feat(standalone)：new operators and platform-standard RISC-V asm backend

pyproject.toml

@@ -9,7 +9,7 @@ description = "A compiler from ONNX models to RISC-V assembly and LLVM IR"
 readme = "README.md"
 license = {text = "MIT"}
 keywords = ["compiler", "risc-v", "onnx", "llvm", "machine-learning"]
-requires-python = ">=3.8"
+requires-python = ">=3.11"
 dependencies = [
     "onnx>=1.14",
     "numpy>=1.24",
@@ -21,9 +21,6 @@ classifiers = [
     "Intended Audience :: Education",
     "License :: OSI Approved :: MIT License",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.8",
-    "Programming Language :: Python :: 3.9",
-    "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Topic :: Software Development :: Compilers",

requirements/ci.txt

@@ -0,0 +1,15 @@
+# CI / verification environment
+# Target Python: 3.11 - 3.12 (the bundled Python 3.8 .venv is broken; do not use)
+# CI and local runs use this file. Install:
+#     python3.11 -m venv .venv311 && source .venv311/bin/activate
+#     pip install -r requirements/ci.txt
+#     pip install -e ".[all]"        # optional: tinyfive / llvmlite / onnxruntime
+
+numpy>=1.26,<3
+onnx>=1.14,<2
+protobuf>=4.21
+pytest>=7
+
+# Optional (accelerators / independent verification): uncomment to use
+# onnxruntime
+# llvmlite

scratchv/standalone/spike_sim.py

@@ -12,7 +12,7 @@
   - Instruction trace samples
   - Spike execution time
 
-Spike binary:  /home/kinsomwang/workspace/coralnpu-spike-rv32/bin/spike
+Spike binary:  $SCRATCHV_SPIKE, else `spike` resolved on PATH (no hardcoded path)
 ScratchV binary: output.bin
 
 Usage:
@@ -25,6 +25,7 @@
 
 import argparse
 import os
+import shutil
 import struct
 import subprocess
 import sys
@@ -34,9 +35,16 @@
 from dataclasses import dataclass, field
 
 # ── Paths ──────────────────────────────────────────────────────────────────
-SPIKE = "/home/kinsomwang/workspace/coralnpu-spike-rv32/bin/spike"
-SPIKE_DASM = "/home/kinsomwang/workspace/coralnpu-spike-rv32/bin/spike-dasm"
-SPIKE_LOG_PARSER = "/home/kinsomwang/workspace/coralnpu-spike-rv32/bin/spike-log-parser"
+# Resolve Spike tools portably: explicit env override first, then PATH.
+# No hardcoded machine-specific paths.
+def _resolve_tool(name: str, env_var: str) -> str:
+    """Resolve a Spike tool path: env override → PATH lookup → bare name."""
+    return os.environ.get(env_var) or shutil.which(name) or name
+
+
+SPIKE = _resolve_tool("spike", "SCRATCHV_SPIKE")
+SPIKE_DASM = _resolve_tool("spike-dasm", "SCRATCHV_SPIKE_DASM")
+SPIKE_LOG_PARSER = _resolve_tool("spike-log-parser", "SCRATCHV_SPIKE_LOG_PARSER")
 
 # ── Constants ──────────────────────────────────────────────────────────────
 ELF_BASE = 0x80000000       # RISC-V DRAM base (Spike default)

tests/test_platform_asm.py

@@ -0,0 +1,113 @@
+"""--platform-asm output shape (platform contract; no RISC-V toolchain needed)."""
+
+import contextlib
+import io
+import tempfile
+
+import onnx
+from onnx import TensorProto, helper
+import pytest
+
+from scratchv.standalone.onnx_to_riscv_standalone import (
+    ONNXModel,
+    CNNRISCVGenerator,
+    MemoryPlan,
+    emit_platform_asm,
+)
+
+
+def _conv_model():
+    x = helper.make_tensor_value_info("x", TensorProto.FLOAT, [1, 3, 8, 8])
+    y = helper.make_tensor_value_info("y", TensorProto.FLOAT, [1, 8, 8, 8])
+    import numpy as np
+    rng = np.random.default_rng(0)
+    w = helper.make_tensor("w", TensorProto.FLOAT, [8, 3, 3, 3],
+                           rng.normal(0, 0.3, size=8 * 3 * 9).astype(np.float32).ravel().tolist())
+    node = helper.make_node("Conv", ["x", "w"], ["y"], pads=[1, 1, 1, 1])
+    graph = helper.make_graph([node], "c", [x], [y], [w])
+    return helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)])
+
+
+def _build_platform_asm(tmp_path):
+    path = tmp_path / "m.onnx"
+    onnx.save(_conv_model(), str(path))
+    model = ONNXModel.from_file(str(path))
+    mem = MemoryPlan()
+    for vi in model.inputs:
+        n = 1
+        for d in model.get_shape(vi.name):
+            n *= d
+        mem.alloc_workspace(vi.name, n)
+    weight_data = mem.layout_weights(model.initializers)
+    gen = CNNRISCVGenerator(model, mem)
+    with contextlib.redirect_stdout(io.StringIO()):
+        gen.generate()
+    return emit_platform_asm(gen, weight_data)
+
+
+def _fwht_model():
+    x = helper.make_tensor_value_info("X", TensorProto.FLOAT, [1, 64])
+    y = helper.make_tensor_value_info("Y", TensorProto.FLOAT, [1, 64])
+    node = helper.make_node("Fwht", ["X"], ["Y"], domain="org.scratchv")
+    graph = helper.make_graph([node], "fwht", [x], [y])
+    return helper.make_model(
+        graph,
+        opset_imports=[helper.make_opsetid("org.scratchv", 1),
+                       helper.make_opsetid("", 13)],
+    )
+
+
+def test_platform_asm_is_size_independent_for_fwht(tmp_path):
+    from scratchv.standalone.onnx_to_riscv_standalone import emit_platform_asm
+
+    path = tmp_path / "fwht.onnx"
+    onnx.save(_fwht_model(), str(path))
+    model = ONNXModel.from_file(str(path))
+    mem = MemoryPlan()
+    for vi in model.inputs:
+        n = 1
+        for d in model.get_shape(vi.name):
+            n *= d
+        mem.alloc_workspace(vi.name, n)
+    weight_data = mem.layout_weights(model.initializers)
+    gen = CNNRISCVGenerator(model, mem)
+    with contextlib.redirect_stdout(io.StringIO()):
+        gen.generate()
+
+    asm = emit_platform_asm(gen, weight_data, model)
+    assert ".globl cnn_entry" in asm
+    # runtime-sized: bounds come from a2, not a compile-time constant
+    assert "mv   t2, a2" in asm
+    assert "blt  t3, t2, _p_fwht_copy" in asm  # copy uses runtime N
+    # no hard-coded 64 anywhere as a loop bound
+    assert "li   t2, 64" not in asm
+
+
+def test_platform_asm_contract(tmp_path):
+    asm = _build_platform_asm(tmp_path)
+
+    # entry symbol is global cnn_entry, and old _start is gone
+    assert ".globl cnn_entry" in asm
+    assert "\ncnn_entry:" in asm
+    assert not any(l.strip() == "_start:" for l in asm.splitlines())
+
+    # no forbidden directives
+    assert ".incbin" not in asm
+    assert ".include" not in asm
+
+    # no unresolved placeholder / symbolic temp labels leak
+    assert "auipc gp, 0x0" not in asm
+    assert ".Lsv_" not in asm
+    assert "la gp, __data_start" in asm
+
+    # branch/jump targets use labels, not numeric offsets
+    import re
+    for line in asm.splitlines():
+        code = line.split("#", 1)[0]
+        if re.match(r"\s*(bne|beq|blt|bge|j|jal)\b", code):
+            assert not re.search(r",\s*-?\d+\s*$", code), f"numeric target: {line}"
+
+    # inline data section with .word, no incbin
+    assert "__data_start:" in asm
+    assert ".word" in asm
+    assert asm.count(".word") > 10