defmodule ExTorch.MixProject do
  use Mix.Project

  def project do
    [
      app: :extorch,
      version: "0.4.0",
      elixir: "~> 1.16",
      start_permanent: Mix.env() == :prod,
      deps: deps(),
      docs: docs(),
      test_coverage: [
        ignore_modules: [
          ExTorch.DType,
          ExTorch.DelegateWithDocs,
          ExTorch.DelegateWithDocs.Error,
          ExTorch.Device,
          ExTorch.Layout,
          ExTorch.MemoryFormat,
          ExTorch.ModuleMixin,
          ExTorch.Native.BindingDeclaration,
          ExTorch.Native.Macros,
          ExTorch.Index.Slice,
          ExTorch.Utils.ListWrapper,
          Inspect.ExTorch.Tensor,
          Inspect.ExTorch.JIT.Model,
          Inspect.ExTorch.NN.Layer,
          Inspect.ExTorch.Tensor.BlobView,
          Mix.Tasks.PullLibTorch
        ]
      ],
      description: description(),
      package: package()
      # compilers: [:rustler] ++ Mix.compilers(),
      # rustler_crates: [extorch_native: []]
    ]
  end

  # Run "mix help compile.app" to learn about applications.
  def application do
    [
      mod: {ExTorch.Application, []},
      extra_applications: [:logger, :ssl, :inets]
    ]
  end

  # Run "mix help deps" to learn about dependencies.
  defp deps do
    [
      {:rustler, "~> 0.37.3"},
      {:telemetry, "~> 1.2"},
      {:ex_doc, "~> 0.35", only: :dev, runtime: false},
      # {:credo, "~> 1.7", only: [:dev, :test], runtime: false},
      {:dialyxir, "~> 1.4", only: [:dev], runtime: false},
      {:phoenix_live_dashboard, "~> 0.8", optional: true}
    ]
  end

  defp description do
    "Production ML model serving on the BEAM. Serve PyTorch models faster than Python with pre-compiled graph execution, AOTI compiled inference, and OTP fault tolerance."
  end

  defp package do
    [
      # This option is only needed when you don't want to use the OTP application name
      name: "extorch",
      # These are the default files included in the package
      files: ~w(lib priv native .formatter.exs mix.exs README* LICENSE* CHANGELOG* CLAUDE.md),
      exclude_patterns: [
        "native/extorch/target",
        "native/extorch/.cargo",
        "priv/native/libtorch",
        "priv/native/libextorch.so",
        "native/extorch/src/native/native.rs.sum"
      ],
      licenses: ["MIT"],
      links: %{"GitHub" => "https://github.com/andfoy/extorch"}
    ]
  end

  defp docs do
    [
      main: "getting-started",
      extras: [
        "guides/getting-started.md",
        "guides/serving-models.md",
        "guides/neural-network-dsl.md",
        "guides/observability.md"
      ],
      groups_for_extras: [
        Guides: Path.wildcard("guides/*.md")
      ],
      # You can specify a function for adding
      # custom content to the generated HTML.
      # This is useful for custom JS/CSS files you want to include.
      before_closing_body_tag: &before_closing_body_tag/1,
      groups_for_docs: [
        {:"Per-process settings", &(&1[:kind] == :process_values)},
        {:"Tensor information", &(&1[:kind] == :tensor_info)},
        {:"Tensor creation", &(&1[:kind] == :tensor_creation)},
        {:"Tensor manipulation", &(&1[:kind] == :tensor_manipulation)},
        {:"Tensor indexing", &(&1[:kind] == :tensor_indexing)},
        {:"Pointwise math operations", &(&1[:kind] == :tensor_pointwise)},
        {:"Reduction operations", &(&1[:kind] == :tensor_reduction)},
        {:"Comparison operations", &(&1[:kind] == :tensor_comparison)},
        {:"Other operations", &(&1[:kind] == :tensor_other_ops)}
      ],
      groups_for_modules: [
        "General API": [ExTorch, ExTorch.Tensor],
        "JIT Model Serving": [
          ExTorch.JIT,
          ExTorch.JIT.Model,
          ExTorch.JIT.Server
        ],
        "Neural Network": [
          ExTorch.NN,
          ExTorch.NN.Module,
          ExTorch.NN.Layer,
          ExTorch.NN.Introspect,
          ExTorch.NN.Introspect.Schema,
          ExTorch.NN.JITBackedModel
        ],
        "NN Layers": [
          ExTorch.NN.Linear,
          ExTorch.NN.Conv1d,
          ExTorch.NN.Conv2d,
          ExTorch.NN.Conv3d,
          ExTorch.NN.ConvTranspose1d,
          ExTorch.NN.ConvTranspose2d,
          ExTorch.NN.MaxPool1d,
          ExTorch.NN.MaxPool2d,
          ExTorch.NN.AvgPool1d,
          ExTorch.NN.AvgPool2d,
          ExTorch.NN.AdaptiveAvgPool1d,
          ExTorch.NN.AdaptiveAvgPool2d,
          ExTorch.NN.BatchNorm1d,
          ExTorch.NN.BatchNorm2d,
          ExTorch.NN.LayerNorm,
          ExTorch.NN.GroupNorm,
          ExTorch.NN.InstanceNorm1d,
          ExTorch.NN.InstanceNorm2d,
          ExTorch.NN.Dropout,
          ExTorch.NN.Embedding,
          ExTorch.NN.LSTM,
          ExTorch.NN.GRU,
          ExTorch.NN.MultiheadAttention,
          ExTorch.NN.Flatten,
          ExTorch.NN.Unflatten
        ],
        "NN Activations": [
          ExTorch.NN.ReLU,
          ExTorch.NN.LeakyReLU,
          ExTorch.NN.GELU,
          ExTorch.NN.ELU,
          ExTorch.NN.SiLU,
          ExTorch.NN.Mish,
          ExTorch.NN.PReLU,
          ExTorch.NN.Sigmoid,
          ExTorch.NN.Tanh,
          ExTorch.NN.Softmax,
          ExTorch.NN.LogSoftmax
        ],
        "Tensor Exchange": [
          ExTorch.Tensor.Blob,
          ExTorch.Tensor.BlobView
        ],
        "AOTI Compiled Models": [
          ExTorch.AOTI,
          ExTorch.AOTI.Model,
          ExTorch.AOTI.Server
        ],
        "Export Reader": [
          ExTorch.Export,
          ExTorch.Export.Model,
          ExTorch.Export.Server
        ],
        "Observability": [
          ExTorch.Metrics,
          ExTorch.Observer.Dashboard
        ],
        "Exchange types": [
          ExTorch.Complex,
          ExTorch.Index,
          ExTorch.Index.Slice,
          ExTorch.Tensor.Options,
          ExTorch.Utils.PrintOptions,
          ExTorch.Utils.ListWrapper
        ],
        "Spec types": [
          ExTorch.Scalar,
          ExTorch.DType,
          ExTorch.Device,
          ExTorch.Layout,
          ExTorch.MemoryFormat
        ],
        Protocols: [ExTorch.Protocol.DefaultStruct],
        Macros: [
          ExTorch.Native.Macros,
          ExTorch.Native.BindingDeclaration,
          ExTorch.DelegateWithDocs,
          ExTorch.ModuleMixin
        ],
        "Native API": [ExTorch.Native],
        "Other utilities": [ExTorch.Utils, ExTorch.Utils.Types]
      ]
      # ...
    ]
  end

  # In our case we simply add a <script> tag
  # that loads MathJax from CDN and specify the configuration.
  # Once loaded, the script will dynamically turn any LaTeX
  # expressions on the page into SVG images.
  defp before_closing_body_tag(:html) do
    """
    <script>
      window.MathJax = {
        tex: {
          inlineMath: [['$', '$']],
          displayMath: [['$$','$$']],
        },
      };
    </script>
    <script type="text/javascript" src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-svg.js"></script>
    """
  end

  defp before_closing_body_tag(_), do: ""
end