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Relaxed transformers dependency (#270)
## Summary - Make the `transformers` dependency optional so we only have `torch` and `triton` as required deps, which is helpful if you're not using `transformers` for modeling code. This was also causing installation issues for people using slightly older transformers versions. - If transformers is needed, make it compatible with any 4.x version. The specific model being used should dictate the transformers version compatibility. ## Testing Done `pip install -e .[transformers]` `pip install -e .[dev]` A100-80G-PCIe - Hardware Type: A100-80G-PCIe - [x] run `make test` to ensure correctness - [x] run `make checkstyle` to ensure code style - [x] run `make test-convergence` to ensure convergence
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@@ -106,7 +106,10 @@ With one line of code, Liger Kernel can increase throughput by more than 20% and
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- `torch >= 2.1.2`
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- `triton >= 2.3.0`
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- `transformers >= 4.42.0`
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### Optional Dependencies
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- `transformers >= 4.x`: Required if you plan to use the transformers models patching APIs. The specific model you are working will dictate the minimum version of transformers.
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> **Note:**
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> Our kernels inherit the full spectrum of hardware compatibility offered by [Triton](https://github.com/triton-lang/triton).
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@@ -129,7 +132,10 @@ To install from source:
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git clone https://github.com/linkedin/Liger-Kernel.git
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cd Liger-Kernel
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pip install -e .
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# or if using transformers
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pip install -e .[transformers]
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```
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## Getting Started
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There are a couple of ways to apply Liger kernels, depending on the level of customization required.
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+5
-2
@@ -12,18 +12,21 @@ license = { file = "LICENSE" }
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dependencies = [
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"torch>=2.1.2",
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"triton>=2.3.0",
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"transformers>=4.42.0"
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]
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[project.optional-dependencies]
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transformers = [
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"transformers~=4.0"
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]
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dev = [
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"transformers>=4.44.2",
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"matplotlib>=3.7.2",
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"flake8>=4.0.1.1",
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"black>=24.4.2",
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"isort>=5.13.2",
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"pytest>=7.1.2",
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"datasets>=2.19.2",
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"jupyter==1.0.0",
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"seaborn",
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]
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