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Hello,
this code:
```python
def create_look_ahead_mask(size_0):
mask = np.ones((size_0, size_0), dtype=np.int32)
for a in range(size_0): # Timestep
for c in range(size…
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## 🚀 Feature
Unify matrix multiplication operations
## Motivation
Currently, there exists a number of different ways to perform matrix multiplications depending on the layouts of the in…
pearu updated
10 months ago
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## __Description__
AirPLS (Adaptive Iteratively Reweighted Penalized Least Squares) and ArPLS (Asymmetrically Reweighted Penalized Least Squares) are powerful algorithms for removing complex non-li…
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I hope this message finds you well. I have a question regarding the use of FP8 type in GEMM computations, particularly in the context of the `gemm_plugin` and `cublasLtMatmul` functions.
In the `ge…
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In MLA, the KVCache compresses $h_t$ into $C_t^{KV} \in \mathbb{R}^{d_c}$, and to circumvent the issue of incompatibility with RoPE for low-rank KVCache compression, it concatenates $k_t^R = \text{RoP…
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In https://cuelang.org/cl/1192024 we identified the desirability of having a single "encoding matrix" to link to, so users can know which features/etc are supported by which encoders. This issue track…
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Hello,
Is there a plan to extend this awesome work to support matrix operations? For example, converting XYZ matrices to sRGB matrices.
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I can contribute to your code forupper triangular matrix operation.
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The current matrix factorization router (`MFModel`) is unnecessarily complex. Given that all operations in the forward pass are linear with no activations, we can significantly simplify this model.
…
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```
Implement the following:
- construction mechanisms
- assignment operator
- index-based access operators
```
Original issue reported on code.google.com by `cpi...@gmail.com` on 27 Jan 2009 at 5:…