test: define qwen35 pruning contract

MVP/tests/fixtures/qwen35_metadata.json

@@ -0,0 +1,20 @@
+{
+  "hidden_size": 1024,
+  "intermediate_size": 3584,
+  "vocab_size": 248320,
+  "tie_word_embeddings": true,
+  "layer_types": [
+    "linear_attention", "linear_attention", "linear_attention", "full_attention",
+    "linear_attention", "linear_attention", "linear_attention", "full_attention",
+    "linear_attention", "linear_attention", "linear_attention", "full_attention",
+    "linear_attention", "linear_attention", "linear_attention", "full_attention",
+    "linear_attention", "linear_attention", "linear_attention", "full_attention",
+    "linear_attention", "linear_attention", "linear_attention", "full_attention"
+  ],
+  "embedding_params": 254279680,
+  "linear_attention_params": 21555360,
+  "full_attention_params": 18352640,
+  "final_norm_params": 1024,
+  "all_named_params": 873438784,
+  "text_backbone_params": 752393024
+}

MVP/tests/test_pruning_contract.py

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+import json
+from pathlib import Path
+
+import pytest
+
+from MVP.qwen35_prune import (
+    ParameterReport,
+    build_text_config,
+    choose_prefix,
+    translate_text_key,
+)
+from MVP.validate_checkpoint import validate_state_dict_keys
+
+
+FIXTURE = Path(__file__).parent / "fixtures" / "qwen35_metadata.json"
+
+
+def load_fixture():
+    return json.loads(FIXTURE.read_text())
+
+
+def test_measured_n4_prefix_is_inside_required_interval():
+    data = load_fixture()
+    report = ParameterReport(
+        embedding_params=data["embedding_params"],
+        layer_params=tuple(
+            [data["linear_attention_params"]] * 3
+            + [data["full_attention_params"]]
+            + [data["linear_attention_params"]] * 3
+            + [data["full_attention_params"]] * 5
+        ),
+        layer_types=tuple(data["layer_types"]),
+        final_norm_params=data["final_norm_params"],
+        all_named_params=data["all_named_params"],
+    )
+
+    choice = choose_prefix(report, 330_000_000, 350_000_000)
+
+    assert choice.layer_count == 4
+    assert choice.parameter_count == 337_299_424
+    assert 330_000_000 <= choice.parameter_count <= 350_000_000
+
+
+def test_prefix_selection_rejects_incomplete_hybrid_block():
+    data = load_fixture()
+    report = ParameterReport(
+        embedding_params=data["embedding_params"],
+        layer_params=(data["linear_attention_params"],) * 24,
+        layer_types=tuple(data["layer_types"]),
+        final_norm_params=data["final_norm_params"],
+        all_named_params=data["all_named_params"],
+    )
+
+    with pytest.raises(ValueError, match="complete hybrid"):
+        choose_prefix(report, 330_000_000, 350_000_000, requested_layers=3)
+
+
+def test_text_prefix_translation_drops_vision_and_mtp():
+    assert (
+        translate_text_key("model.language_model.layers.3.linear_attn.A_log")
+        == "model.layers.3.linear_attn.A_log"
+    )
+    assert translate_text_key("model.visual.patch_embed.proj.weight") is None
+    assert translate_text_key("mtp.layers.0.mlp.down_proj.weight") is None
+
+
+def test_text_config_is_standalone_and_keeps_live_attention_fields():
+    full = {
+        "model_type": "qwen3_5",
+        "tie_word_embeddings": True,
+        "vision_config": {"hidden_size": 512},
+        "text_config": {
+            "model_type": "qwen3_5_text",
+            "hidden_size": 1024,
+            "intermediate_size": 3584,
+            "num_hidden_layers": 24,
+            "layer_types": list(load_fixture()["layer_types"]),
+            "linear_num_key_heads": 16,
+            "linear_num_value_heads": 16,
+            "linear_key_head_dim": 128,
+            "linear_value_head_dim": 128,
+            "linear_conv_kernel_dim": 4,
+            "vocab_size": 248320,
+        },
+    }
+
+    text = build_text_config(full, 4)
+
+    assert text["model_type"] == "qwen3_5_text"
+    assert text["num_hidden_layers"] == 4
+    assert text["layer_types"] == load_fixture()["layer_types"][:4]
+    assert text["linear_num_value_heads"] == 16
+    assert text["tie_word_embeddings"] is True
+    assert "vision_config" not in text
+
+
+def test_validator_rejects_vision_mtp_and_duplicate_tied_head():
+    config = {
+        "model_type": "qwen3_5_text",
+        "tie_word_embeddings": True,
+        "num_hidden_layers": 4,
+        "layer_types": load_fixture()["layer_types"][:4],
+    }
+    keys = {
+        "model.embed_tokens.weight": (248320, 1024),
+        "model.layers.0.input_layernorm.weight": (1024,),
+        "model.layers.1.input_layernorm.weight": (1024,),
+        "model.layers.2.input_layernorm.weight": (1024,),
+        "model.layers.3.input_layernorm.weight": (1024,),
+        "model.norm.weight": (1024,),
+        "lm_head.weight": (248320, 1024),
+        "model.visual.patch_embed.proj.weight": (1, 1),
+        "mtp.fc.weight": (1, 1),
+    }
+
+    with pytest.raises(ValueError, match="vision|MTP|tied"):
+        validate_state_dict_keys(keys, config, 330_000_000, 350_000_000)
+