines, and
  here are tips on formatting docstrings.
• Did you write any new necessary tests?

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.

[sayakpaul]

Good initiative. Can we see an example message on Slack?

Also, the benefit of the previous action was it pointed to the specific action run of which the failing tests are a part of. Are we doing that in this PR? If not, I emphasize on including that part.

[github-actions]

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the contributing guidelines are likely to be ignored.

[DN6]

@sayakpaul Latest CI Status message in Slack
https://huggingface.slack.com/archives/C06LR0CSR6H/p1749110804130769

Think this PR should be good to merge now.

[sayakpaul]

Much better. Thanks a lot for iterating!