SolitaryThinker
4e331eb7ff
Mechanical conversion of every relative import under v2/ to an absolute v2.* path (from .x / ..x / ...x -> from v2.<pkg>.x) so imports are unambiguous, grep-able, and stable when code is copied/moved between entrypoints (VideoGenerator, CLI, server). Surgical prefix-only rewrite: only the 'from <dots><module>' prefix changed — import names, parentheses, multi-line formatting, comments, and ordering are byte-for-byte preserved (no collapsing, no reorder, no unrelated reformatting). - 471 imports across 125 files; v2/tests/ was already absolute (untouched). - Validated: all 125 files compile, every 'from v2.* import' target resolves to a real module/package, zero relative imports remain (full sweep), CPU mini suite green (202 passed, 2 skipped).
32 lines
1.7 KiB
Python
32 lines
1.7 KiB
Python
"""BAGEL/lance program (design_v3 §16): one resident MoT instance, two runtime-visible loops.
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tokenize → generate_text (ar_decode) → pack(text→cond) → generate_image (diffusion) → vae_decode
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generate_text and generate_image hit the SAME resident weights; their steps are WorkUnits the
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scheduler interleaves — the shared-weight MoT made native, not a monolith bypassing the abstraction.
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"""
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from __future__ import annotations
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from v2.program import ComponentNode, ModelLoopNode, Program, ProgramKind
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from v2.models.omni import emit_text_node, pack_cond_from_tokens, tokenize_node, vae_decode_node
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def build_bagel_program() -> Program:
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return Program(
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program_id="bagel.mot", kind=ProgramKind.INLINE,
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nodes=[
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ComponentNode("tokenize", fn=tokenize_node, writes=("prompt_tokens",)),
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ModelLoopNode("generate_text", loop_id="generate_text", output_slot="gen_text_out",
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reads=("prompt_tokens",), writes=("gen_text_out",)),
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ComponentNode("emit_text", fn=emit_text_node("gen_text_out", "text"),
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reads=("gen_text_out",), writes=("text",)),
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ComponentNode("pack", fn=pack_cond_from_tokens("gen_text_out"),
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reads=("gen_text_out",), writes=("text_embeds", "neg_text_embeds")),
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ModelLoopNode("generate_image", loop_id="generate_image", output_slot="gen_image_out",
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reads=("text_embeds",), writes=("gen_image_out",)),
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ComponentNode("vae_decode", fn=vae_decode_node("gen_image_out", "image"),
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reads=("gen_image_out",), writes=("image",)),
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],
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output_artifacts={"text": "text", "image": "image"},
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).validate()
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