Implement prototype for torch based fermionic library.

.github/workflows/CI.yml

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+name: CI
+
+on: [push, pull_request]
+
+jobs:
+  CI:
+
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - python-version: "3.10"
+            pytorch-version: "1.12"
+          - python-version: "3.10"
+            pytorch-version: "1.13"
+          - python-version: "3.10"
+            pytorch-version: "2.0"
+          - python-version: "3.10"
+            pytorch-version: "2.1"
+
+          - python-version: "3.11"
+            pytorch-version: "1.13"
+          - python-version: "3.11"
+            pytorch-version: "2.0"
+          - python-version: "3.11"
+            pytorch-version: "2.1"
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install requirements
+        run: |
+          pip install pylint==2.17 mypy==1.6 pytest==7.4 pytest-cov==4.1
+          pip install torch==${{ matrix.pytorch-version }}+cpu --index-url https://download.pytorch.org/whl/cpu
+          pip install multimethod
+      - name: Run pylint
+        run: pylint tat tests
+        working-directory: ${{ github.workspace }}
+      - name: Run mypy
+        run: mypy tat tests
+        working-directory: ${{ github.workspace }}
+      - name: Run pytest
+        run: pytest
+        working-directory: ${{ github.workspace }}

.gitignore

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+.coverage
+.mypy_cache
+__pycache__
+env

README.md

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+# TAT
+
+A Fermionic tensor library based on pytorch.

pyproject.toml

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+[project]
+name = "tat"
+version = "0.4.0"
+authors = [
+  {email = "[email protected]", name = "Hao Zhang"}
+]
+description = "A Fermionic tensor library based on pytorch."
+readme = "README.md"
+requires-python = ">=3.10"
+license = {text = "GPL-3.0-or-later"}
+dependencies = [
+  "multimethod>=1.9",
+  "torch>=1.12",
+]
+
+[tool.pylint]
+max-line-length = 120
+generated-members = "torch.*"
+init-hook="import sys; sys.path.append(\".\")"
+
+[tool.yapf]
+based_on_style = "google"
+column_limit = 120
+
+[tool.mypy]
+check_untyped_defs = true
+disallow_untyped_defs = true
+
+[tool.pytest.ini_options]
+pythonpath = "."
+testpaths = ["tests",]
+addopts = "--cov=tat"

tat/__init__.py

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+"""
+The tat is a Fermionic tensor library based on pytorch.
+"""
+
+from .edge import Edge
+from .tensor import Tensor

tat/_utility.py

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+"""
+Some internal utilities used by tat.
+"""
+
+import torch
+
+# pylint: disable=missing-function-docstring
+# pylint: disable=no-else-return
+
+
+def unsqueeze(tensor: torch.Tensor, index: int, rank: int) -> torch.Tensor:
+    return tensor.reshape([-1 if i == index else 1 for i in range(rank)])
+
+
+def neg_symmetry(tensor: torch.Tensor) -> torch.Tensor:
+    if tensor.dtype is torch.bool:
+        return tensor
+    else:
+        return -tensor
+
+
+def add_symmetry(tensor_1: torch.Tensor, tensor_2: torch.Tensor) -> torch.Tensor:
+    if tensor_1.dtype is torch.bool:
+        return torch.logical_xor(tensor_1, tensor_2)
+    else:
+        return torch.add(tensor_1, tensor_2)
+
+
+def zero_symmetry(tensor: torch.Tensor) -> torch.Tensor:
+    # pylint: disable=singleton-comparison
+    if tensor.dtype is torch.bool:
+        return tensor == False
+    else:
+        return tensor == 0
+
+
+def parity(tensor: torch.Tensor) -> torch.Tensor:
+    if tensor.dtype is torch.bool:
+        return tensor
+    else:
+        return tensor % 2 != 0