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torch-webgpu

Supported Ops

jmaczan/torch-webgpu

Supported Operations¶

torch-webgpu supports many PyTorch operations. This page lists what's available.

Tensor Creation¶

Operation	Status	Notes
`torch.tensor()`	✅
`torch.zeros()`	✅
`torch.ones()`	✅
`torch.randn()`	✅
`torch.arange()`	✅
`torch.full()`	✅
`torch.empty()`	✅

Arithmetic Operations¶

Operation	Status	Notes
`+` / `torch.add()`	✅
`-` / `torch.sub()`	✅
`*` / `torch.mul()`	✅
`/` / `torch.div()`	✅
`-x` / `torch.neg()`	✅
`torch.pow()`	✅

Matrix Operations¶

Operation	Status	Notes
`@` / `torch.matmul()`	✅
`torch.mm()`	✅
`F.linear()`	✅

Activation Functions¶

Operation	Status	Notes
`torch.relu()`	✅
`F.silu()`	✅
`F.gelu()`	✅
`torch.tanh()`	✅
`F.softmax()`	✅
`torch.sigmoid()`	🚧	Coming soon

Math Functions¶

Operation	Status	Notes
`torch.exp()`	✅
`torch.log()`	🚧
`torch.sqrt()`	✅
`torch.rsqrt()`	✅
`torch.cos()`	✅
`torch.sin()`	✅
`torch.abs()`	🚧

Reduction Operations¶

Operation	Status	Notes
`torch.sum()`	✅
`torch.mean()`	✅
`torch.max()`	✅
`torch.min()`	✅
`torch.argmax()`	✅
`torch.cumsum()`	✅

Shape Operations¶

Operation	Status	Notes
`view()`	✅
`reshape()`	✅
`transpose()`	✅
`permute()`	✅
`squeeze()`	✅
`unsqueeze()`	✅
`expand()`	✅
`contiguous()`	✅
`clone()`	✅

Indexing & Slicing¶

Operation	Status	Notes
`tensor[idx]`	✅
`tensor[start:end]`	✅
`torch.cat()`	✅
`torch.index_select()`	✅

Comparison Operations¶

Operation	Status	Notes
`==` / `torch.eq()`	✅
`!=` / `torch.ne()`	✅
`<` / `torch.lt()`	✅
`<=` / `torch.le()`	✅
`>` / `torch.gt()`	✅
`>=` / `torch.ge()`	✅
`torch.where()`	✅

Neural Network Layers¶

Operation	Status	Notes
`F.linear()`	✅
`F.embedding()`	✅
`F.layer_norm()`	✅
`F.scaled_dot_product_attention()`	✅
`F.dropout()`	✅	Identity in eval mode

Type Casting¶

Operation	Status	Notes
`.float()`	✅
`.half()`	🚧
`.int()`	✅
`.long()`	✅
`.bool()`	✅
`.to(dtype)`	✅

Legend¶

✅ Supported
🚧 Coming soon / Partial support
❌ Not supported

Missing an Op?¶

If you need an operation that's not listed:

Check if it works anyway (many ops just work)
Open an issue
Submit a PR