1

2026-08-26 18:16:00 +08:00
parent a4568d8a55
commit 0ddc556a3f
1 changed files with 0 additions and 94 deletions
@@ -1,94 +0,0 @@
-#!/usr/bin/env python3
-"""纯标准库解析 TFLite flatbuffer,打印 subgraph[0] 输入/输出张量的形状与类型。
-
-schema 依据 tensorflow/lite/schema/schema.fbs(字段顺序敏感)。
-"""
-import struct
-import sys
-
-TENSOR_TYPE = {0: "FLOAT32", 1: "FLOAT16", 2: "INT32", 3: "UINT8", 4: "INT64",
-               5: "STRING", 6: "BOOL", 7: "INT16", 8: "COMPLEX64", 9: "INT8",
-               10: "FLOAT64", 11: "COMPLEX128", 12: "UINT64", 13: "RESOURCE",
-               14: "VARIANT", 15: "UINT32", 16: "UINT16", 17: "INT4",
-               18: "BFLOAT16", 19: "FLOAT8_E4M3FN", 20: "FLOAT8_E4M3FNUZ",
-               21: "FLOAT8_E5M2", 22: "FLOAT8_E5M2FNUZ"}
-
-
-class FB:
-    def __init__(self, data):
-        self.d = data
-
-    def u32(self, pos):
-        return struct.unpack_from("<I", self.d, pos)[0]
-
-    def i32(self, pos):
-        return struct.unpack_from("<i", self.d, pos)[0]
-
-    def u16(self, pos):
-        return struct.unpack_from("<H", self.d, pos)[0]
-
-    def field(self, table_pos, idx):
-        """返回字段值的位置;table/string/vector 字段此处是 uoffset 所在位置"""
-        vto = self.i32(table_pos)
-        vtable = table_pos - vto
-        vsize = self.u16(vtable)
-        off = vtable + 4 + 2 * idx
-        if off + 2 > vtable + vsize:
-            return None
-        foff = self.u16(off)
-        return None if foff == 0 else table_pos + foff
-
-    def deref(self, pos):
-        """uoffset 字段解引用:目标 = uoffset 所在位置 + 其值"""
-        return pos + self.u32(pos) if pos is not None else None
-
-    def vec(self, pos):
-        pos = self.deref(pos)
-        if pos is None:
-            return None
-        n = self.u32(pos)
-        return pos + 4, n
-
-    def vec_table(self, pos):
-        """返回 [table_pos...],每个元素是相对自身位置的 uoffset"""
-        start, n = self.vec(pos)
-        return [start + i * 4 + self.u32(start + i * 4) for i in range(n)]
-
-    def string(self, pos):
-        pos = self.deref(pos)
-        if pos is None:
-            return None
-        n = self.u32(pos)
-        return self.d[pos + 4:pos + 4 + n].decode("utf-8", "replace")
-
-    def int_vec(self, pos):
-        start, n = self.vec(pos)
-        return [self.i32(start + 4 * i) for i in range(n)]
-
-
-def main(path):
-    fb = FB(open(path, "rb").read())
-    root = fb.u32(0)                       # Model 表
-    subgraphs = fb.vec_table(fb.field(root, 2))   # Model.subgraphs [2]
-    sg = subgraphs[0]
-    tensors = fb.vec_table(fb.field(sg, 0))       # SubGraph.tensors [0]
-    inputs = fb.int_vec(fb.field(sg, 1))          # SubGraph.inputs [1]
-    outputs = fb.int_vec(fb.field(sg, 2))         # SubGraph.outputs [2]
-
-    def describe(i):
-        t = tensors[i]
-        shape = fb.int_vec(fb.field(t, 0))
-        ttype = fb.u8(fb.field(t, 1)) if fb.field(t, 1) else 0
-        name = fb.string(fb.field(t, 3)) or "?"
-        return f"{name} shape={shape} type={TENSOR_TYPE.get(ttype, ttype)}"
-
-    print("inputs:")
-    for i in inputs:
-        print(" ", describe(i))
-    print("outputs:")
-    for i in outputs:
-        print(" ", describe(i))
-
-
-if __name__ == "__main__":
-    main(sys.argv[1])