Text Generation
Transformers
Safetensors
MLX
code
llama
fill-in-the-middle
multi-token-prediction
speculative-decoding
apple-silicon
text-generation-inference
Instructions to use philipjohnbasile/wisp-coder-110m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philipjohnbasile/wisp-coder-110m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="philipjohnbasile/wisp-coder-110m")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("philipjohnbasile/wisp-coder-110m") model = AutoModelForCausalLM.from_pretrained("philipjohnbasile/wisp-coder-110m", device_map="auto") - MLX
How to use philipjohnbasile/wisp-coder-110m with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("philipjohnbasile/wisp-coder-110m") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- vLLM
How to use philipjohnbasile/wisp-coder-110m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "philipjohnbasile/wisp-coder-110m" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "philipjohnbasile/wisp-coder-110m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/philipjohnbasile/wisp-coder-110m
- SGLang
How to use philipjohnbasile/wisp-coder-110m with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "philipjohnbasile/wisp-coder-110m" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "philipjohnbasile/wisp-coder-110m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "philipjohnbasile/wisp-coder-110m" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "philipjohnbasile/wisp-coder-110m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - MLX LM
How to use philipjohnbasile/wisp-coder-110m with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "philipjohnbasile/wisp-coder-110m" --prompt "Once upon a time"
- Docker Model Runner
How to use philipjohnbasile/wisp-coder-110m with Docker Model Runner:
docker model run hf.co/philipjohnbasile/wisp-coder-110m
- Atomic Chat
File size: 37,513 Bytes
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The E2 arm must not reopen upstream datasets. Run 1 did not preserve an ordered
raw-row manifest, and its source loader used different parser dispatch from the
corrected loader. The strongest available input is therefore the exact token
stream already used by run 1. Literal control strings created observationally
ambiguous EOS boundaries, so the receipt records a deterministic grammar
recovery and its limits rather than claiming unobservable original boundaries.
This tool has two CPU-only commands:
python scripts/derive_no_fim.py attest \
--index data/shards/index.json \
--tokenizer tokenizer/code32k.json \
--out config/run1_shard_integrity_receipt.json
python scripts/derive_no_fim.py build \
--config config/run2_no_fim.json
"""
import argparse
from datetime import datetime, timezone
import hashlib
import json
import os
import struct
import sys
import numpy as np
from tokenizers import Tokenizer
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from data import canonical_json_sha256, file_sha256, stable_file_sha256
from scripts.hf_metadata import write_json_atomic
from scripts.prepare_data import require_fresh_output_dir
ALGORITHM = "run1_deterministic_no_fim_normalization_v1"
INDEX_SCHEMA_VERSION = 3
RECEIPT_SCHEMA_VERSION = 1
DEFAULT_CHUNK_BYTES = 8 * 1024 * 1024
SHARD_TOKENS = 100_000_000
KIND_CODES = {"l2r": 0, "fim_psm": 1, "fim_spm": 2}
UNIT_RECORD_DTYPE = np.dtype(
[
("length", "<u4"),
("kind", "u1"),
("reserved", "u1", (3,)),
]
)
def load_json(path):
with open(path, encoding="utf-8") as f:
value = json.load(f)
if not isinstance(value, dict):
raise ValueError(f"{path}: top-level JSON must be an object")
return value
def special_token_ids(tokenizer_path):
tokenizer = Tokenizer.from_file(tokenizer_path)
names = {
"eos": "<|endoftext|>",
"prefix": "<|fim_prefix|>",
"middle": "<|fim_middle|>",
"suffix": "<|fim_suffix|>",
}
values = {key: tokenizer.token_to_id(value) for key, value in names.items()}
if any(value is None for value in values.values()):
raise ValueError("tokenizer is missing an EOS or FIM special token")
if len(set(values.values())) != len(values):
raise ValueError("EOS and FIM special-token ids must be distinct")
return values, tokenizer.get_vocab_size()
def _as_uint16_le(ids):
value = np.asarray(ids, dtype="<u2")
if value.ndim != 1:
raise ValueError("token unit must be one-dimensional")
return value
def fim_scan_state(ids, special_ids):
"""Classify a segment as L2R, complete FIM, or visibly incomplete FIM."""
ids = _as_uint16_le(ids)
prefix_id = special_ids["prefix"]
middle_id = special_ids["middle"]
suffix_id = special_ids["suffix"]
positions = {
"prefix": np.flatnonzero(ids == prefix_id),
"middle": np.flatnonzero(ids == middle_id),
"suffix": np.flatnonzero(ids == suffix_id),
}
counts = {key: int(value.size) for key, value in positions.items()}
if counts == {"prefix": 0, "middle": 0, "suffix": 0}:
return "l2r"
if any(value > 1 for value in counts.values()):
raise ValueError(f"malformed FIM sentinel counts: {counts}")
if counts["prefix"] != 1:
raise ValueError("FIM sentinel fragment has no prefix sentinel")
prefix = int(positions["prefix"][0])
if prefix != 0:
raise ValueError("malformed FIM unit does not begin with prefix sentinel")
if counts["suffix"] == 0:
if counts["middle"]:
raise ValueError("FIM middle sentinel appears before suffix sentinel")
return "incomplete"
suffix = int(positions["suffix"][0])
if suffix == 1:
if counts["middle"] == 0:
return "incomplete"
middle = int(positions["middle"][0])
if middle <= suffix:
raise ValueError("SPM middle sentinel precedes its suffix payload")
if middle < 4 or ids.size - middle - 1 < 2:
return "incomplete"
return "complete"
if suffix < 2:
raise ValueError("malformed PSM unit has an empty prefix")
if counts["middle"] == 0:
return "incomplete"
middle = int(positions["middle"][0])
if middle <= suffix:
raise ValueError("PSM middle sentinel precedes its suffix payload")
if middle < suffix + 3 or middle >= ids.size - 1:
return "incomplete"
return "complete"
def decode_fim_unit(ids, special_ids):
"""Return `(kind, raw_ids)` for one complete recovered run 1 unit."""
ids = _as_uint16_le(ids)
state = fim_scan_state(ids, special_ids)
if state == "l2r":
return "l2r", ids
if state == "incomplete":
raise ValueError("incomplete FIM unit")
prefix_id = special_ids["prefix"]
middle_id = special_ids["middle"]
suffix_id = special_ids["suffix"]
prefix = int(np.flatnonzero(ids == prefix_id)[0])
middle = int(np.flatnonzero(ids == middle_id)[0])
suffix = int(np.flatnonzero(ids == suffix_id)[0])
if prefix != 0:
raise AssertionError("complete FIM unit lost its prefix position")
if suffix == 1:
raw = _as_uint16_le(
np.concatenate((ids[middle + 1:], ids[2:middle]))
)
if any(
np.any(raw == special_ids[key])
for key in ("prefix", "middle", "suffix")
):
raise ValueError("decoded SPM raw unit retains a FIM sentinel")
if not 16 <= raw.size <= 1024:
raise ValueError("decoded SPM raw length is outside 16 to 1024")
return "fim_spm", raw
raw = _as_uint16_le(
np.concatenate(
(
ids[1:suffix],
ids[middle + 1:],
ids[suffix + 1:middle],
)
)
)
if any(
np.any(raw == special_ids[key])
for key in ("prefix", "middle", "suffix")
):
raise ValueError("decoded PSM raw unit retains a FIM sentinel")
if not 16 <= raw.size <= 1024:
raise ValueError("decoded PSM raw length is outside 16 to 1024")
return "fim_psm", raw
class UnitEvidence:
"""Streaming hashes and counts for recovered ordered raw units."""
def __init__(self, eos_token_id, domain="unspecified"):
self.eos_token_id = eos_token_id
self.domain = domain.encode("utf-8")
self.ordered = hashlib.sha256()
self.destination = hashlib.sha256()
self.source_wire = hashlib.sha256()
for digest, label in (
(self.ordered, b"RECOVERED_RAW"),
(self.destination, b"DESTINATION"),
(self.source_wire, b"SOURCE_WIRE"),
):
digest.update(b"WISP_NO_FIM_V1\0" + label + b"\0")
digest.update(struct.pack("<Q", len(self.domain)))
digest.update(self.domain)
self.units = 0
self.source_tokens = 0
self.derived_tokens = 0
self.raw_tokens = 0
self.empty_units = 0
self.internal_eos_tokens = 0
self.counts = {"l2r": 0, "fim_psm": 0, "fim_spm": 0}
self._eos_bytes = np.asarray([eos_token_id], dtype="<u2").tobytes()
self._source_wire_complete = True
def add(
self,
source_ids,
kind,
raw,
internal_eos_tokens=0,
):
raw = _as_uint16_le(raw)
if kind not in KIND_CODES:
raise ValueError(f"unknown recovered unit kind: {kind}")
if kind == "l2r":
if not 1 <= raw.size <= 1024:
raise ValueError("plain recovered raw length is outside 1 to 1024")
elif not 16 <= raw.size <= 1024:
raise ValueError("FIM recovered raw length is outside 16 to 1024")
raw_bytes = raw.tobytes()
ordinal = self.units
kind_code = KIND_CODES[kind]
self.ordered.update(
b"U"
+ struct.pack("<QBQ", ordinal, kind_code, int(raw.size))
)
self.ordered.update(raw_bytes)
destination_bytes = raw_bytes + self._eos_bytes
self.destination.update(
b"U"
+ struct.pack(
"<QBQ",
ordinal,
kind_code,
int(raw.size) + 1,
)
)
self.destination.update(destination_bytes)
if source_ids is None:
source_length = int(raw.size) + (3 if kind != "l2r" else 0)
self._source_wire_complete = False
else:
source_ids = _as_uint16_le(source_ids)
source_length = int(source_ids.size)
self.source_wire.update(
b"U"
+ struct.pack(
"<QBQ",
ordinal,
kind_code,
source_length + 1,
)
)
self.source_wire.update(source_ids.tobytes())
self.source_wire.update(self._eos_bytes)
self.units += 1
self.source_tokens += int(source_length) + 1
self.raw_tokens += int(raw.size)
self.derived_tokens += int(raw.size) + 1
self.empty_units += int(raw.size == 0)
self.internal_eos_tokens += int(internal_eos_tokens)
self.counts[kind] += 1
def summary(self):
removed = self.source_tokens - self.derived_tokens
fim_units = self.counts["fim_psm"] + self.counts["fim_spm"]
if removed != 3 * fim_units:
raise RuntimeError(
"recovered stream did not remove exactly three tokens per "
"FIM unit"
)
footer = b"END" + struct.pack(
"<QQQQQQ",
self.units,
self.source_tokens,
self.raw_tokens,
self.derived_tokens,
self.counts["l2r"],
fim_units,
)
ordered = self.ordered.copy()
ordered.update(footer)
destination = self.destination.copy()
destination.update(footer)
source_wire = self.source_wire.copy()
source_wire.update(footer)
result = {
"units": self.units,
"source_tokens": self.source_tokens,
"raw_tokens": self.raw_tokens,
"derived_tokens": self.derived_tokens,
"removed_fim_tokens": removed,
"empty_eos_segments": self.empty_units,
"reassembled_internal_eos_tokens": self.internal_eos_tokens,
"l2r_units": self.counts["l2r"],
"fim_psm_units": self.counts["fim_psm"],
"fim_spm_units": self.counts["fim_spm"],
"ordered_raw_units_sha256": ordered.hexdigest(),
"destination_units_sha256": destination.hexdigest(),
}
if self._source_wire_complete:
result["source_wire_units_sha256"] = source_wire.hexdigest()
return result
def _same_summary(left, right):
return canonical_json_sha256(left) == canonical_json_sha256(right)
def _normalization_evidence(value):
keys = (
"units",
"source_tokens",
"raw_tokens",
"derived_tokens",
"removed_fim_tokens",
"l2r_units",
"fim_psm_units",
"fim_spm_units",
"ordered_raw_units_sha256",
"destination_units_sha256",
)
return {key: value.get(key) for key in keys}
def scan_shard(
path,
special_ids,
expected_tokens=None,
emit=None,
split_evidence=None,
evidence_domain="shard:unspecified",
vocab_size=None,
chunk_bytes=DEFAULT_CHUNK_BYTES,
):
"""Scan one shard once, hashing bytes and decoding every EOS segment."""
if chunk_bytes < 2 or chunk_bytes % 2:
raise ValueError("scan chunk size must be a positive even byte count")
if os.path.islink(path):
raise ValueError(f"{path}: shard cannot be a symbolic link")
if not os.path.isfile(path):
raise FileNotFoundError(path)
before = os.stat(path, follow_symlinks=False)
size = before.st_size
if size % 2:
raise ValueError(f"{path}: uint16 shard has an odd byte length")
tokens = size // 2
if expected_tokens is not None and tokens != expected_tokens:
raise ValueError(
f"{path}: {tokens} tokens != declared {expected_tokens}"
)
local = UnitEvidence(special_ids["eos"], evidence_domain)
split_evidence = split_evidence or UnitEvidence(
special_ids["eos"],
"split:unspecified",
)
shard_digest = hashlib.sha256()
carry = np.empty(0, dtype="<u2")
pending = None
pending_internal_eos = 0
pending_start_segment = None
pending_start_token = None
eos_segment_ordinal = 0
reassembly_groups = []
token_offset = 0
unit_ordinal = 0
with open(path, "rb") as f:
while True:
block = f.read(chunk_bytes)
if not block:
break
shard_digest.update(block)
if len(block) % 2:
raise ValueError(f"{path}: partial uint16 token in scan chunk")
current = np.frombuffer(block, dtype="<u2")
if (
vocab_size is not None
and current.size
and int(current.max()) >= vocab_size
):
raise ValueError(f"{path}: token id is outside tokenizer vocab")
if carry.size:
current = np.concatenate((carry, current))
starts_at = token_offset - int(carry.size)
boundaries = np.flatnonzero(current == special_ids["eos"])
start = 0
for boundary_value in boundaries:
boundary = int(boundary_value)
segment = current[start:boundary]
if pending is not None:
segment = np.concatenate((pending, segment))
try:
state = fim_scan_state(segment, special_ids)
except ValueError as exc:
absolute = starts_at + start
raise ValueError(
f"{path}: malformed unit {unit_ordinal} at token "
f"{absolute}: {exc}"
) from exc
if state == "incomplete":
if segment.size >= 1027:
raise ValueError(
f"{path}: incomplete FIM unit {unit_ordinal} "
"exceeds the maximum framed length"
)
pending = np.concatenate(
(
segment,
np.asarray(
[special_ids["eos"]],
dtype="<u2",
),
)
)
if pending_start_segment is None:
pending_start_segment = eos_segment_ordinal
pending_start_token = starts_at + start
pending_internal_eos += 1
start = boundary + 1
eos_segment_ordinal += 1
continue
kind, raw = decode_fim_unit(segment, special_ids)
local.add(
segment,
kind,
raw,
internal_eos_tokens=pending_internal_eos,
)
split_evidence.add(
segment,
kind,
raw,
internal_eos_tokens=pending_internal_eos,
)
if emit is not None:
emit(raw, special_ids["eos"], kind)
if pending_internal_eos:
reassembly_groups.append(
{
"unit_ordinal": unit_ordinal,
"first_eos_segment": pending_start_segment,
"last_eos_segment": eos_segment_ordinal,
"internal_eos_tokens": pending_internal_eos,
"source_token_start": pending_start_token,
"writer_eos_token": starts_at + boundary,
}
)
unit_ordinal += 1
pending = None
pending_internal_eos = 0
pending_start_segment = None
pending_start_token = None
start = boundary + 1
eos_segment_ordinal += 1
carry = current[start:].copy()
if carry.size > 1027:
raise ValueError(
f"{path}: unterminated unit exceeds maximum wire length"
)
token_offset += len(block) // 2
if pending is not None:
raise ValueError(f"{path}: incomplete FIM unit at shard boundary")
if carry.size:
raise ValueError(
f"{path}: shard does not end at an EOS-delimited unit boundary"
)
after = os.stat(path, follow_symlinks=False)
if (
before.st_dev,
before.st_ino,
before.st_size,
before.st_mtime_ns,
) != (
after.st_dev,
after.st_ino,
after.st_size,
after.st_mtime_ns,
):
raise RuntimeError(f"{path}: shard changed during integrity scan")
summary = local.summary()
return {
"bytes": size,
"tokens": tokens,
"sha256": shard_digest.hexdigest(),
"reassembly_groups": reassembly_groups,
**summary,
}
def scan_index(index_path, tokenizer_path):
index = load_json(index_path)
special_ids, vocab_size = special_token_ids(tokenizer_path)
tokenizer_sha256 = file_sha256(tokenizer_path)
if index.get("vocab_size") != vocab_size:
raise ValueError("source index vocab size differs from tokenizer")
root = os.path.dirname(os.path.abspath(index_path))
split_receipts = {}
for split in ("train", "val"):
entries = index.get("splits", {}).get(split)
if not isinstance(entries, list) or not entries:
raise ValueError(f"source index split {split} is empty")
paths = [entry.get("path") for entry in entries]
if len(set(paths)) != len(paths):
raise ValueError(f"source index split {split} repeats a shard path")
split_evidence = UnitEvidence(
special_ids["eos"],
f"split:{split}:tokenizer:{tokenizer_sha256}",
)
shard_receipts = []
for entry in entries:
relative = entry.get("path")
if (
not isinstance(relative, str)
or not relative
or os.path.isabs(relative)
or os.path.normpath(relative) != relative
or relative == ".."
or relative.startswith(".." + os.sep)
):
raise ValueError(
f"source index split {split} has unsafe shard path"
)
path = os.path.join(root, relative)
shard = scan_shard(
path,
special_ids,
expected_tokens=entry.get("tokens"),
split_evidence=split_evidence,
evidence_domain=(
f"shard:{split}:{relative}:tokenizer:{tokenizer_sha256}"
),
vocab_size=vocab_size,
)
shard_receipts.append({"path": relative, **shard})
summary = split_evidence.summary()
declared_total = entries[0].get("total_tokens")
if summary["source_tokens"] != declared_total:
raise ValueError(
f"source split {split} scan total differs from index"
)
split_receipts[split] = {
**summary,
"shards": shard_receipts,
"shard_manifest_sha256": canonical_json_sha256(
[
{
key: shard[key]
for key in ("path", "tokens", "bytes", "sha256")
}
for shard in shard_receipts
]
),
}
return index, special_ids, split_receipts
def build_attestation(index_path, tokenizer_path):
index, special_ids, splits = scan_index(index_path, tokenizer_path)
reassembly_groups = sum(
len(shard["reassembly_groups"])
for shard in splits["train"]["shards"]
+ splits["val"]["shards"]
)
restored_internal_eos = sum(
split["reassembled_internal_eos_tokens"]
for split in splits.values()
)
return {
"schema_version": RECEIPT_SCHEMA_VERSION,
"created_at": datetime.now(timezone.utc).isoformat(),
"status": "complete",
"algorithm": ALGORITHM,
"dtype": "uint16_le",
"source_index": {
"path": index_path,
"sha256": file_sha256(index_path),
"schema_version": index.get("schema_version", 1),
},
"tokenizer": {
"path": tokenizer_path,
"sha256": file_sha256(tokenizer_path),
"vocab_size": index["vocab_size"],
},
"special_token_ids": special_ids,
"attestation_script": {
"path": os.path.relpath(
os.path.abspath(__file__),
os.getcwd(),
),
"sha256": file_sha256(__file__),
},
"boundary_recovery": {
"exact_original_units_proven": False,
"mode": "deterministic_visible_grammar_normalization",
"rule": (
"Start only at a partial prefix-bearing EOS segment, append "
"following same-shard segments, restore each intervening EOS "
"as payload, and stop at the first complete valid FIM grammar."
),
"detectable_reassembly_groups": reassembly_groups,
"restored_internal_eos_tokens": restored_internal_eos,
"cross_shard_reassembly_allowed": False,
},
"splits": splits,
"limitations": [
(
"Literal EOS tokens in L2R content and after the final FIM "
"marker can be observationally indistinguishable from writer "
"boundaries."
),
(
"A raw untransformed segment that exactly mimics one valid FIM "
"frame is structurally indistinguishable from a generated frame."
),
(
"This post-build receipt binds current token bytes and visible "
"grammar, not raw source rows, build-time shard hashes, or exact "
"original unit boundaries."
),
],
}
class DerivedShardWriter:
"""Write one destination shard plus a fixed-width unit-boundary sidecar."""
def __init__(self, out_dir, split, name):
self.out_dir = out_dir
self.split = split
self.name = name
self.buf = []
self.records = []
self.total = 0
def add_raw(self, raw, eos_token_id, kind):
raw = _as_uint16_le(raw)
unit = np.empty(raw.size + 1, dtype="<u2")
unit[:-1] = raw
unit[-1] = eos_token_id
self.buf.append(unit)
self.records.append((int(unit.size), KIND_CODES[kind]))
self.total += int(unit.size)
def flush(self):
if not self.buf:
raise ValueError(f"derived shard {self.name} has no units")
values = np.concatenate(self.buf).astype("<u2", copy=False)
path = os.path.join(self.out_dir, self.name)
if os.path.lexists(path):
raise FileExistsError(f"refusing to replace derived shard: {path}")
digest = hashlib.sha256()
digest.update(memoryview(values).cast("B"))
with open(path, "xb") as f:
values.tofile(f)
f.flush()
os.fsync(f.fileno())
sidecar_name = self.name + ".units.bin"
sidecar_path = os.path.join(self.out_dir, sidecar_name)
if os.path.lexists(sidecar_path):
raise FileExistsError(
f"refusing to replace unit sidecar: {sidecar_path}"
)
records = np.zeros(len(self.records), dtype=UNIT_RECORD_DTYPE)
records["length"] = [value[0] for value in self.records]
records["kind"] = [value[1] for value in self.records]
sidecar_digest = hashlib.sha256()
sidecar_digest.update(memoryview(records).cast("B"))
with open(sidecar_path, "xb") as f:
records.tofile(f)
f.flush()
os.fsync(f.fileno())
entry = {
"path": self.name,
"tokens": int(values.size),
"bytes": int(values.nbytes),
"sha256": digest.hexdigest(),
"unit_sidecar": {
"path": sidecar_name,
"records": int(records.size),
"bytes": int(records.nbytes),
"sha256": sidecar_digest.hexdigest(),
"record_format": "uint32_length_uint8_kind_3_zero_bytes",
},
}
self.buf = []
self.records = []
return entry
def verify_derived_shard(
out_dir,
split,
entry,
special_ids,
tokenizer_sha256,
split_evidence=None,
):
"""Independently reread one destination shard and its unit sidecar."""
path = os.path.join(out_dir, entry["path"])
sidecar = entry["unit_sidecar"]
sidecar_path = os.path.join(out_dir, sidecar["path"])
if stable_file_sha256(path) != entry["sha256"]:
raise ValueError(f"derived shard hash differs: {entry['path']}")
if stable_file_sha256(sidecar_path) != sidecar["sha256"]:
raise ValueError(
f"derived unit-sidecar hash differs: {sidecar['path']}"
)
values = np.memmap(path, dtype="<u2", mode="r")
records = np.memmap(
sidecar_path,
dtype=UNIT_RECORD_DTYPE,
mode="r",
)
if values.size != entry["tokens"] or values.nbytes != entry["bytes"]:
raise ValueError(f"derived shard size differs: {entry['path']}")
if (
records.size != sidecar["records"]
or records.nbytes != sidecar["bytes"]
or np.any(records["reserved"] != 0)
):
raise ValueError(
f"derived unit-sidecar structure differs: {sidecar['path']}"
)
if int(records["length"].sum(dtype=np.uint64)) != int(values.size):
raise ValueError(
f"derived unit-sidecar lengths differ: {sidecar['path']}"
)
if np.any(records["kind"] > max(KIND_CODES.values())):
raise ValueError(
f"derived unit-sidecar kind differs: {sidecar['path']}"
)
for key in ("prefix", "middle", "suffix"):
if np.any(values == special_ids[key]):
raise ValueError(
f"derived shard retains FIM sentinel: {entry['path']}"
)
domain = (
f"shard:{split}:{entry['path']}:tokenizer:{tokenizer_sha256}"
)
evidence = UnitEvidence(special_ids["eos"], domain)
split_evidence = split_evidence or UnitEvidence(
special_ids["eos"],
f"split:{split}:tokenizer:{tokenizer_sha256}",
)
kinds = {value: key for key, value in KIND_CODES.items()}
offset = 0
for record in records:
length = int(record["length"])
end = offset + length
if length < 2 or end > values.size:
raise ValueError(
f"derived unit-sidecar boundary differs: {sidecar['path']}"
)
unit = np.asarray(values[offset:end])
if int(unit[-1]) != special_ids["eos"]:
raise ValueError(
f"derived unit lacks writer EOS: {sidecar['path']}"
)
kind = kinds[int(record["kind"])]
raw = unit[:-1]
evidence.add(None, kind, raw)
split_evidence.add(None, kind, raw)
offset = end
if offset != values.size:
raise ValueError(
f"derived unit-sidecar does not cover shard: {sidecar['path']}"
)
return evidence.summary()
def validate_derivation_contract(config, receipt):
contract = config.get("data_build_contract")
expected = {
"schema_version": 2,
"strategy": ALGORITHM,
"source_index": receipt["source_index"],
"source_integrity_receipt": config.get("data_integrity", {}).get(
"receipt"
),
"source_integrity_receipt_sha256": config.get(
"data_integrity", {}
).get("sha256"),
"require_fresh_output_dir": True,
}
if contract != expected:
raise ValueError(
"no-FIM derivation request differs from config contract:\n"
f"expected {contract!r}\n"
f"actual {expected!r}"
)
if config.get("fim_rate") != 0.0:
raise ValueError("no-FIM derivation config fim_rate must be 0.0")
if "sources" in config:
raise ValueError(
"no-FIM derivation config must not contain executable sources"
)
return contract
def build_no_fim(config_path):
config = load_json(config_path)
integrity = config.get("data_integrity", {})
if integrity.get("role") != "source":
raise ValueError("run 2 data_integrity role must be source")
receipt_path = integrity.get("receipt")
receipt = load_json(receipt_path)
if file_sha256(receipt_path) != integrity.get("sha256"):
raise ValueError("run 1 source integrity receipt hash differs")
if receipt.get("status") != "complete" or receipt.get(
"algorithm"
) != ALGORITHM:
raise ValueError("run 1 source integrity receipt is incomplete")
contract = validate_derivation_contract(config, receipt)
tokenizer_path = config["tokenizer_path"]
special_ids, vocab_size = special_token_ids(tokenizer_path)
if receipt.get("special_token_ids") != special_ids:
raise ValueError("source receipt special-token ids differ")
if receipt.get("tokenizer", {}).get("sha256") != file_sha256(
tokenizer_path
):
raise ValueError("source receipt tokenizer differs")
out_dir = require_fresh_output_dir(config["data_dir"])
os.makedirs(out_dir, exist_ok=True)
source_index_path = receipt["source_index"]["path"]
if file_sha256(source_index_path) != receipt["source_index"]["sha256"]:
raise ValueError("run 1 source index hash differs")
source_index = load_json(source_index_path)
source_root = os.path.dirname(os.path.abspath(source_index_path))
tokenizer_sha256 = file_sha256(tokenizer_path)
output_splits = {}
split_evidence_out = {}
for split in ("train", "val"):
split_evidence = UnitEvidence(
special_ids["eos"],
f"split:{split}:tokenizer:{tokenizer_sha256}",
)
verified_split_evidence = UnitEvidence(
special_ids["eos"],
f"split:{split}:tokenizer:{tokenizer_sha256}",
)
expected_split = receipt["splits"][split]
source_entries = source_index["splits"][split]
if [entry["path"] for entry in source_entries] != [
entry["path"] for entry in expected_split["shards"]
]:
raise ValueError(f"run 1 split {split} shard order differs")
output_entries = []
for source_entry, expected_shard in zip(
source_entries,
expected_split["shards"],
):
path = os.path.join(source_root, source_entry["path"])
writer = DerivedShardWriter(
out_dir,
split,
source_entry["path"],
)
actual_shard = {
"path": source_entry["path"],
**scan_shard(
path,
special_ids,
expected_tokens=source_entry["tokens"],
emit=writer.add_raw,
split_evidence=split_evidence,
evidence_domain=(
f"shard:{split}:{source_entry['path']}:"
f"tokenizer:{tokenizer_sha256}"
),
vocab_size=vocab_size,
),
}
if not _same_summary(actual_shard, expected_shard):
raise ValueError(
f"run 1 source shard changed: {source_entry['path']}"
)
output_entry = writer.flush()
verified = verify_derived_shard(
out_dir,
split,
output_entry,
special_ids,
tokenizer_sha256,
split_evidence=verified_split_evidence,
)
if _normalization_evidence(verified) != (
_normalization_evidence(actual_shard)
):
raise ValueError(
f"derived shard evidence differs: "
f"{source_entry['path']}"
)
output_entry["source"] = {
"path": source_entry["path"],
"tokens": actual_shard["tokens"],
"sha256": actual_shard["sha256"],
"source_wire_units_sha256": actual_shard[
"source_wire_units_sha256"
],
"ordered_raw_units_sha256": actual_shard[
"ordered_raw_units_sha256"
],
}
output_entry["normalization"] = _normalization_evidence(
verified
)
output_entries.append(output_entry)
actual_split = split_evidence.summary()
verified_split = verified_split_evidence.summary()
expected_summary = {
key: value
for key, value in expected_split.items()
if key not in ("shards", "shard_manifest_sha256")
}
if not _same_summary(actual_split, expected_summary):
raise ValueError(f"run 1 split {split} evidence changed")
if _normalization_evidence(verified_split) != (
_normalization_evidence(actual_split)
):
raise ValueError(
f"independent derived split {split} evidence differs"
)
output_total = sum(entry["tokens"] for entry in output_entries)
if output_total != actual_split["derived_tokens"]:
raise ValueError(f"derived split {split} token total differs")
for entry in output_entries:
entry["total_tokens"] = output_total
output_splits[split] = output_entries
split_evidence_out[split] = actual_split
index = {
"schema_version": INDEX_SCHEMA_VERSION,
"vocab_size": vocab_size,
"fim_rate": 0.0,
"fim_chunk": config["fim_chunk"],
"splits": output_splits,
"build": {
"completed": True,
"strategy": ALGORITHM,
"fresh_output_directory": True,
"config_path": config_path,
"config_canonical_sha256": canonical_json_sha256(config),
"tokenizer_path": tokenizer_path,
"tokenizer_sha256": file_sha256(tokenizer_path),
"source_index": receipt["source_index"],
"source_integrity_receipt": {
"path": receipt_path,
"sha256": integrity["sha256"],
},
"special_token_ids": special_ids,
"derivation_script": {
"path": os.path.relpath(
os.path.abspath(__file__),
os.getcwd(),
),
"sha256": file_sha256(__file__),
},
"split_evidence": split_evidence_out,
"contract": contract,
},
}
if (
file_sha256(receipt_path) != integrity["sha256"]
or file_sha256(source_index_path)
!= receipt["source_index"]["sha256"]
or file_sha256(tokenizer_path) != tokenizer_sha256
):
raise RuntimeError("no-FIM derivation input changed before publication")
index_path = os.path.join(out_dir, "index.json")
write_json_atomic(index_path, index)
return index_path, index
def main():
parser = argparse.ArgumentParser()
subparsers = parser.add_subparsers(dest="command", required=True)
attest = subparsers.add_parser("attest")
attest.add_argument("--index", required=True)
attest.add_argument("--tokenizer", required=True)
attest.add_argument("--out", required=True)
build = subparsers.add_parser("build")
build.add_argument("--config", required=True)
cli = parser.parse_args()
if cli.command == "attest":
if os.path.lexists(cli.out):
raise FileExistsError(
f"refusing to replace integrity receipt: {cli.out}"
)
receipt = build_attestation(cli.index, cli.tokenizer)
write_json_atomic(cli.out, receipt)
print(
f"wrote {cli.out}: "
f"{receipt['splits']['train']['source_tokens']:,} train source "
"tokens"
)
return
index_path, index = build_no_fim(cli.config)
print(
f"wrote {index_path}: "
f"{index['splits']['train'][0]['total_tokens']:,} train / "
f"{index['splits']['val'][0]['total_tokens']:,} val tokens"
)
if __name__ == "__main__":
main()
|