{"id":5921,"library":"einops-exts","title":"einops-exts: Einops Extensions","description":"einops-exts provides personal helper functions and extensions for the `einops` tensor manipulation library, primarily focusing on deep learning frameworks. It is currently at version 0.0.4 and has an irregular release cadence, with the latest release in January 2023.","status":"active","version":"0.0.4","language":"en","source_language":"en","source_url":"https://github.com/lucidrains/einops-exts","tags":["einops","deep learning","tensor manipulation","pytorch","extensions","machine learning"],"install":[{"cmd":"pip install einops-exts","lang":"bash","label":"Install with pip"}],"dependencies":[{"reason":"This library provides extensions for `einops` and is a core dependency.","package":"einops","optional":false},{"reason":"Many extensions are implemented for PyTorch, making it a common practical dependency.","package":"torch","optional":true}],"imports":[{"note":"Classes are typically found within framework-specific submodules like `torch`.","wrong":"from einops_exts import EinopsToAndFrom","symbol":"EinopsToAndFrom","correct":"from einops_exts.torch import EinopsToAndFrom"}],"quickstart":{"code":"import torch\nfrom torch import nn\nfrom einops_exts.torch import EinopsToAndFrom\n\n# Define a simple PyTorch model using EinopsToAndFrom\nclass MyModel(nn.Module):\n    def __init__(self):\n        super().__init__()\n        self.transform = EinopsToAndFrom('b h w c -> b c h w', 'b c h w -> b h w c', nn.Identity())\n        self.conv = nn.Conv2d(3, 64, kernel_size=3, padding=1)\n\n    def forward(self, x):\n        # Input x is expected as (batch, height, width, channels)\n        x = self.transform(x) # Transforms to (batch, channels, height, width) for Conv2d\n        x = self.conv(x)\n        x = self.transform(x) # Transforms back to (batch, height, width, channels)\n        return x\n\n# Example usage\nmodel = MyModel()\ninput_tensor = torch.randn(1, 64, 64, 3) # Batch 1, 64x64, 3 channels\noutput_tensor = model(input_tensor)\n\nprint(f\"Input shape: {input_tensor.shape}\")\nprint(f\"Output shape: {output_tensor.shape}\")","lang":"python","description":"This quickstart demonstrates the `EinopsToAndFrom` layer, a common utility in `einops-exts.torch`, which facilitates tensor shape transformations for PyTorch modules that expect specific dimension orders (e.g., `Conv2d` expecting channel-first data)."},"warnings":[{"fix":"Thoroughly test `einops` patterns. Refer to the `einops` documentation for correct notation and common transformations.","message":"As an extension library, `einops-exts` critically depends on `einops`. Incorrect `einops` pattern strings within `einops-exts` operations will lead to runtime errors due to shape mismatches or invalid axis compositions/decompositions. Users should be familiar with `einops` notation.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Ensure you are using the correct submodule (e.g., `einops_exts.torch`) for your chosen deep learning framework. If no specific submodule exists, the functionality might not be supported for that framework.","message":"While the core `einops` library is framework-agnostic, `einops-exts` primarily provides utilities for PyTorch (e.g., `einops_exts.torch`). Users attempting to use it with other frameworks (TensorFlow, JAX, NumPy) should verify if specific extensions exist for those backends, as direct use of PyTorch-specific modules will fail.","severity":"gotcha","affected_versions":"All versions"},{"fix":"Pin `einops-exts` and `einops` to specific versions in your `requirements.txt` or `pyproject.toml` to prevent unexpected breakages. Regularly review the GitHub repository for updates and changes before upgrading.","message":"The library is in an early development stage (0.0.x versioning). While no explicit breaking changes are documented for `einops-exts` itself, its API might evolve rapidly, and changes in its core dependency (`einops`) could indirectly lead to breaking behavior.","severity":"breaking","affected_versions":"<1.0.0"}],"env_vars":null,"last_verified":"2026-04-14T00:00:00.000Z","next_check":"2026-07-13T00:00:00.000Z","problems":[]}