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+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[Sample example]\n",
+ "Prompt: <|endoftext|>\n",
+ "Response: An artwork of a broken wine bottle in the medium of dry pigments<|endoftext|>\n",
+ "Reward: 7\n",
+ "[Mean prompt length] 1.00 β [1, 1]\n",
+ "[Mean output length] 25.64 β [1, 63]\n",
+ "[Mean sample length] 26.64 β [2, 64]\n",
+ "[Mean return] 5.53 β [1.0, 10.0]\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n"
+ ]
+ },
+ {
+ "data": {
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+ " Evaluation #0 \n",
+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β prompt β output β\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β Quant, Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β Quant Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β Or, 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 β\n",
+ "β β 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 β\n",
+ "β β 131 131 131 131 131 131 131 131 131 131 131 131 131 β\n",
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+ "
\n"
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+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β\u001b[1m \u001b[0m\u001b[1mprompt \u001b[0m\u001b[1m \u001b[0mβ\u001b[1m \u001b[0m\u001b[1moutput \u001b[0m\u001b[1m \u001b[0mβ\n",
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+ "β Hatsune Miku, Red Dress β Quant, Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β Quant Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold Bold β\n",
+ "β β Bold Bold Bold Bold Bold Bold β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β Or, 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 β\n",
+ "β β 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 131 β\n",
+ "β β 131 131 131 131 131 131 131 131 131 131 131 131 131 β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
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+ "output_type": "stream",
+ "text": [
+ "losses/loss: 5.24, losses/loss_q: 0.27, losses/loss_v: 0.06, losses/loss_cql: 18.15, losses/loss_awac: 3.08: 10%|β | 99/1000 [01:43<15:45, 1.05s/it]"
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+ " Evaluation #1 \n",
+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β prompt β output β\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β , ArtStation, High Definition, realistic, 4k color concept paintings, trending, art β\n",
+ "β β stock, character concept concept art, character concept art, 3d concept art, 4k color β\n",
+ "β β concept color concept, ArtStation, trending, trending, trending, trending, trending, β\n",
+ "β β trending, β\n",
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+ "β Hatsune Miku, Red Dress β , 4k color dry white portrait matte concept disc matte concept art, 2d concept still β\n",
+ "β β concept still concept still concept still concept still concept still concept still β\n",
+ "β β concept still concept still concept still β\n",
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+ "β Hatsune Miku, Red Dress β , ArtStation #digitalart, ArtStation #paper, matte color, matte color, ArtStation by β\n",
+ "β β Oskar HellstrΓΆh Its a beautiful painting colorized. β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "
\n"
+ ],
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+ "\u001b[3m Evaluation #1 \u001b[0m\n",
+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β\u001b[1m \u001b[0m\u001b[1mprompt \u001b[0m\u001b[1m \u001b[0mβ\u001b[1m \u001b[0m\u001b[1moutput \u001b[0m\u001b[1m \u001b[0mβ\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β , ArtStation, High Definition, realistic, 4k color concept paintings, trending, art β\n",
+ "β β stock, character concept concept art, character concept art, 3d concept art, 4k color β\n",
+ "β β concept color concept, ArtStation, trending, trending, trending, trending, trending, β\n",
+ "β β trending, β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , 4k color dry white portrait matte concept disc matte concept art, 2d concept still β\n",
+ "β β concept still concept still concept still concept still concept still concept still β\n",
+ "β β concept still concept still concept still β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , ArtStation #digitalart, ArtStation #paper, matte color, matte color, ArtStation by β\n",
+ "β β Oskar HellstrΓΆh Its a beautiful painting colorized. β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "losses/loss: 4.92, losses/loss_q: 0.28, losses/loss_v: 0.04, losses/loss_cql: 16.81, losses/loss_awac: 2.92: 20%|ββ | 199/1000 [03:29<14:03, 1.05s/it]"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ " Evaluation #2 \n",
+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β prompt β output β\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β girl, beautiful color palette, character made, Character art, trending, style β\n",
+ "β β #swtor, trending #swtorcomcast β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , 4kh photography, full color face, trending, fashion house wallpaper, 4k hd, β\n",
+ "β β photography, 4khd, ArtStation HQ, 4k hd, ArtStation HQ, 4k concept concept concept β\n",
+ "β β featured, Key art by Craig Mullins, Mo β\n",
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+ "β Hatsune Miku, Red Dress β , 4k Rembrandt Mark Wahlberg as an ancient man, full color photography, Hi-Fh, β\n",
+ "β β Hi-Pixels drybaking during manufacturing, Hi-Reh drymering at room flame. β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "
\n"
+ ],
+ "text/plain": [
+ "\u001b[3m Evaluation #2 \u001b[0m\n",
+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β\u001b[1m \u001b[0m\u001b[1mprompt \u001b[0m\u001b[1m \u001b[0mβ\u001b[1m \u001b[0m\u001b[1moutput \u001b[0m\u001b[1m \u001b[0mβ\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β girl, beautiful color palette, character made, Character art, trending, style β\n",
+ "β β #swtor, trending #swtorcomcast β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , 4kh photography, full color face, trending, fashion house wallpaper, 4k hd, β\n",
+ "β β photography, 4khd, ArtStation HQ, 4k hd, ArtStation HQ, 4k concept concept concept β\n",
+ "β β featured, Key art by Craig Mullins, Mo β\n",
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+ "β Hatsune Miku, Red Dress β , 4k Rembrandt Mark Wahlberg as an ancient man, full color photography, Hi-Fh, β\n",
+ "β β Hi-Pixels drybaking during manufacturing, Hi-Reh drymering at room flame. β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "losses/loss: 4.75, losses/loss_q: 0.37, losses/loss_v: 0.04, losses/loss_cql: 15.73, losses/loss_awac: 2.76: 30%|βββ | 299/1000 [05:15<12:19, 1.05s/it]"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ " Evaluation #3 \n",
+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β prompt β output β\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β β\n",
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+ "β Hatsune Miku, Red Dress β , White Art, Floating, White, 4k, Floating, Artistic, 4k hd, CGSociety, 4k art, UHD, β\n",
+ "β β 4k art, ArtStation. β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , White, 4kh, 4k, Studio Ghibli, 4k, 4k, Studio Ghibli, Studio Ghibli, 4k, 4k, Studio β\n",
+ "β β Jap, ArtStation, 4k,, Hi-Fh, Hi- β\n",
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+ "
\n"
+ ],
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+ "\u001b[3m Evaluation #3 \u001b[0m\n",
+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β\u001b[1m \u001b[0m\u001b[1mprompt \u001b[0m\u001b[1m \u001b[0mβ\u001b[1m \u001b[0m\u001b[1moutput \u001b[0m\u001b[1m \u001b[0mβ\n",
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+ "β Hatsune Miku, Red Dress β β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , White Art, Floating, White, 4k, Floating, Artistic, 4k hd, CGSociety, 4k art, UHD, β\n",
+ "β β 4k art, ArtStation. β\n",
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+ "β β Jap, ArtStation, 4k,, Hi-Fh, Hi- β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n"
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+ },
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+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β prompt β output β\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β , 4k UHD 4k UHD 4k UHD β\n",
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+ "β Hatsune Miku, Red Dress β , 4k Digital Character Art, Trending on ArtStation, Trendy β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , 4k digital character portrait, realistic character design, David Heskin, Hi-Fh, β\n",
+ "β β Hiigyemi, trending on ArtStation, 4k β\n",
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+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
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+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β , 4k UHD 4k UHD 4k UHD β\n",
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+ "β Hatsune Miku, Red Dress β , 4k Digital Character Art, Trending on ArtStation, Trendy β\n",
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+ "β β Hiigyemi, trending on ArtStation, 4k β\n",
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+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β prompt β output β\n",
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+ "β Hatsune Miku, Red Dress β , Black Eyes, Black Eyes, Black, Black, Black Eyes #1, Black Eyes #5, Black Eyes β\n",
+ "β β #hbphotography, Black, Black Eyes #oem, Trending on Artstation, β\n",
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+ "β Hatsune Miku, Red Dress β β\n",
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+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β , Black Eyes, Black Eyes, Black, Black, Black Eyes #1, Black Eyes #5, Black Eyes β\n",
+ "β β #hbphotography, Black, Black Eyes #oem, Trending on Artstation, β\n",
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+ "β Hatsune Miku, Red Dress β , Cherry, Hi-Pint, Kyoto Art, Keyframe, 4k Character art, ArtStation, UHD HD art β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n"
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+ ]
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+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β prompt β output β\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β , 4k digital illustration, Akihito Yamamoto, Tom Bagshaw, Takato Yamamoto, Takato β\n",
+ "β β Yamamoto, Takato Yamamoto, Hi-Fh, 8k resolution still photography, full color β\n",
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+ "β Hatsune Miku, Red Dress β , White, Black, Pink, White, Pink, Squeaky, 4k Hyperdetailed. β\n",
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+ "β Hatsune Miku, Red Dress β , 4k digital illustration, Ishimori, 4k illustration, ArtstationHQ, CGsociety, Render β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
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+ "β\u001b[1m \u001b[0m\u001b[1mprompt \u001b[0m\u001b[1m \u001b[0mβ\u001b[1m \u001b[0m\u001b[1moutput \u001b[0m\u001b[1m \u001b[0mβ\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β , 4k digital illustration, Akihito Yamamoto, Tom Bagshaw, Takato Yamamoto, Takato β\n",
+ "β β Yamamoto, Takato Yamamoto, Hi-Fh, 8k resolution still photography, full color β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , White, Black, Pink, White, Pink, Squeaky, 4k Hyperdetailed. β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , 4k digital illustration, Ishimori, 4k illustration, ArtstationHQ, CGsociety, Render β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n"
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+ ]
+ },
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+ " Evaluation #7 \n",
+ "βββββββββββββββββββββββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n",
+ "β prompt β output β\n",
+ "β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©\n",
+ "β Hatsune Miku, Red Dress β , 4k photo β\n",
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+ "β Hatsune Miku, Red Dress β , Blue Shoes, Style of art gallery, Ukiyo-e, 4k photo β\n",
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+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , Blue Shoes, Style of art gallery, Ukiyo-e, 4k photo β\n",
+ "βββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€\n",
+ "β Hatsune Miku, Red Dress β , 4k UHD 4k photo by J S Takahashi, Sung Choi, Sung Choi, CGsociety, Hi-Fructose, β\n",
+ "β β CGSociety, HD remap β\n",
+ "βββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ\n"
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+ ]
+ },
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+ " Evaluation #8 \n",
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+ "model_module_version": "1.2.0",
+ "model_name": "LayoutModel",
+ "state": {
+ "_model_module": "@jupyter-widgets/base",
+ "_model_module_version": "1.2.0",
+ "_model_name": "LayoutModel",
+ "_view_count": null,
+ "_view_module": "@jupyter-widgets/base",
+ "_view_module_version": "1.2.0",
+ "_view_name": "LayoutView",
+ "align_content": null,
+ "align_items": null,
+ "align_self": null,
+ "border": null,
+ "bottom": null,
+ "display": null,
+ "flex": null,
+ "flex_flow": null,
+ "grid_area": null,
+ "grid_auto_columns": null,
+ "grid_auto_flow": null,
+ "grid_auto_rows": null,
+ "grid_column": null,
+ "grid_gap": null,
+ "grid_row": null,
+ "grid_template_areas": null,
+ "grid_template_columns": null,
+ "grid_template_rows": null,
+ "height": null,
+ "justify_content": null,
+ "justify_items": null,
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+ "min_width": null,
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+ "overflow_x": null,
+ "overflow_y": null,
+ "padding": null,
+ "right": null,
+ "top": null,
+ "visibility": null,
+ "width": null
+ }
+ },
+ "ffc4ab3f25e749268547690002a4b8c5": {
+ "model_module": "@jupyter-widgets/controls",
+ "model_module_version": "1.5.0",
+ "model_name": "DescriptionStyleModel",
+ "state": {
+ "_model_module": "@jupyter-widgets/controls",
+ "_model_module_version": "1.5.0",
+ "_model_name": "DescriptionStyleModel",
+ "_view_count": null,
+ "_view_module": "@jupyter-widgets/base",
+ "_view_module_version": "1.2.0",
+ "_view_name": "StyleView",
+ "description_width": ""
+ }
+ }
+ }
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
}
diff --git a/examples/randomwalks/randomwalks.py b/examples/randomwalks/randomwalks.py
index dc42126d3..27de95799 100644
--- a/examples/randomwalks/randomwalks.py
+++ b/examples/randomwalks/randomwalks.py
@@ -197,9 +197,7 @@ def metric_fn(
# Calculate optimality scores, in [0, 1], as compared to the shortest
# path
lengths_tensor = torch.tensor(lengths, dtype=torch.float)
- bound_lengths: torch.Tensor = torch.where(
- lengths_tensor.eq(invalid_path_length), max_length, lengths_tensor
- ).abs()
+ bound_lengths: torch.Tensor = torch.where(lengths_tensor.eq(invalid_path_length), max_length, lengths_tensor).abs()
optimal_lengths = torch.as_tensor(sample_optimal_lengths)
# Optimality scores, in [0, 1], as compared to the shortest path
diff --git a/examples/summarize_daily_cnn/t5_summarize_daily_cnn.py b/examples/summarize_daily_cnn/t5_summarize_daily_cnn.py
index 4c3a56758..5e490f29c 100755
--- a/examples/summarize_daily_cnn/t5_summarize_daily_cnn.py
+++ b/examples/summarize_daily_cnn/t5_summarize_daily_cnn.py
@@ -5,22 +5,13 @@
from transformers import AutoTokenizer
import trlx
-from trlx.data.configs import (
- ModelConfig,
- OptimizerConfig,
- SchedulerConfig,
- TokenizerConfig,
- TrainConfig,
- TRLConfig,
-)
+from trlx.data.configs import ModelConfig, OptimizerConfig, SchedulerConfig, TokenizerConfig, TrainConfig, TRLConfig
from trlx.models.modeling_ppo import PPOConfig
try:
import evaluate
except ImportError:
- raise ImportError(
- "To run this example, please install the `evaluate` and `nltk` packages" "by running `pip install evaluate`"
- )
+ raise ImportError("To run this example, please install the `evaluate` and `nltk` packages" "by running `pip install evaluate`")
config = TRLConfig(
train=TrainConfig(
diff --git a/examples/summarize_rlhf/sft/train_gptj_summarize.py b/examples/summarize_rlhf/sft/train_gptj_summarize.py
index b0da7d525..36a2b59d0 100755
--- a/examples/summarize_rlhf/sft/train_gptj_summarize.py
+++ b/examples/summarize_rlhf/sft/train_gptj_summarize.py
@@ -4,13 +4,7 @@
import numpy as np
import torch
from summarize_dataset import TLDRDataset
-from transformers import (
- AutoModelForCausalLM,
- AutoTokenizer,
- Trainer,
- TrainingArguments,
- default_data_collator,
-)
+from transformers import AutoModelForCausalLM, AutoTokenizer, Trainer, TrainingArguments, default_data_collator
def set_seed(seed_val=42):
diff --git a/examples/summarize_rlhf/trlx_gptj_text_summarization.py b/examples/summarize_rlhf/trlx_gptj_text_summarization.py
index 5ce01afce..7da6b8fce 100755
--- a/examples/summarize_rlhf/trlx_gptj_text_summarization.py
+++ b/examples/summarize_rlhf/trlx_gptj_text_summarization.py
@@ -8,14 +8,7 @@
from transformers import AutoTokenizer
import trlx
-from trlx.data.configs import (
- ModelConfig,
- OptimizerConfig,
- SchedulerConfig,
- TokenizerConfig,
- TrainConfig,
- TRLConfig,
-)
+from trlx.data.configs import ModelConfig, OptimizerConfig, SchedulerConfig, TokenizerConfig, TrainConfig, TRLConfig
from trlx.models.modeling_ppo import PPOConfig
REWARD_CHECKPOINT_PATH = "reward_model/rm_checkpoint/pytorch_model.bin"
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 000000000..cb4885a4f
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,1294 @@
+# This file is automatically @generated by Poetry and should not be changed by hand.
+
+[[package]]
+name = "appnope"
+version = "0.1.3"
+description = "Disable App Nap on macOS >= 10.9"
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+python-versions = "*"
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+ {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
+]
+
+[[package]]
+name = "astroid"
+version = "2.14.2"
+description = "An abstract syntax tree for Python with inference support."
+category = "dev"
+optional = false
+python-versions = ">=3.7.2"
+files = [
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+lazy-object-proxy = ">=1.4.0"
+typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""}
+wrapt = [
+ {version = ">=1.11,<2", markers = "python_version < \"3.11\""},
+ {version = ">=1.14,<2", markers = "python_version >= \"3.11\""},
+]
+
+[[package]]
+name = "asttokens"
+version = "2.2.1"
+description = "Annotate AST trees with source code positions"
+category = "main"
+optional = false
+python-versions = "*"
+files = [
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+ {file = "asttokens-2.2.1.tar.gz", hash = "sha256:4622110b2a6f30b77e1473affaa97e711bc2f07d3f10848420ff1898edbe94f3"},
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+[package.dependencies]
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+
+[package.extras]
+test = ["astroid", "pytest"]
+
+[[package]]
+name = "attrs"
+version = "22.2.0"
+description = "Classes Without Boilerplate"
+category = "dev"
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+[package.extras]
+cov = ["attrs[tests]", "coverage-enable-subprocess", "coverage[toml] (>=5.3)"]
+dev = ["attrs[docs,tests]"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope.interface"]
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+
+[[package]]
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+category = "main"
+optional = false
+python-versions = "*"
+files = [
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+[[package]]
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+ {file = "wrapt-1.15.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:078e2a1a86544e644a68422f881c48b84fef6d18f8c7a957ffd3f2e0a74a0d4a"},
+ {file = "wrapt-1.15.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:2cf56d0e237280baed46f0b5316661da892565ff58309d4d2ed7dba763d984b8"},
+ {file = "wrapt-1.15.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:7dc0713bf81287a00516ef43137273b23ee414fe41a3c14be10dd95ed98a2df9"},
+ {file = "wrapt-1.15.0-cp39-cp39-win32.whl", hash = "sha256:46ed616d5fb42f98630ed70c3529541408166c22cdfd4540b88d5f21006b0eff"},
+ {file = "wrapt-1.15.0-cp39-cp39-win_amd64.whl", hash = "sha256:eef4d64c650f33347c1f9266fa5ae001440b232ad9b98f1f43dfe7a79435c0a6"},
+ {file = "wrapt-1.15.0-py3-none-any.whl", hash = "sha256:64b1df0f83706b4ef4cfb4fb0e4c2669100fd7ecacfb59e091fad300d4e04640"},
+ {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
+]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.8"
+content-hash = "ebdfcb7682b8da5f97021c19c88bf55905f394c5a4c7a12c74231a6211c174b3"
diff --git a/pyproject.toml b/pyproject.toml
index 40e261241..048840e42 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,15 +1,101 @@
-[build-system]
-requires = ["setuptools"]
-build-backend = "setuptools.build_meta"
-
-[tool.isort]
-multi_line_output = 3
-profile = "black"
-
-[tool.black]
-line-length = 120
-
[tool.pytest.ini_options]
minversion = "6.0"
addopts = "-ra -q --doctest-modules -vv --cov=trlx/ "
testpaths = ["tests"]
+
+[tool.poetry]
+name = "trlx"
+authors = ["The CarperAI team"]
+description = "Transformer Reinforcement Learning X: A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)"
+keywords = ["Deep Learning", "Reinforcement Learning"]
+license = "MIT"
+readme = "README.md"
+homepage = "https://github.com/CarperAI/trlx"
+repository = "https://github.com/CarperAI/trlx"
+version = "0.5.0"
+classifiers = [
+ "Development Status :: 3 - Alpha",
+ "Intended Audience :: Developers",
+ "Intended Audience :: Education",
+ "Intended Audience :: Science/Research",
+ "License :: OSI Approved :: MIT>=0.13.5",
+ "Operating System :: OS Independent",
+ "Programming Language :: Python :: 3",
+ "Programming Language :: Python :: 3.8",
+ "Topic :: Scientific/Engineering :: Artificial Intelligence"
+]
+include = [
+ { path = 'CHANGELOG.md', format = 'sdist' },
+ { path = 'LICENSE', format = 'sdist' },
+ { path = 'README.md', format = 'sdist' },
+ { path = 'docs', format = 'sdist' },
+ { path = 'tests', format = 'sdist' },
+]
+
+# Published version is managed using Git tags
+# We get either the tag (like "0.24.1") or a snapshot-type version (like "0.24.1+3.e8319c4")
+# If the plugin is not installed, then the version is always "0.0.0", taken from above
+[tool.poetry-dynamic-versioning]
+enable = true
+pattern = '^[vV](?P\d+\.\d+\.\d+)' # this extracts the version from our vX.Y.Z tag format
+format-jinja = "{% if distance == 0 and not dirty %}{{ base }}{% else %}{{ base }}+{{ distance }}.{{ commit }}{% endif %}"
+
+[tool.poetry.dependencies]
+python = "^3.8"
+black = { extras = ["jupyter"], version = "^23.1.0" }
+
+[tool.flake8]
+max-complexity = 10
+max-line-length = 127
+# flake8 error codes: https://flake8.pycqa.org/en/latest/user/error-codes.html
+# pycodestyle codes: https://pycodestyle.pycqa.org/en/latest/intro.html#error-codes
+# E203 # whitespace before β,β, β;β, or β:β
+# E741 # do not use variables named βlβ, βOβ, or βIβ
+# F401 # module imported but unused
+# F821 # undefined name name
+# W503 # line break before binary operator
+# W605 # invalid escape sequence βxβ
+ignore = ["E203", "E741", "F821", "W503", "W605"]
+per-file-ignores = "__init__.py:F401,loading.py:F401"
+exclude = [".git", "__pycache__", "docs/source/conf.py", "build", "dist"]
+
+[tool.poetry.group.dev.dependencies]
+pytest = "^7.2.1"
+pytest-testdox = "^3.0.1"
+coverage = "^6.5.0"
+pylint = "^2.16.2"
+pre-commit = "^3.1.0"
+black = "^23.1.0"
+mypy = "^1.0.1"
+isort = "^5.12.0"
+coveralls = "^3.3.1"
+click = "^8.1.3"
+colorama = "~0, >=0.4.6"
+
+[tool.black]
+line-length = 132
+target-version = ['py38', 'py39', 'py310', 'py311']
+include = '(src\/scripts\/.*$|\.pyi?$)'
+exclude = '''
+/(
+ \.git
+ | __pycache__
+ | \.tox
+ | \.venv
+ | \.poetry
+ | build
+ | dist
+ | docs
+ | notes
+)/
+'''
+
+[tool.isort]
+skip_glob = ["docs", "notes"]
+profile = "black"
+line_length = 132
+multi_line_output = 3
+
+[build-system]
+requires = ["poetry-core>=1.0.0", "poetry-dynamic-versioning"]
+build-backend = "poetry_dynamic_versioning.backend"
diff --git a/setup.cfg b/setup.cfg
index cdf160d16..e69de29bb 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,94 +0,0 @@
-[metadata]
-author = The CarperAI team
-description = Transformer Reinforcement Learning X: A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)
-keywords =
- Deep Learning
- Reinforcement Learning
-license = MIT
-long_description = file: README.md
-long_description_content_type = text/markdown
-name = trlx
-url = https://github.com/CarperAI/trlx
-version = v0.5.0
-
-classifiers =
- Development Status :: 3 - Alpha
- Intended Audience :: Developers
- Intended Audience :: Education
- Intended Audience :: Science/Research
- License :: OSI Approved :: MIT>=0.13.5
- Operating System :: OS Independent
- Programming Language :: Python :: 3
- Programming Language :: Python :: 3.8
- Topic :: Scientific/Engineering :: Artificial Intelligence
-
-
-[options]
-python_requires =
- >=3.8.0
-packages = find:
-install_requires =
- accelerate~=0.15.0
- attrs ~=22.1.0
- cattrs ~=22.2.0
- datasets
- deepspeed>=0.7.3
- einops>=0.4.1
- networkx
- numpy>=1.23.2
- packaging>=20.0
- psutil
- pyyaml
- ray
- ray>=2.0.1
- rich
- tabulate>=0.9.0
- torch~=1.13.0
- torchtyping~=0.1.4
- tqdm
- transformers>=4.21.2
- typing-extensions~=3.10.0
- tritonclient
-
-[options.extras_require]
-bnb =
- bitsandbytes
-wandb =
- wandb
-dev =
- black
- isort
- flake8
- pre-commit>= 2.21.0
- pytest>=6.0
- pytest-cov
-
-[options.packages.find]
-exclude =
- docs*
- tests*
-
-[flake8]
-max-complexity = 10
-max-line-length = 127
-# flake8 error codes: https://flake8.pycqa.org/en/latest/user/error-codes.html
-# pycodestyle codes: https://pycodestyle.pycqa.org/en/latest/intro.html#error-codes
-# E203 # whitespace before β,β, β;β, or β:β
-# E741 # do not use variables named βlβ, βOβ, or βIβ
-# F401 # module imported but unused
-# F821 # undefined name name
-# W503 # line break before binary operator
-# W605 # invalid escape sequence βxβ
-ignore =
- E203
- E741
- F821
- W503
- W605
-per-file-ignores = __init__.py:F401,loading.py:F401
-exclude =
- .git
- __pycache__
- docs/source/conf.py
- build
- dist
diff --git a/setup.py b/setup.py
index 482112223..7f1a1763c 100644
--- a/setup.py
+++ b/setup.py
@@ -1,5 +1,4 @@
from setuptools import setup
-e
if __name__ == "__main__":
setup()
diff --git a/trlx/__init__.py b/src/trlx/__init__.py
similarity index 100%
rename from trlx/__init__.py
rename to src/trlx/__init__.py
diff --git a/trlx/data/__init__.py b/src/trlx/data/__init__.py
similarity index 100%
rename from trlx/data/__init__.py
rename to src/trlx/data/__init__.py
diff --git a/trlx/data/accelerate_base_datatypes.py b/src/trlx/data/accelerate_base_datatypes.py
similarity index 100%
rename from trlx/data/accelerate_base_datatypes.py
rename to src/trlx/data/accelerate_base_datatypes.py
diff --git a/trlx/data/configs.py b/src/trlx/data/configs.py
similarity index 100%
rename from trlx/data/configs.py
rename to src/trlx/data/configs.py
diff --git a/trlx/data/default_configs.py b/src/trlx/data/default_configs.py
similarity index 77%
rename from trlx/data/default_configs.py
rename to src/trlx/data/default_configs.py
index 1f9297db2..9e34118a8 100644
--- a/trlx/data/default_configs.py
+++ b/src/trlx/data/default_configs.py
@@ -2,14 +2,7 @@
from trlx.models.modeling_ppo import PPOConfig
from trlx.trainer.accelerate_sft_trainer import SFTConfig
-from .configs import (
- ModelConfig,
- OptimizerConfig,
- SchedulerConfig,
- TokenizerConfig,
- TrainConfig,
- TRLConfig,
-)
+from .configs import ModelConfig, OptimizerConfig, SchedulerConfig, TokenizerConfig, TrainConfig, TRLConfig
def default_ppo_config():
@@ -26,9 +19,7 @@ def default_ppo_config():
),
model=ModelConfig(model_path="lvwerra/gpt2-imdb", num_layers_unfrozen=2),
tokenizer=TokenizerConfig(tokenizer_path="gpt2", truncation_side="right"),
- optimizer=OptimizerConfig(
- name="adamw", kwargs=dict(lr=1.0e-4, betas=(0.9, 0.95), eps=1.0e-8, weight_decay=1.0e-6)
- ),
+ optimizer=OptimizerConfig(name="adamw", kwargs=dict(lr=1.0e-4, betas=(0.9, 0.95), eps=1.0e-8, weight_decay=1.0e-6)),
scheduler=SchedulerConfig(name="cosine_annealing", kwargs=dict(T_max=10000, eta_min=1.0e-4)),
method=PPOConfig(
name="PPOConfig",
@@ -71,12 +62,8 @@ def default_ilql_config():
),
model=ModelConfig(model_path="gpt2", num_layers_unfrozen=-1),
tokenizer=TokenizerConfig(tokenizer_path="gpt2", truncation_side="right"),
- optimizer=OptimizerConfig(
- name="adamw", kwargs=dict(lr=5.0e-5, betas=(0.9, 0.95), eps=1.0e-8, weight_decay=1.0e-6)
- ),
- scheduler=SchedulerConfig(
- name="cosine_annealing", kwargs=dict(T_max=1000, eta_min=5.0e-5) # train.total_steps
- ),
+ optimizer=OptimizerConfig(name="adamw", kwargs=dict(lr=5.0e-5, betas=(0.9, 0.95), eps=1.0e-8, weight_decay=1.0e-6)),
+ scheduler=SchedulerConfig(name="cosine_annealing", kwargs=dict(T_max=1000, eta_min=5.0e-5)), # train.total_steps
method=ILQLConfig(
name="ilqlconfig",
tau=0.7,
@@ -106,12 +93,8 @@ def default_sft_config():
),
model=ModelConfig(model_path="gpt2", num_layers_unfrozen=-1),
tokenizer=TokenizerConfig(tokenizer_path="gpt2", truncation_side="right"),
- optimizer=OptimizerConfig(
- name="adamw", kwargs=dict(lr=1.0e-4, betas=(0.9, 0.95), eps=1.0e-8, weight_decay=1.0e-6)
- ),
- scheduler=SchedulerConfig(
- name="cosine_annealing", kwargs=dict(T_max=10000, eta_min=1.0e-4) # train.total_steps
- ),
+ optimizer=OptimizerConfig(name="adamw", kwargs=dict(lr=1.0e-4, betas=(0.9, 0.95), eps=1.0e-8, weight_decay=1.0e-6)),
+ scheduler=SchedulerConfig(name="cosine_annealing", kwargs=dict(T_max=10000, eta_min=1.0e-4)), # train.total_steps
method=SFTConfig(
name="sftconfig",
gen_kwargs=dict(max_new_tokens=40, top_k=0, top_p=1.0, do_sample=True),
diff --git a/trlx/data/ilql_types.py b/src/trlx/data/ilql_types.py
similarity index 100%
rename from trlx/data/ilql_types.py
rename to src/trlx/data/ilql_types.py
diff --git a/trlx/data/method_configs.py b/src/trlx/data/method_configs.py
similarity index 100%
rename from trlx/data/method_configs.py
rename to src/trlx/data/method_configs.py
diff --git a/trlx/data/ppo_types.py b/src/trlx/data/ppo_types.py
similarity index 100%
rename from trlx/data/ppo_types.py
rename to src/trlx/data/ppo_types.py
diff --git a/trlx/models/README.md b/src/trlx/models/README.md
similarity index 100%
rename from trlx/models/README.md
rename to src/trlx/models/README.md
diff --git a/trlx/models/__init__.py b/src/trlx/models/__init__.py
similarity index 100%
rename from trlx/models/__init__.py
rename to src/trlx/models/__init__.py
diff --git a/trlx/models/modeling_base.py b/src/trlx/models/modeling_base.py
similarity index 100%
rename from trlx/models/modeling_base.py
rename to src/trlx/models/modeling_base.py
diff --git a/trlx/models/modeling_ilql.py b/src/trlx/models/modeling_ilql.py
similarity index 97%
rename from trlx/models/modeling_ilql.py
rename to src/trlx/models/modeling_ilql.py
index 5eab697e4..0b6a1db9d 100644
--- a/trlx/models/modeling_ilql.py
+++ b/src/trlx/models/modeling_ilql.py
@@ -16,13 +16,7 @@
from trlx.data.ilql_types import ILQLBatch
from trlx.data.method_configs import MethodConfig, register_method
from trlx.models.modeling_base import PreTrainedModelWrapper
-from trlx.utils.modeling import (
- flatten_dict,
- get_tensor_stats,
- hf_get_hidden_size,
- hf_get_lm_head,
- make_head,
-)
+from trlx.utils.modeling import flatten_dict, get_tensor_stats, hf_get_hidden_size, hf_get_lm_head, make_head
def topk_mask(xs: torch.FloatTensor, k: int):
@@ -83,10 +77,7 @@ def loss(self, outputs, labels: ILQLBatch):
targetQ = targetQ.detach()
loss_v = (
- (
- (targetQ >= V).int() * self.tau * (targetQ - V).pow(2)
- + (targetQ < V).int() * (1 - self.tau) * (targetQ - V).pow(2)
- )
+ ((targetQ >= V).int() * self.tau * (targetQ - V).pow(2) + (targetQ < V).int() * (1 - self.tau) * (targetQ - V).pow(2))
* terminal_mask
).sum() / n_nonterminal
@@ -191,7 +182,7 @@ def sync_target_q_heads(self):
class AutoModelForCausalLMWithILQLHeads(PreTrainedModelWrapper):
- """An `AutoModel` class wrapper for `transformers` causal models wtih a language
+ """An `AutoModel` class wrapper for `transformers` causal models with a language
modeling head and ILQL heads.
References:
diff --git a/trlx/models/modeling_nemo_ilql.py b/src/trlx/models/modeling_nemo_ilql.py
similarity index 97%
rename from trlx/models/modeling_nemo_ilql.py
rename to src/trlx/models/modeling_nemo_ilql.py
index 17cfef358..4c8b6ae4e 100644
--- a/trlx/models/modeling_nemo_ilql.py
+++ b/src/trlx/models/modeling_nemo_ilql.py
@@ -11,32 +11,17 @@
import torch.nn as nn
import torch.nn.functional as F
from apex.transformer import parallel_state, tensor_parallel
-from apex.transformer.tensor_parallel.mappings import (
- gather_from_sequence_parallel_region,
-)
+from apex.transformer.tensor_parallel.mappings import gather_from_sequence_parallel_region
from einops import rearrange
-from nemo.collections.nlp.data.language_modeling.megatron.megatron_batch_samplers import (
- MegatronPretrainingBatchSampler,
-)
-from nemo.collections.nlp.models.language_modeling.megatron.gpt_model import (
- post_language_model_processing,
-)
-from nemo.collections.nlp.models.language_modeling.megatron_gpt_model import (
- MegatronGPTModel,
-)
-from nemo.collections.nlp.modules.common.megatron.module import (
- Float16Module,
- MegatronModule,
-)
+from nemo.collections.nlp.data.language_modeling.megatron.megatron_batch_samplers import MegatronPretrainingBatchSampler
+from nemo.collections.nlp.models.language_modeling.megatron.gpt_model import post_language_model_processing
+from nemo.collections.nlp.models.language_modeling.megatron_gpt_model import MegatronGPTModel
+from nemo.collections.nlp.modules.common.megatron.module import Float16Module, MegatronModule
from nemo.collections.nlp.modules.common.megatron.utils import (
average_losses_across_data_parallel_group,
get_ltor_masks_and_position_ids,
)
-from nemo.collections.nlp.modules.common.transformer.text_generation import (
- LengthParam,
- OutputType,
- SamplingParam,
-)
+from nemo.collections.nlp.modules.common.transformer.text_generation import LengthParam, OutputType, SamplingParam
from nemo.collections.nlp.parts.utils_funcs import get_last_rank
from trlx.data.ilql_types import ILQLBatch, unflatten_dataclass
@@ -61,9 +46,7 @@ def __init__(
):
super().__init__()
- no_async_tensor_model_parallel_allreduce = (
- parallel_state.get_tensor_model_parallel_world_size() == 1 or sequence_parallel
- )
+ no_async_tensor_model_parallel_allreduce = parallel_state.get_tensor_model_parallel_world_size() == 1 or sequence_parallel
if in_size < out_size:
self.layer = tensor_parallel.ColumnParallelLinear(
@@ -597,9 +580,7 @@ def validation_step(self, batch: Tuple[List[int], List[int]], batch_idx: int):
self.sequence_parallel_(True)
# NeMo generate resets the microbatch calculator
- from apex.transformer.pipeline_parallel.utils import (
- _reconfigure_microbatch_calculator,
- )
+ from apex.transformer.pipeline_parallel.utils import _reconfigure_microbatch_calculator
from nemo.utils import AppState
_reconfigure_microbatch_calculator(
diff --git a/trlx/models/modeling_ppo.py b/src/trlx/models/modeling_ppo.py
similarity index 97%
rename from trlx/models/modeling_ppo.py
rename to src/trlx/models/modeling_ppo.py
index 787286123..8602aef80 100644
--- a/trlx/models/modeling_ppo.py
+++ b/src/trlx/models/modeling_ppo.py
@@ -448,9 +448,7 @@ def forward( # noqa: max-complexity
batch_size = hidden_states.size()[0]
output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
- output_hidden_states = (
- output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
- )
+ output_hidden_states = output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
use_cache = use_cache if use_cache is not None else self.config.use_cache
return_dict = return_dict if return_dict is not None else self.config.use_return_dict
@@ -580,9 +578,7 @@ def forward( # noqa: max-complexity
https://github.com/huggingface/transformers/blob/bdb84e2bada3658f99c6a81c963ec562f8485151/src/transformers/models/opt/modeling_opt.py#L840 # noqa: E501
"""
output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
- output_hidden_states = (
- output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
- )
+ output_hidden_states = output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
use_cache = use_cache if use_cache is not None else self.config.use_cache
return_dict = return_dict if return_dict is not None else self.config.use_return_dict
@@ -601,9 +597,9 @@ def forward( # noqa: max-complexity
).to(hidden_states.device)
if attention_mask is not None:
- expanded_attn_mask = modeling_opt._expand_mask(
- attention_mask, hidden_states.dtype, tgt_len=input_shape[-1]
- ).to(hidden_states.device)
+ expanded_attn_mask = modeling_opt._expand_mask(attention_mask, hidden_states.dtype, tgt_len=input_shape[-1]).to(
+ hidden_states.device
+ )
combined_attention_mask = (
expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask
)
@@ -700,9 +696,7 @@ def forward( # noqa: max-complexity
https://github.com/huggingface/transformers/blob/2411f0e465e761790879e605a4256f3d4afb7f82/src/transformers/models/bloom/modeling_bloom.py#L623 # noqa: E501
"""
output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
- output_hidden_states = (
- output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
- )
+ output_hidden_states = output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
use_cache = use_cache if use_cache is not None else self.config.use_cache
return_dict = return_dict if return_dict is not None else self.config.use_return_dict
@@ -1008,18 +1002,14 @@ def forward( # noqa: max-complexity
batch_size, seq_length = hidden_states.shape[:2]
input_shape = (batch_size, seq_length)
- output_hidden_states = (
- output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
- )
+ output_hidden_states = output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
return_dict = return_dict if return_dict is not None else self.config.use_return_dict
if attention_mask is None:
attention_mask = torch.ones(batch_size, seq_length, device=hidden_states.device)
if self.is_decoder and encoder_attention_mask is None and encoder_hidden_states is not None:
encoder_seq_length = encoder_hidden_states.shape[1]
- encoder_attention_mask = torch.ones(
- batch_size, encoder_seq_length, device=hidden_states.device, dtype=torch.long
- )
+ encoder_attention_mask = torch.ones(batch_size, encoder_seq_length, device=hidden_states.device, dtype=torch.long)
extended_attention_mask = self.get_extended_attention_mask(attention_mask, input_shape)
diff --git a/trlx/pipeline/__init__.py b/src/trlx/pipeline/__init__.py
similarity index 100%
rename from trlx/pipeline/__init__.py
rename to src/trlx/pipeline/__init__.py
diff --git a/trlx/pipeline/offline_pipeline.py b/src/trlx/pipeline/offline_pipeline.py
similarity index 93%
rename from trlx/pipeline/offline_pipeline.py
rename to src/trlx/pipeline/offline_pipeline.py
index dfd09dea8..3897df347 100644
--- a/trlx/pipeline/offline_pipeline.py
+++ b/src/trlx/pipeline/offline_pipeline.py
@@ -57,17 +57,13 @@ class PromptPipeline(BasePipeline):
def __init__(self, prompts: List[str], max_prompt_length: int, tokenizer: PreTrainedTokenizer):
super().__init__()
- model_inputs = tokenizer(
- prompts, truncation=True, padding=False, max_length=max_prompt_length, add_special_tokens=False
- )
+ model_inputs = tokenizer(prompts, truncation=True, padding=False, max_length=max_prompt_length, add_special_tokens=False)
prompts_tokens = model_inputs["input_ids"]
attention_mask = model_inputs["attention_mask"]
self.tokenizer = tokenizer
- self.prompts = [
- {"input_ids": tokens, "attention_mask": mask} for tokens, mask in zip(prompts_tokens, attention_mask)
- ]
+ self.prompts = [{"input_ids": tokens, "attention_mask": mask} for tokens, mask in zip(prompts_tokens, attention_mask)]
def __getitem__(self, ix: int):
return self.prompts[ix]
diff --git a/trlx/pipeline/ppo_pipeline.py b/src/trlx/pipeline/ppo_pipeline.py
similarity index 100%
rename from trlx/pipeline/ppo_pipeline.py
rename to src/trlx/pipeline/ppo_pipeline.py
diff --git a/trlx/ray_tune/__init__.py b/src/trlx/ray_tune/__init__.py
similarity index 100%
rename from trlx/ray_tune/__init__.py
rename to src/trlx/ray_tune/__init__.py
diff --git a/trlx/ray_tune/train_funcs.py b/src/trlx/ray_tune/train_funcs.py
similarity index 100%
rename from trlx/ray_tune/train_funcs.py
rename to src/trlx/ray_tune/train_funcs.py
diff --git a/trlx/ray_tune/wandb.py b/src/trlx/ray_tune/wandb.py
similarity index 100%
rename from trlx/ray_tune/wandb.py
rename to src/trlx/ray_tune/wandb.py
diff --git a/trlx/sweep.py b/src/trlx/sweep.py
similarity index 100%
rename from trlx/sweep.py
rename to src/trlx/sweep.py
diff --git a/trlx/trainer/__init__.py b/src/trlx/trainer/__init__.py
similarity index 100%
rename from trlx/trainer/__init__.py
rename to src/trlx/trainer/__init__.py
diff --git a/trlx/trainer/accelerate_base_trainer.py b/src/trlx/trainer/accelerate_base_trainer.py
similarity index 98%
rename from trlx/trainer/accelerate_base_trainer.py
rename to src/trlx/trainer/accelerate_base_trainer.py
index 0e92efc90..ed2ba9e37 100644
--- a/trlx/trainer/accelerate_base_trainer.py
+++ b/src/trlx/trainer/accelerate_base_trainer.py
@@ -227,9 +227,7 @@ def generate(self, input_ids, attention_mask=None, **kwargs):
kwargs = dict(self.generate_kwargs, **kwargs)
with torch.no_grad():
- return self.accelerator.unwrap_model(self.model).generate(
- input_ids=input_ids, attention_mask=attention_mask, **kwargs
- )
+ return self.accelerator.unwrap_model(self.model).generate(input_ids=input_ids, attention_mask=attention_mask, **kwargs)
def generate_eval(self, input_ids, attention_mask=None, **kwargs):
"""Wraps hf's `generate` adding some specific method's defaults"""
@@ -240,9 +238,7 @@ def generate_eval(self, input_ids, attention_mask=None, **kwargs):
kwargs = dict(self.generate_kwargs, **kwargs)
with torch.no_grad():
- return self.accelerator.unwrap_model(self.model).generate(
- input_ids=input_ids, attention_mask=attention_mask, **kwargs
- )
+ return self.accelerator.unwrap_model(self.model).generate(input_ids=input_ids, attention_mask=attention_mask, **kwargs)
def save(self, directory: Optional[str] = None):
"""Creates a checkpoint of the optimizer, scheduler and model"""
@@ -378,9 +374,7 @@ def evaluate(self): # noqa: C901
)
stats["time/metric"] = time() - metric_time
- mean_metrics = {
- f"metrics/{k}{sweep_suffix}": torch.as_tensor(xs).mean(-1) for k, xs in metrics.items()
- }
+ mean_metrics = {f"metrics/{k}{sweep_suffix}": torch.as_tensor(xs).mean(-1) for k, xs in metrics.items()}
stats.update(mean_metrics)
diff --git a/trlx/trainer/accelerate_ilql_trainer.py b/src/trlx/trainer/accelerate_ilql_trainer.py
similarity index 100%
rename from trlx/trainer/accelerate_ilql_trainer.py
rename to src/trlx/trainer/accelerate_ilql_trainer.py
diff --git a/trlx/trainer/accelerate_ppo_trainer.py b/src/trlx/trainer/accelerate_ppo_trainer.py
similarity index 99%
rename from trlx/trainer/accelerate_ppo_trainer.py
rename to src/trlx/trainer/accelerate_ppo_trainer.py
index c988ea12d..afea3ac36 100644
--- a/trlx/trainer/accelerate_ppo_trainer.py
+++ b/src/trlx/trainer/accelerate_ppo_trainer.py
@@ -442,10 +442,7 @@ def make_experience(self, num_rollouts: int = 1024, iter_count: int = 0): # noq
kl_divergence_estimate: List[torch.Tensor] = [
-self.kl_ctl.value
- * (
- logprobs[sample_idx, start : ends[sample_idx]]
- - ref_logprobs[sample_idx, start : ends[sample_idx]]
- )
+ * (logprobs[sample_idx, start : ends[sample_idx]] - ref_logprobs[sample_idx, start : ends[sample_idx]])
for sample_idx in range(n_samples)
]
diff --git a/trlx/trainer/accelerate_sft_trainer.py b/src/trlx/trainer/accelerate_sft_trainer.py
similarity index 100%
rename from trlx/trainer/accelerate_sft_trainer.py
rename to src/trlx/trainer/accelerate_sft_trainer.py
diff --git a/trlx/trainer/nemo_ilql_trainer.py b/src/trlx/trainer/nemo_ilql_trainer.py
similarity index 98%
rename from trlx/trainer/nemo_ilql_trainer.py
rename to src/trlx/trainer/nemo_ilql_trainer.py
index a23a94f43..a5b7fd0e3 100644
--- a/trlx/trainer/nemo_ilql_trainer.py
+++ b/src/trlx/trainer/nemo_ilql_trainer.py
@@ -14,9 +14,7 @@
from omegaconf.omegaconf import OmegaConf, open_dict
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks.timer import Timer
-from pytorch_lightning.trainer.connectors.checkpoint_connector import (
- CheckpointConnector,
-)
+from pytorch_lightning.trainer.connectors.checkpoint_connector import CheckpointConnector
from rich.console import Console
from rich.table import Table
@@ -24,11 +22,7 @@
from trlx.data.ilql_types import ILQLBatch, ILQLElement, flatten_dataclass
from trlx.models.modeling_ilql import ILQLConfig
from trlx.models.modeling_nemo_ilql import ILQLGPT
-from trlx.pipeline.offline_pipeline import (
- ILQLRolloutStorage,
- ilql_collate_fn,
- tokenize_dialogue,
-)
+from trlx.pipeline.offline_pipeline import ILQLRolloutStorage, ilql_collate_fn, tokenize_dialogue
from trlx.trainer import register_trainer
from . import BaseRLTrainer
diff --git a/trlx/trlx.py b/src/trlx/trlx.py
similarity index 97%
rename from trlx/trlx.py
rename to src/trlx/trlx.py
index f50753d14..b5f998faf 100644
--- a/trlx/trlx.py
+++ b/src/trlx/trlx.py
@@ -3,11 +3,7 @@
from typing import Callable, Dict, Iterable, List, Optional, Tuple
from trlx.data.configs import TRLConfig
-from trlx.data.default_configs import (
- default_ilql_config,
- default_ppo_config,
- default_sft_config,
-)
+from trlx.data.default_configs import default_ilql_config, default_ppo_config, default_sft_config
from trlx.utils import set_seed
from trlx.utils.loading import get_pipeline, get_trainer
diff --git a/trlx/utils/__init__.py b/src/trlx/utils/__init__.py
similarity index 97%
rename from trlx/utils/__init__.py
rename to src/trlx/utils/__init__.py
index 803557724..f1d6e85e6 100644
--- a/trlx/utils/__init__.py
+++ b/src/trlx/utils/__init__.py
@@ -102,8 +102,7 @@ def get_optimizer_class(name: OptimizerName):
return Adam8bit
except ImportError:
raise ImportError(
- "You must install the `bitsandbytes` package to use the 8-bit Adam. "
- "Install with: `pip install bitsandbytes`"
+ "You must install the `bitsandbytes` package to use the 8-bit Adam. " "Install with: `pip install bitsandbytes`"
)
if name == OptimizerName.ADAMW_8BIT_BNB.value:
try:
@@ -112,8 +111,7 @@ def get_optimizer_class(name: OptimizerName):
return AdamW8bit
except ImportError:
raise ImportError(
- "You must install the `bitsandbytes` package to use 8-bit AdamW. "
- "Install with: `pip install bitsandbytes`"
+ "You must install the `bitsandbytes` package to use 8-bit AdamW. " "Install with: `pip install bitsandbytes`"
)
if name == OptimizerName.SGD.value:
return torch.optim.SGD
diff --git a/trlx/utils/loading.py b/src/trlx/utils/loading.py
similarity index 100%
rename from trlx/utils/loading.py
rename to src/trlx/utils/loading.py
diff --git a/trlx/utils/logging.py b/src/trlx/utils/logging.py
similarity index 98%
rename from trlx/utils/logging.py
rename to src/trlx/utils/logging.py
index 79badb4a3..ef97398b9 100644
--- a/trlx/utils/logging.py
+++ b/src/trlx/utils/logging.py
@@ -244,9 +244,7 @@ def enable_explicit_format() -> None:
handlers = _get_library_root_logger().handlers
for handler in handlers:
- formatter = logging.Formatter(
- "[%(asctime)s] [%(levelname)s] [%(filename)s:%(lineno)d:%(funcName)s] %(message)s"
- )
+ formatter = logging.Formatter("[%(asctime)s] [%(levelname)s] [%(filename)s:%(lineno)d:%(funcName)s] %(message)s")
handler.setFormatter(formatter)
diff --git a/trlx/utils/modeling.py b/src/trlx/utils/modeling.py
similarity index 97%
rename from trlx/utils/modeling.py
rename to src/trlx/utils/modeling.py
index d810dacc4..9de070e90 100644
--- a/trlx/utils/modeling.py
+++ b/src/trlx/utils/modeling.py
@@ -9,13 +9,7 @@
import transformers
try:
- from opendelta import (
- AdapterModel,
- BitFitModel,
- LoraModel,
- PrefixModel,
- SoftPromptModel,
- )
+ from opendelta import AdapterModel, BitFitModel, LoraModel, PrefixModel, SoftPromptModel
HAS_OPENDELTA = True
except ModuleNotFoundError:
@@ -55,12 +49,7 @@ def freeze_bottom_seq2seq_layers(model: nn.Module, num_layers_unfrozen: int = 0)
decoder_norm_layer = model.decoder.final_layer_norm
decoder_blocks = model.decoder.block[:-num_layers_unfrozen]
blocks_to_freeze = (
- list(encoder_blocks)
- + list(decoder_blocks)
- + [shared_embed]
- + [encoder_norm_layer]
- + [decoder_norm_layer]
- + [decoder_embed]
+ list(encoder_blocks) + list(decoder_blocks) + [shared_embed] + [encoder_norm_layer] + [decoder_norm_layer] + [decoder_embed]
)
for block in blocks_to_freeze:
block.requires_grad_(False)
@@ -433,14 +422,11 @@ def parse_delta_kwargs(
if modified_modules in ["all", "attention", "mlp"]:
if config.model_type not in MODIFIED_MODULES_DICT:
raise ValueError(
- f"Model type `{config.model_type}` is not currently supported for "
- "delta training with default modified modules."
+ f"Model type `{config.model_type}` is not currently supported for " "delta training with default modified modules."
)
modified_modules = MODIFIED_MODULES_DICT[config.model_type][modified_modules]
# Update the `modified_modules` with the correct layer ranges
- delta_kwargs["modified_modules"] = get_delta_modified_modules(
- config, modified_modules, num_layers_unfrozen=num_layers_unfrozen
- )
+ delta_kwargs["modified_modules"] = get_delta_modified_modules(config, modified_modules, num_layers_unfrozen=num_layers_unfrozen)
return delta_type, delta_kwargs
diff --git a/tests/test_models.py b/tests/test_models.py
index 7924393a7..3c5ce5fdf 100644
--- a/tests/test_models.py
+++ b/tests/test_models.py
@@ -152,9 +152,7 @@ def _create_inputs(self, model_path):
tokenizer.pad_token = tokenizer.eos_token
tokenizer.padding_side = "left"
- encoder_inputs = tokenizer(
- self.encoder_text, truncation=True, padding="max_length", max_length=10, return_tensors="pt"
- )
+ encoder_inputs = tokenizer(self.encoder_text, truncation=True, padding="max_length", max_length=10, return_tensors="pt")
decoder_inputs = tokenizer(self.decoder_text, return_tensors="pt")
return {
**encoder_inputs,
@@ -326,9 +324,7 @@ def test_save_load(self):
# Assert loaded states are not the same as the original unmodified pretrained model
self.assertFalse(
- torch.all(
- torch.isclose(modified_model.ilql_heads.q_heads[0][0].bias, model.ilql_heads.q_heads[0][0].bias)
- )
+ torch.all(torch.isclose(modified_model.ilql_heads.q_heads[0][0].bias, model.ilql_heads.q_heads[0][0].bias))
)
def test_from_config(self):