67 lines
1.9 KiB
Python
67 lines
1.9 KiB
Python
"""Validate tools.export_onnx with a tiny synthetic model."""
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from __future__ import annotations
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import json
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from pathlib import Path
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import pytest
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import torch
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from tools.export_onnx import (
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_check_flow_parity,
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_check_scroll_parity,
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export_flow_model,
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export_scroll_decoder,
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)
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@pytest.fixture
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def tiny_flow_ckpt(tmp_path: Path) -> Path:
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"""A flow model with seq_len=8, d_model=16, 1 layer — small but valid."""
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from tools.models import TrajectoryFlowModel
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cfg = {
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"seq_len": 8,
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"d_model": 16,
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"nhead": 2,
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"num_layers": 1,
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"dim_feedforward": 32,
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"cond_dim": 3,
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}
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model = TrajectoryFlowModel(**cfg, dropout=0.0)
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model.eval()
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out = tmp_path / "flow_ckpt"
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out.mkdir()
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torch.save(model.state_dict(), out / "flow_model.pt")
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(out / "train_config.json").write_text(json.dumps(cfg))
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return out
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@pytest.fixture
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def tiny_scroll_ckpt(tmp_path: Path) -> Path:
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"""A scroll model with seq_len=4, latent=4, hidden=8."""
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from tools.scroll.models import ScrollCVAE
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cfg = {"seq_len": 4, "latent_dim": 4, "hidden": 8, "cond_dim": 7}
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model = ScrollCVAE(**cfg)
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model.eval()
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out = tmp_path / "scroll_ckpt"
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out.mkdir()
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torch.save(model.state_dict(), out / "scroll_model.pt")
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(out / "scroll_config.json").write_text(json.dumps(cfg))
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return out
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def test_export_flow_model_parity(tiny_flow_ckpt: Path, tmp_path: Path) -> None:
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out_dir = tmp_path / "out"
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onnx_path = export_flow_model(tiny_flow_ckpt, out_dir)
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assert onnx_path.exists()
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_check_flow_parity(tiny_flow_ckpt, onnx_path) # raises on failure
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def test_export_scroll_decoder_parity(tiny_scroll_ckpt: Path, tmp_path: Path) -> None:
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out_dir = tmp_path / "out"
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onnx_path = export_scroll_decoder(tiny_scroll_ckpt, out_dir)
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assert onnx_path.exists()
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_check_scroll_parity(tiny_scroll_ckpt, onnx_path)
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