Rename to torchruntime

Author: cmdr2

.github/workflows/pci-update-workflow.yml

@@ -63,7 +63,7 @@ jobs:
       - name: Update files and generate database
         if: steps.check_changes.outputs.has_changes == 'true'
         run: |
-          python scripts/txt_to_db.py pci.ids.new torch_runtime/gpu_pci_ids.db
+          python scripts/txt_to_db.py pci.ids.new torchruntime/gpu_pci_ids.db
 
       - name: Run tests
         if: steps.check_changes.outputs.has_changes == 'true'
@@ -100,7 +100,7 @@ jobs:
 
           cat pyproject.toml
           cat pci.ids.sha256
-          ls -l torch_runtime/gpu_pci_ids.db
+          ls -l torchruntime/gpu_pci_ids.db
 
       - name: Configure Git
         if: steps.check_changes.outputs.has_changes == 'true'
@@ -111,7 +111,7 @@ jobs:
       # - name: Commit changes
       #   if: steps.check_changes.outputs.has_changes == 'true'
       #   run: |
-      #     git add pci.ids.sha256 torch_runtime/gpu_pci_ids.db pyproject.toml
+      #     git add pci.ids.sha256 torchruntime/gpu_pci_ids.db pyproject.toml
       #     git commit -m "Update PCI database, raw data file and version"
 
       # - name: Create Release
@@ -121,7 +121,7 @@ jobs:
       #     tag_name: v${{ steps.update_version.outputs.new_version }}
       #     name: Release ${{ steps.update_version.outputs.new_version }}
       #     body: |
-      #       Automatic update of PCI database. Install using `pip install --upgrade torch-runtime==${{ steps.update_version.outputs.new_version }}`
+      #       Automatic update of PCI database. Install using `pip install --upgrade torchruntime==${{ steps.update_version.outputs.new_version }}`
       #     draft: false
       #     prerelease: false
 

.github/workflows/pypi-release-workflow.yml

@@ -11,7 +11,7 @@ jobs:
     runs-on: ubuntu-latest
     environment:
       name: pypi-beta
-      url: https://test.pypi.org/p/torch-runtime
+      url: https://test.pypi.org/p/torchruntime
     permissions:
       contents: read
       id-token: write
@@ -31,7 +31,7 @@ jobs:
 
       - name: Copy tests
         run: |
-          cp -R tests torch_runtime/
+          cp -R tests torchruntime/
 
       - name: Build package
         run: python -m build
@@ -43,8 +43,9 @@ jobs:
           cd /tmp/install-test
           pip install *.whl
 
-          python -m torch_runtime --help  # test invocation
-          pytest --pyargs torch-runtime  # run tests
+          pip show torchruntime
+          python -m torchruntime --help  # test invocation
+          pytest --pyargs torchruntime  # run tests
 
       # - name: Publish to PyPI
       #   uses: pypa/gh-action-pypi-publish@release/v1

MANIFEST.in

@@ -1 +1 @@
-include torch_runtime/gpu_pci_ids.db
+include torchruntime/gpu_pci_ids.db

README.md

@@ -1,7 +1,7 @@
-# torch-runtime
+# torchruntime
 [![Discord Server](https://img.shields.io/discord/1014774730907209781?label=Discord)](https://discord.com/invite/u9yhsFmEkB)
 
-**torch-runtime** is a lightweight package for automatically installing the appropriate variant of PyTorch on a user's computer, based on their OS, and GPU manufacturer and GPU model.
+**torchruntime** is a lightweight package for automatically installing the appropriate variant of PyTorch on a user's computer, based on their OS, and GPU manufacturer and GPU model.
 
 This package is used by [Easy Diffusion](https://github.com/easydiffusion/easydiffusion), but you're welcome to use it as well. It's useful for developers who make PyTorch-based apps that target users with NVIDIA, AMD and Intel graphics cards (as well as CPU-only usage), on Windows, Mac and Linux.
 
@@ -15,38 +15,38 @@ It deals with the complexity of the variety of torch builds and configurations r
 # Installation
 Supports Windows, Linux, and Mac.
 
-`pip install torch-runtime`
+`pip install torchruntime`
 
 ## Usage
 ### Step 1. Install the appropriate variant of PyTorch
 *This command should be run on the user's computer, or while creating platform-specific builds:*
 
-`python -m torch_runtime install` (*note the underscore in `torch_runtime`*)
+`python -m torchruntime install`
 
 This will install `torch`, `torchvision`, and `torchaudio`, and will decide the variant based on the user's OS, GPU manufacturer and GPU model number. See [customizing packages](#customizing-packages) for more options.
 
 ### Step 2. Initialize torch
 This should be run inside your program, to initialize the required environment variables (if any) for the variant of torch being used.
 
 ```py
-import torch_runtime
+import torchruntime
 
-torch_runtime.init_torch()
+torchruntime.init_torch()
 ```
 
 ## Customizing packages
-By default, `python -m torch_runtime install` will install the latest available `torch`, `torchvision` and `torchaudio` suitable on the user's platform.
+By default, `python -m torchruntime install` will install the latest available `torch`, `torchvision` and `torchaudio` suitable on the user's platform.
 
 You can customize the packages to install by including their names:
-* For e.g. to install only `torch` and `torchvision`, you can run `python -m torch_runtime install torch torchvision`
-* To install specific versions (in pip format), you can run `python -m torch_runtime install "torch>2.0" "torchvision==0.20"`
+* For e.g. to install only `torch` and `torchvision`, you can run `python -m torchruntime install torch torchvision`
+* To install specific versions (in pip format), you can run `python -m torchruntime install "torch>2.0" "torchvision==0.20"`
 
 **Note:** If you specify package versions, please keep in mind that the version may not be available to *all* the users on *all* the torch platforms. For e.g. a user with Python 3.8 would not be able to install torch 2.5 (or higher), because torch 2.5 dropped support for Python 3.8.
 
-So in general, it's better to avoid specifying a version unless it really matters to you (or you know what you're doing). Instead, please allow `torch-runtime` to pick the latest-possible version for the user.
+So in general, it's better to avoid specifying a version unless it really matters to you (or you know what you're doing). Instead, please allow `torchruntime` to pick the latest-possible version for the user.
 
 # Compatibility table
-The list of platforms on which `torch-runtime` can install a working variant of PyTorch.
+The list of platforms on which `torchruntime` can install a working variant of PyTorch.
 
 **Note:** *This list is based on user feedback (since I don't have all the cards). Please let me know if your card is supported (or not) by opening a pull request or issue or messaging on [Discord](https://discord.com/invite/u9yhsFmEkB) (with supporting logs).*
 
@@ -102,7 +102,7 @@ Different models of AMD cards require different LLVM targets, and sometimes diff
 
 And plenty of AMD cards work with ROCm (even when they aren't in the official list of supported cards). Information about these cards (for e.g. the LLVM target to use) is pretty scattered.
 
-`torch-runtime` deals with this complexity for your convenience.
+`torchruntime` deals with this complexity for your convenience.
 
 # Contributing
 📢 I'm looking for contributions in these specific areas:

pyproject.toml

@@ -3,7 +3,7 @@ requires = [ "setuptools",]
 build-backend = "setuptools.build_meta"
 
 [project]
-name = "torch-runtime"
+name = "torchruntime"
 version = "0.0.0"
 description = "Meant for app developers. A convenient way to install and configure the appropriate version of PyTorch on the user's computer, based on the OS and GPU manufacturer and model number."
 readme = "README.md"
@@ -16,8 +16,8 @@ name = "cmdr2"
 email = "[email protected]"
 
 [project.urls]
-Homepage = "https://github.com/easydiffusion/torch-runtime"
-"Bug Tracker" = "https://github.com/easydiffusion/torch-runtime/issues"
+Homepage = "https://github.com/easydiffusion/torchruntime"
+"Bug Tracker" = "https://github.com/easydiffusion/torchruntime/issues"
 
 [tool.isort]
 profile = "black"

scripts/txt_to_db.py

@@ -4,7 +4,7 @@
 import re
 import sys
 
-from torch_runtime.consts import NVIDIA, INTEL, AMD
+from torchruntime.consts import NVIDIA, INTEL, AMD
 
 # Compile all regular expressions
 ARC_REGEX = re.compile(r"\barc(\b|\W)")

tests/test_device_db.py

@@ -1,4 +1,4 @@
-from torch_runtime.device_db import parse_windows_output, parse_linux_output, parse_macos_output
+from torchruntime.device_db import parse_windows_output, parse_linux_output, parse_macos_output
 
 
 def test_parse_windows_output():

tests/test_device_db_integration.py

@@ -1,12 +1,12 @@
 # Integration test, which connects to the database and checks for some common devices
 
-from torch_runtime.device_db import get_device_infos, DEVICE_DB_FILE
+from torchruntime.device_db import get_device_infos, DEVICE_DB_FILE
 
 
 def test_db_file_exists():
     import os
 
-    db_path = os.path.join("torch_runtime", DEVICE_DB_FILE)
+    db_path = os.path.join("torchruntime", DEVICE_DB_FILE)
     assert os.path.exists(db_path)
 
 

tests/test_installer.py

@@ -1,6 +1,6 @@
 import pytest
 from unittest.mock import patch
-from torch_runtime.installer import get_install_commands, get_pip_commands, run_commands
+from torchruntime.installer import get_install_commands, get_pip_commands, run_commands
 
 
 def test_empty_args():
@@ -30,15 +30,15 @@ def test_rocm_platform():
 
 
 def test_xpu_platform_windows_with_torch_only(monkeypatch):
-    monkeypatch.setattr("torch_runtime.installer.os_name", "Windows")
+    monkeypatch.setattr("torchruntime.installer.os_name", "Windows")
     packages = ["torch"]
     result = get_install_commands("xpu", packages)
     expected_url = "https://download.pytorch.org/whl/test/xpu"
     assert result == [packages + ["--index-url", expected_url]]
 
 
 def test_xpu_platform_windows_with_torchvision(monkeypatch, capsys):
-    monkeypatch.setattr("torch_runtime.installer.os_name", "Windows")
+    monkeypatch.setattr("torchruntime.installer.os_name", "Windows")
     packages = ["torch", "torchvision"]
     result = get_install_commands("xpu", packages)
     expected_url = "https://download.pytorch.org/whl/nightly/xpu"
@@ -48,7 +48,7 @@ def test_xpu_platform_windows_with_torchvision(monkeypatch, capsys):
 
 
 def test_xpu_platform_linux(monkeypatch):
-    monkeypatch.setattr("torch_runtime.installer.os_name", "Linux")
+    monkeypatch.setattr("torchruntime.installer.os_name", "Linux")
     packages = ["torch", "torchvision"]
     result = get_install_commands("xpu", packages)
     expected_url = "https://download.pytorch.org/whl/test/xpu"