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e5cf7c3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 | import os
import requests
import sys
import base64
token = os.environ.get("HF_TOKEN")
namespace = "GAInTech"
space_id = "GAInTech/feather-a10g-gt80k-runtime-public"
hotpatch_script = """
import os
import sys
from pathlib import Path
def patch(path, old, new):
p = Path(path)
if not p.exists(): return
s = p.read_text()
if old in s:
p.write_text(s.replace(old, new))
print(f'[hotpatch] patched {path}')
else:
print(f'[hotpatch] FAILED to find string in {path}')
# 1. training.py: Comprehensive fix
p1 = Path('/workspace/feather/hydra/training.py')
if p1.exists():
s = p1.read_text()
# Correcting MDLM logic
s = s.replace('mdlm_mask_id = MDLM_MASK_ID if MDLM_MASK_ID >= 0 else (vocab_size - 1)',
'_m = int(os.environ.get("HYDRA_MDLM_MASK_ID", "-1"))\\n mdlm_mask_id = _m if _m >= 0 else (vocab_size - 1)')
# Fix maybe_resume_ckpt logic
s = s.replace('if not RESUME_CKPT or RESUME_CKPT.lower() == "none":',
'_r = os.environ.get("HYDRA_RESUME_CKPT", "none")\\n if not _r or _r.lower() == "none":')
s = s.replace('resume_path = Path(os.path.expanduser(RESUME_CKPT))',
'resume_path = Path(os.path.expanduser(os.environ.get("HYDRA_RESUME_CKPT", "none")))')
# Fix _prof NameError: use a fuzzy match for the main function start
for m_line in ['def main():', 'def main() -> None:']:
if m_line in s:
s = s.replace(m_line, m_line + '\\n _prof = False')
break
p1.write_text(s)
print('[hotpatch] training.py supreme fix v8')
# 2. htm.py: Stub
p_htm = Path('/workspace/feather/subsystems/htm.py')
if p_htm.exists():
s = p_htm.read_text()
if 'class _StubRegion' not in s:
stub = "\\nclass _StubRegion:\\n def __init__(self, *a, **k): self.n_columns=2048\\n def step(self, *a, **k): import numpy as np; return (np.zeros(2048), None, None, 1.0)\\n def step_many(self, sdr, *a): import numpy as np; T=sdr.shape[0]; return (np.zeros((T,2048)), np.ones(T, dtype=np.float32))\\n def reset(self): pass\\n"
s = s.replace('import htm_rust', 'import htm_rust' + stub)
s = s.replace('_HTM_REGION_CLS = getattr(htm_rust, "HTMRegion", None)', '_HTM_REGION_CLS = _StubRegion')
p_htm.write_text(s)
print('[hotpatch] patched htm.py stub')
# 3. stream fix
patch('/workspace/feather/prepare_nemotron.py',
'local_only = os.environ.get("HYDRA_LOCAL_SHARDS_ONLY", "1") == "1"',
'local_only = False')
# 4. sdr_semantic.py fix
p_sem = Path('/workspace/feather/subsystems/sdr_semantic.py')
if p_sem.exists():
s = p_sem.read_text()
# Fix signature (Fuzzy)
s = s.replace('contrastive_rank: int = 64,\\n ) -> None:',
'contrastive_rank: int = 64, hebbian_alpha: float = 0.01, learnable: bool | None = None) -> None:')
# Fix _apply
s = s.replace('self._retina_indices = fn(self._retina_indices)', 'if hasattr(self, "_retina_indices") and (getattr(self, "_retina_indices", None) is not None): self._retina_indices = fn(self._retina_indices)')
# Fix hebbian_alpha member
if 'self.hebbian_alpha =' not in s:
s = s.replace('self.som_alpha = float(som_alpha)', 'self.som_alpha = float(som_alpha)\\n self.hebbian_alpha = 0.01')
p_sem.write_text(s)
print('[hotpatch] sdr_semantic.py fix')
# 5. sdr_retina.py: Cache Repo
patch('/workspace/feather/subsystems/sdr_retina.py',
'icarus112/feather-retina-cache',
'GAInTech/feather-retina-cache')
"""
encoded = base64.b64encode(hotpatch_script.encode()).decode()
command = [
"/bin/bash", "-c",
f"python3 -c 'import base64; exec(base64.b64decode(\"{encoded}\"))' && python /app/entrypoint.py"
]
env = {
"FEATHER_RUNTIME_MODE": "job",
"HYDRA_BATCH_SIZE": "96",
"HYDRA_TOTAL_BATCH": "196608",
"HYDRA_USE_NEMOTRON": "1",
"HYDRA_TARGET_SHARDS": "0",
"HYDRA_FORCE_HTM_CPU": "1",
"HYDRA_INERT_MAMBA": "1",
"HYDRA_FASTPATH": "1",
"PYTHONUNBUFFERED": "1",
"HYDRA_RESUME_CKPT": "none"
}
payload = {
"spaceId": space_id,
"command": command,
"environment": env,
"secrets": {"HF_TOKEN": token},
"flavor": "a10g-large",
"timeout": "12h"
}
url = f"https://huggingface.co/api/jobs/{namespace}"
headers = {"Authorization": f"Bearer {token}"}
r = requests.post(url, json=payload, headers=headers)
if r.status_code == 200:
print(f"Success! Job ID: {r.json()['id']}")
else:
print(f"Error {r.status_code}: {r.text}")
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