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### Describe the question.
### All images are green after the video is decoded.
When I use `fn.readers.video` to decode my own h265 video, the decoded image size is normal, but the pixels are abnorma…
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## Environment
### Hardware Environment(`Ascend`/`GPU`/`CPU`):
CPU and GPU
### Software Environment:
- **MindSpore version (source or binary)**: 2.2.14
- **Python version (e.g., Python 3.7…
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### 🐛 Describe the bug
🐛 Describe the bug
The torch_cpu.dll is ~200 Mb, which is way too large for us. Therefore, we'd like to build torch statically. I followed the procedures hinted in the READM…
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### 🐛 Describe the bug
Test code:
```python
import torch
self = torch.randn([1,1,1,1,1], dtype=torch.complex128)
b = torch.randn([1,1,3,1], dtype=torch.complex128)
torch.linalg.lstsq(self, b…
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Platforms: asan, linux
This test was disabled because it is failing in CI. See [recent examples](https://hud.pytorch.org/flakytest?name=test_device_mode_ops_sparse_sampled_addmm_cpu_float64&suite=Tes…
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### 🐛 Describe the bug
I'm getting profiles like this:
The first `all_to_all_single` / `barrier` are taking large amounts of time (and invoking thousands of `cudaMemcpyAsync`, `cudaGetDevice…
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**Describe the bug**
There is a mismatch in the number of speech references and the number of speakers (which is 2 for the Librimix dataset).
Because of this issue, we cannot run the recipe training…
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### 🐛 Describe the bug
Using MPS, torch.multinomial() always return [0], even when the probability is 0.
It works as expected on CPU:
```
import torch
In [1]: x = torch.tensor([0.5, 0.5], dty…
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### 🐛 Describe the bug
```
import torch
import torch.nn.functional as F
def test_log_softmax(device):
print(f"Testing on {device}")
input_tensor = torch.randn(3, 4, 5, device=device)…
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### 🐛 Describe the bug
I observed the following errors while building PyTorch v1.11 with USE_CUDA=0 on ppc64le:
```
/work/aten/src/ATen/cpu/vec/vec256/vsx/vec256_qint8_vsx.h: In static member fun…