Merge pull request #21 from lenianiva/experiments/dsp
experiment: DSP with GPT-4o and o1-preview
This commit is contained in:
Leni Aniva
GitHub
commit
bc512a6ae2
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@ -13,7 +13,7 @@ lake build
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```
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```
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Then run `main.py`
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Then run `main.py`
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``` sh
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``` sh
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python3 experiments/dsp/main.py -h
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python3 main.py -h
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```
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```
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The main command for running DSP is `eval`. Due to the multitude of data format
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The main command for running DSP is `eval`. Due to the multitude of data format
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@ -21,7 +21,19 @@ out there, use the `--format` flag to specify the data format. For example,
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running DSP on minif2f is:
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running DSP on minif2f is:
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``` sh
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``` sh
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python3 experiments/dsp/main.py eval --dataset ../minif2f/valid.jsonl --format minif2f
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python3 main.py eval \
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--dataset ../minif2f/valid.jsonl \
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--format minif2f \
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--output results-minif2f-valid
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```
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Then, use `plot.py` to generate the plots
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``` sh
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python3 plot.py \
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--result results-minif2f-{valid,test} \
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--names valid test \
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--plot-output output-plot
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```
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```
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## Related work
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## Related work
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@ -1,186 +0,0 @@
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examples_for_dsp_draft_prompt_original = [
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{"tag": "aimeI_2000_p7", "category": "algebra", "metadata": {}, "prompt": "Informal:\n(*### Problem\n\nSuppose that $x,$ $y,$ and $z$ are three positive numbers that satisfy the equations $xyz = 1,$ $x + \\frac {1}{z} = 5,$ and $y + \\frac {1}{x} = 29.$ Then $z + \\frac {1}{y} = \\frac {m}{n},$ where $m$ and $n$ are [[relatively prime]] positive integers. Find $m + n$. Show that it is 5.\n\n\nnote: this is the type of problem that makes you think symmetry, but actually can be solved easily with substitution, and other normal technniques\n\n### Solution\n\nWe can rewrite $xyz=1$ as $\\frac{1}{z}=xy$.\n\nSubstituting into one of the given equations, we have \n$x+xy=5$\n$x(1+y)=5$\n$\\frac{1}{x}=\\frac{1+y}{5}.$\n\nWe can substitute back into $y+\\frac{1}{x}=29$ to obtain\n$y+\\frac{1+y}{5}=29$\n$5y+1+y=145$\n$y=24.$\n\nWe can then substitute once again to get\n$x=\\frac15$\n$z=\\frac{5}{24}.$\nThus, $z+\\frac1y=\\frac{5}{24}+\\frac{1}{24}=\\frac{1}{4}$, so $m+n=005$.*)\n\nFormal:\ntheorem\n fixes x y z :: real\n and p :: rat\n assumes \"0 < x \\<and> 0 < y \\<and> 0 < z\"\n and \"x * y * z = 1\"\n and \"x + 1 / z = 5\"\n and \"y + 1 / x = 29\"\n and \"z + 1 / y = p\"\n and \"0 < p\" \n shows \"let (m,n) = quotient_of p in m + n = 5\"\nproof -\n (* We can rewrite $xyz=1$ as $\\frac{1}{z}=xy$. *)\n have c0: \"z = 1 / (x*y)\"\n sledgehammer\n (* Substituting into one of the given equations, we have \n $x+xy=5$\n $x(1+y)=5$\n $\\frac{1}{x}=\\frac{1+y}{5}.$ *)\n have c1: \"1 / x = (1+y) / 5\" \n proof -\n have \"x + x * y = 5\" using assms(3) unfolding c0\n sledgehammer\n then have \"x * (1 + y) = 5\"\n sledgehammer\n then have t1: \"x = 5 / (1+y)\"\n sledgehammer\n then show ?thesis\n sledgehammer\n qed\n (* We can substitute back into $y+\\frac{1}{x}=29$ to obtain\n $y+\\frac{1+y}{5}=29$\n $5y+1+y=145$\n $y=24.$ *)\n have \"y + (1+y)/5 = 29\" using assms(4) unfolding c1 sledgehammer\n then have \"5* (y + (1+y)/5) = 5 * 29\" sledgehammer\n also have \"... = 145\" sledgehammer\n finally have c2_1: \"5* (y + (1+y)/5) = 145\" sledgehammer\n have \"5* (y + (1+y)/5) = 5*y + (1+y)\" sledgehammer\n also have \"... = 6*y + 1\" sledgehammer\n finally have c2_2: \"5* (y + (1+y)/5) = 6*y + 1\" sledgehammer\n have \"6*y + 1 = 145\" using c2_1 c2_2 sledgehammer\n then have c2: \"y = 24\" sledgehammer\n (* We can then substitute once again to get\n $x=\\frac15$\n $z=\\frac{5}{24}.$ *)\n have \"1/x = 5\" using c1 unfolding c2 sledgehammer\n then have c3: \"x = 1/5\"\n sledgehammer\n then have c4: \"z = 5/24\"\n sledgehammer\n (* Thus, $z+\\frac1y=\\frac{5}{24}+\\frac{1}{24}=\\frac{1}{4}$, so $m+n=005$. *)\n have \"p = z + 1/y\" using assms(5) sledgehammer\n also have \"... = 5/24 + 1/24\" unfolding c2 c4 sledgehammer\n also have \"... = 1/4\" sledgehammer\n finally have c5: \"p = 1/4\"\n sledgehammer\n have \"quotient_of p = (1, 4)\" unfolding c5 sledgehammer\n then show ?thesis sledgehammer\nqed"},
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{"tag": "algebra_2rootsintpoly_am10tap11eqasqpam110", "category": "algebra", "metadata": {}, "prompt": "Informal:\n(*### Problem\n\nShow that for any complex number a, $(a-10)(a+11) = a^2 + a - 110$.\n\n### Solution\n\nWe first expand all terms of the left hand side to get $a^2 - 10a + 11a - 10*11$.\nThis equals $a^2 + a - 10*11 = a^2 + a - 110$.*)\n\nFormal:\ntheorem\n fixes a :: complex\n shows \"(a-10) * (a+11) = a^2 + a -110\"\nproof -\n (* We first expand all terms of the left hand side to get $a^2 - 10a + 11a - 10*11$. *)\n have \"(a-10) * (a+11) = a^2 - 10*a + 11*a - 10 *11\"\n sledgehammer\n (* This equals $a^2 + a - 10*11 = a^2 + a - 110$. *)\n also have \"\\<dots> = a^2 + a - 10 * 11\"\n sledgehammer\n also have \"\\<dots> = a^2 + a - 110\"\n sledgehammer\n finally show ?thesis\n sledgehammer\nqed"},
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{"tag": "mathd_numbertheory_335", "category": "number_theory", "metadata": {}, "prompt": "Informal:\n(*### Problem\n\nWhen Rachel divides her favorite number by 7, she gets a remainder of 5. What will the remainder be if she multiplies her favorite number by 5 and then divides by 7? Show that it is 4.\n\n### Solution\n\nLet $n$ be Rachel's favorite number. \nThen $n \\equiv 5 \\pmod{7}$, so $5n \\equiv 5 \\cdot 5 \\equiv 25 \\equiv 4 \\pmod{7}$.\n*)\n\nFormal:\ntheorem\n fixes n :: nat\n assumes h0 : \"n mod 7 = 5\"\n shows \"(5 * n) mod 7 = 4\"\nproof -\n (* Then $n \\equiv 5 \\pmod{7}$, so $5n \\equiv 5 \\cdot 5 \\equiv 25 \\equiv 4 \\pmod{7}$. *)\n have c0:\"(5 * n) mod 7 = (5 * 5) mod 7\" using h0\n sledgehammer\n then have \"\\<dots> = 4\" sledgehammer\n then have \"(5 * n) mod 7 = 4\" using c0 sledgehammer\n then show ?thesis sledgehammer\nqed"}
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]
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examples_for_dsp_draft_prompt_template = [
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{
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"tag": "aimeI_2000_p7",
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"category": "algebra",
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"metadata": {},
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"prompt": (
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"Informal:\n"
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"(*### Problem\n\n"
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"Suppose that $x,$ $y,$ and $z$ are three positive numbers that satisfy the equations $xyz = 1,$ "
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"$x + \\frac {1}{z} = 5,$ and $y + \\frac {1}{x} = 29.$ Then $z + \\frac {1}{y} = \\frac {m}{n},$ "
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"where $m$ and $n$ are [[relatively prime]] positive integers. Find $m + n$. Show that it is 5.\n\n"
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"note: this is the type of problem that makes you think symmetry, but actually can be solved easily "
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"with substitution, and other normal technniques\n\n"
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"### Solution\n\n"
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"We can rewrite $xyz=1$ as $\\frac{1}{z}=xy$.\n\n"
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"Substituting into one of the given equations, we have \n$x+xy=5$\n$x(1+y)=5$\n$\\frac{1}{x}=\\frac{1+y}{5}.$\n\n"
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"We can substitute back into $y+\\frac{1}{x}=29$ to obtain\n"
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"$y+\\frac{1+y}{5}=29$\n$5y+1+y=145$\n$y=24.$\n\n"
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"We can then substitute once again to get\n$x=\\frac15$\n$z=\\frac{5}{24}.$\n"
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"Thus, $z+\\frac1y=\\frac{5}{24}+\\frac{1}{24}=\\frac{1}{4}$, so $m+n=005$.*)\n\n"
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"Formal:\n"
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"theorem\n"
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" fixes x y z :: real\n"
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" and p :: rat\n"
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" assumes \"0 < x \\<and> 0 < y \\<and> 0 < z\"\n"
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" and \"x * y * z = 1\"\n"
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" and \"x + 1 / z = 5\"\n"
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" and \"y + 1 / x = 29\"\n"
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" and \"z + 1 / y = p\"\n"
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" and \"0 < p\" \n"
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" shows \"let (m,n) = quotient_of p in m + n = 5\"\n"
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"proof -\n"
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" (* We can rewrite $xyz=1$ as $\\frac{1}{z}=xy$. *)\n"
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" have c0: \"z = 1 / (x*y)\"\n"
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" sledgehammer\n"
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" (* Substituting into one of the given equations, we have \n"
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" $x+xy=5$\n"
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" $x(1+y)=5$\n"
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" $\\frac{1}{x}=\\frac{1+y}{5}.$ *)\n"
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" have c1: \"1 / x = (1+y) / 5\" \n"
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" proof -\n"
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" have \"x + x * y = 5\" using assms(3) unfolding c0\n"
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" sledgehammer\n"
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" then have \"x * (1 + y) = 5\"\n"
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" sledgehammer\n"
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" then have t1: \"x = 5 / (1+y)\"\n"
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" sledgehammer\n"
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" then show ?thesis\n"
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" sledgehammer\n"
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" qed\n"
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" (* We can substitute back into $y+\\frac{1}{x}=29$ to obtain\n"
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" $y+\\frac{1+y}{5}=29$\n"
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" $5y+1+y=145$\n"
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" $y=24.$ *)\n"
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" have \"y + (1+y)/5 = 29\" using assms(4) unfolding c1 sledgehammer\n"
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" then have \"5* (y + (1+y)/5) = 5 * 29\" sledgehammer\n"
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" also have \"... = 145\" sledgehammer\n"
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" finally have c2_1: \"5* (y + (1+y)/5) = 145\" sledgehammer\n"
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" have \"5* (y + (1+y)/5) = 5*y + (1+y)\" sledgehammer\n"
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" also have \"... = 6*y + 1\" sledgehammer\n"
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" finally have c2_2: \"5* (y + (1+y)/5) = 6*y + 1\" sledgehammer\n"
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" have \"6*y + 1 = 145\" using c2_1 c2_2 sledgehammer\n"
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" then have c2: \"y = 24\" sledgehammer\n"
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" (* We can then substitute once again to get\n"
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" $x=\\frac15$\n"
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" $z=\\frac{5}{24}.$ *)\n"
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" have \"1/x = 5\" using c1 unfolding c2 sledgehammer\n"
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" then have c3: \"x = 1/5\"\n"
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" sledgehammer\n"
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" then have c4: \"z = 5/24\"\n"
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" sledgehammer\n"
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" (* Thus, $z+\\frac1y=\\frac{5}{24}+\\frac{1}{24}=\\frac{1}{4}$, so $m+n=005$. *)\n"
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" have \"p = z + 1/y\" using assms(5) sledgehammer\n"
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" also have \"... = 5/24 + 1/24\" unfolding c2 c4 sledgehammer\n"
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" also have \"... = 1/4\" sledgehammer\n"
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" finally have c5: \"p = 1/4\"\n"
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" sledgehammer\n"
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" have \"quotient_of p = (1, 4)\" unfolding c5 sledgehammer\n"
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" then show ?thesis sledgehammer\n"
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"qed"
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),
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},
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{
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"tag": "algebra_2rootsintpoly_am10tap11eqasqpam110",
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"category": "algebra",
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"metadata": {},
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"prompt": (
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"Informal:\n"
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"(*### Problem\n\n"
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"Show that for any complex number a, $(a-10)(a+11) = a^2 + a - 110$.\n\n"
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"### Solution\n\n"
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"We first expand all terms of the left hand side to get $a^2 - 10a + 11a - 10*11$.\n"
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"This equals $a^2 + a - 10*11 = a^2 + a - 110$.*)\n\n"
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"Formal:\n"
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"theorem\n"
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" fixes a :: complex\n"
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" shows \"(a-10) * (a+11) = a^2 + a -110\"\n"
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"proof -\n"
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" (* We first expand all terms of the left hand side to get $a^2 - 10a + 11a - 10*11$. *)\n"
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" have \"(a-10) * (a+11) = a^2 - 10*a + 11*a - 10 *11\"\n"
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" sledgehammer\n"
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" (* This equals $a^2 + a - 10*11 = a^2 + a - 110$. *)\n"
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" also have \"\\<dots> = a^2 + a - 10 * 11\"\n"
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" sledgehammer\n"
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" also have \"\\<dots> = a^2 + a - 110\"\n"
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" sledgehammer\n"
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" finally show ?thesis\n"
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" sledgehammer\n"
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"qed"
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),
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},
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{
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"tag": "mathd_numbertheory_335",
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"category": "number_theory",
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"metadata": {},
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"prompt": (
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"Informal:\n"
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"(*### Problem\n\n"
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"When Rachel divides her favorite number by 7, she gets a remainder of 5. What will the remainder be if she "
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"multiplies her favorite number by 5 and then divides by 7? Show that it is 4.\n\n"
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"### Solution\n\n"
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"Let $n$ be Rachel's favorite number. \n"
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"Then $n \\equiv 5 \\pmod{7}$, so $5n \\equiv 5 \\cdot 5 \\equiv 25 \\equiv 4 \\pmod{7}$.\n*)\n\n"
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"Formal:\n"
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"theorem\n"
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" fixes n :: nat\n"
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" assumes h0 : \"n mod 7 = 5\"\n"
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" shows \"(5 * n) mod 7 = 4\"\n"
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"proof -\n"
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" (* Then $n \\equiv 5 \\pmod{7}$, so $5n \\equiv 5 \\cdot 5 \\equiv 25 \\equiv 4 \\pmod{7}$. *)\n"
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" have c0:\"(5 * n) mod 7 = (5 * 5) mod 7\" using h0\n"
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" sledgehammer\n"
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" then have \"\\<dots> = 4\" sledgehammer\n"
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" then have \"(5 * n) mod 7 = 4\" using c0 sledgehammer\n"
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" then show ?thesis sledgehammer\n"
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"qed"
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),
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}
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]
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# -- Prompts for generating (informal) drafts (basically informal/natural language solution strings, that contain less details than a formal proof, hence why they are called "drafts")
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prompt_draft_template_4_isabelle = """Draft an informal solution similar to the one below.
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The informal solution will be used to sketch a formal Isabelle proof.
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Here are some examples: \n"""
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for example in examples_for_dsp_draft_prompt_template:
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# P_draft_isa_prompt_template += ("Example:\n" + x['prompt'][:x['prompt'].find('Formal:')] + "\n\n")
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# - Extract the 'prompt' field from the current example
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prompt_text = example['prompt']
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# - Find the index where the 'Formal:' keyword starts
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formal_index = prompt_text.find('Formal:')
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# - Extract the part of the prompt before the 'Formal:' keyword
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nl_prob_soln = prompt_text[:formal_index] # Append nl/i draft examples: prob_nl, soln_nl/draft_nl
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# - Append this i draft example our prompt draft/P_draft
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prompt_draft_template_4_isabelle += f"Example:\n{informal_part}\n\n"
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# append the final part of the prompt template that prompts model to do prediction, we'd need to insert new nl problem text here before using it
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prompt_draft_template_4_isabelle += """Informal:
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(*### Problem
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"""
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# P_sketch isabelle, ref: https://github.com/brando90/ntptutorial-II/blob/main/partII_dsp/notebooks/II_dsp__part2_dsp.ipynb
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prompt = """Translate the informal solution into a sketch of the
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formal Isabelle proof. Add `sledgehammer` in the sketch whenever
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possible. `sledgehammer` will be used to call the automated Sledgehammer prover.
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Here are some examples:
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"""
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for x in examples:
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prompt += (x['prompt'] + "\n\n")
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prompt += """Informal:
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(*### Problem
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"""
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xf = """theorem
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fixes x :: int
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assumes h0: "even x"
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shows "odd (x+5)" """
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zi = p.f(prompt, xi + '\n\n' + yi + '\n\n' + xf)
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print(zi)
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@ -1,12 +1,13 @@
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import sys, os, json, subprocess
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import sys, os, json, subprocess, time, datetime
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from dataclasses import dataclass
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from pathlib import Path
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from pathlib import Path
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from typing import Union, Any, Tuple
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from dataclasses import asdict
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from typing import Union, Any, Tuple, Optional
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from tqdm import tqdm
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from tqdm import tqdm
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from openai import OpenAI
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from openai import OpenAI
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import wandb
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import wandb
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from tenacity import retry, stop_after_attempt, wait_exponential
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from tenacity import retry, stop_after_attempt, wait_exponential
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from pantograph import Server
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from pantograph import Server, ServerError, DEFAULT_CORE_OPTIONS
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from pantograph.search import SearchResult
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from termcolor import colored
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from termcolor import colored
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from solve.prompts import (
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from solve.prompts import (
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@ -20,17 +21,16 @@ from solve.prompts import (
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get_prompt_sketch_template_4_lean_v0,
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get_prompt_sketch_template_4_lean_v0,
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)
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)
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from solve.prove import HammerAgent
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from solve.prove import HammerAgent
|
||||||
from solve.data import Datum
|
from solve.data import (
|
||||||
|
Datum,
|
||||||
|
SamplingParams,
|
||||||
|
SketchParseFailure,
|
||||||
|
SearchFailure,
|
||||||
|
DatumResult,
|
||||||
|
)
|
||||||
|
|
||||||
# prompt_draft_template_lean4_v0 = "Draft an informal solution similar to the one below. The informal solution will be used to sketch a formal proof in the Lean 4 Proof Assistant. Here are some examples of informal problem solutions pairs:\n\nInformal:\n(*### Problem\n\nProve that for any natural number n, n + 0 = n.\n\n### Solution\n\nConsider any natural number n. From properties of addition, adding zero does not change its values. Thus, n + 0 = n.*)\n\nInformal:\n(*### Problem\n\nProve that for any natural number n, n + (m + 1) = (n + m) + 1.\n\n### Solution\n\nConsider any natural numbers n and m. From properties of addition, adding 1 to the sum of n and m is the same as first adding m to n and then adding 1. Thus, n + (m + 1) = (n + m) + 1.*)\n\nInformal:\n(*### Problem\n\nProve that for any natural number n and m, n + m = m + n.\n\n### Solution\n\nConsider any natural numbers n and m. We will do induction on n. Base case: 0 + m = m + 0 by properties of addition. Inductive step, we have n + m = m + n. Then (n + 1) + m = (n + m) + 1 = (m + n) + 1 = m + (n + 1). Thus, by induction, n + m = m + n, qed.*)\n\nInformal: \n(*### Problem\n\n{nl_problem}\n\n### Solution\n"
|
# prompt_draft_template_lean4_v0 = "Draft an informal solution similar to the one below. The informal solution will be used to sketch a formal proof in the Lean 4 Proof Assistant. Here are some examples of informal problem solutions pairs:\n\nInformal:\n(*### Problem\n\nProve that for any natural number n, n + 0 = n.\n\n### Solution\n\nConsider any natural number n. From properties of addition, adding zero does not change its values. Thus, n + 0 = n.*)\n\nInformal:\n(*### Problem\n\nProve that for any natural number n, n + (m + 1) = (n + m) + 1.\n\n### Solution\n\nConsider any natural numbers n and m. From properties of addition, adding 1 to the sum of n and m is the same as first adding m to n and then adding 1. Thus, n + (m + 1) = (n + m) + 1.*)\n\nInformal:\n(*### Problem\n\nProve that for any natural number n and m, n + m = m + n.\n\n### Solution\n\nConsider any natural numbers n and m. We will do induction on n. Base case: 0 + m = m + 0 by properties of addition. Inductive step, we have n + m = m + n. Then (n + 1) + m = (n + m) + 1 = (m + n) + 1 = m + (n + 1). Thus, by induction, n + m = m + n, qed.*)\n\nInformal: \n(*### Problem\n\n{nl_problem}\n\n### Solution\n"
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class SamplingParams:
|
|
||||||
n: int
|
|
||||||
max_tokens: int
|
|
||||||
top_p: int
|
|
||||||
temperature: float
|
|
||||||
stop: str
|
|
||||||
|
|
||||||
class Engine:
|
class Engine:
|
||||||
def __init__(self):
|
def __init__(self):
|
||||||
|
|
@ -64,7 +64,7 @@ class OpenAI_DSP_Engine(Engine):
|
||||||
print(f'{base_url=}') if verbose_init else None
|
print(f'{base_url=}') if verbose_init else None
|
||||||
|
|
||||||
|
|
||||||
if not ('gpt-4-' in model or 'gpt-3.5-' in model or 'gpt-4o' in model):
|
if not ('gpt-4-' in model or 'gpt-3.5-' in model or 'gpt-4o' in model or model == "o1-preview"):
|
||||||
raise ValueError(f"Model {model=} not supported.")
|
raise ValueError(f"Model {model=} not supported.")
|
||||||
self.model = model
|
self.model = model
|
||||||
self.api_key = api_key
|
self.api_key = api_key
|
||||||
|
|
@ -82,6 +82,41 @@ class OpenAI_DSP_Engine(Engine):
|
||||||
# Prove params
|
# Prove params
|
||||||
# ...TODO not sure if needed right now...
|
# ...TODO not sure if needed right now...
|
||||||
|
|
||||||
|
@property
|
||||||
|
def role_prompt(self) -> str:
|
||||||
|
return "assistant" if self.model.startswith("o1") else "system"
|
||||||
|
|
||||||
|
def sample_draft(self, prompt: str):
|
||||||
|
extra = {} if self.model.startswith("o1") else dict(
|
||||||
|
temperature=self.draft_sampling_params.temperature,
|
||||||
|
top_p=self.draft_sampling_params.top_p,
|
||||||
|
stop=self.draft_sampling_params.stop[:3],
|
||||||
|
)
|
||||||
|
return self.llm.chat.completions.create(
|
||||||
|
model=self.model,
|
||||||
|
messages=[
|
||||||
|
{"role": self.role_prompt, "content": self.draft_system_prompt},
|
||||||
|
{"role": "user", "content": prompt},
|
||||||
|
],
|
||||||
|
n=self.draft_sampling_params.n,
|
||||||
|
**extra,
|
||||||
|
)
|
||||||
|
def sample_sketch(self, prompt: str):
|
||||||
|
extra = {} if self.model.startswith("o1") else dict(
|
||||||
|
temperature=self.sketch_sampling_params.temperature,
|
||||||
|
top_p=self.sketch_sampling_params.top_p,
|
||||||
|
)
|
||||||
|
return self.llm.chat.completions.create(
|
||||||
|
model=self.model,
|
||||||
|
messages=[
|
||||||
|
{"role": self.role_prompt, "content": self.sketch_system_prompt},
|
||||||
|
{"role": "user", "content": prompt},
|
||||||
|
],
|
||||||
|
n=self.sketch_sampling_params.n,
|
||||||
|
**extra,
|
||||||
|
# stop=eng.sketch_sampling_params.stop[:3],
|
||||||
|
)
|
||||||
|
|
||||||
@retry(stop=stop_after_attempt(15), wait=wait_exponential(multiplier=2, max=128))
|
@retry(stop=stop_after_attempt(15), wait=wait_exponential(multiplier=2, max=128))
|
||||||
def autoformalize_prob(
|
def autoformalize_prob(
|
||||||
eng: Engine,
|
eng: Engine,
|
||||||
|
|
@ -91,8 +126,8 @@ def autoformalize_prob(
|
||||||
""" Autoformalize natural language problem to formal language problem. """
|
""" Autoformalize natural language problem to formal language problem. """
|
||||||
pass
|
pass
|
||||||
|
|
||||||
@retry(stop=stop_after_attempt(15), wait=wait_exponential(multiplier=2, max=128))
|
#@retry(stop=stop_after_attempt(15), wait=wait_exponential(multiplier=2, max=128))
|
||||||
def draft(
|
def step_draft(
|
||||||
eng: Engine,
|
eng: Engine,
|
||||||
datum: Datum,
|
datum: Datum,
|
||||||
verbose: bool = False,
|
verbose: bool = False,
|
||||||
|
|
@ -106,17 +141,7 @@ def draft(
|
||||||
prompt = eng.draft_prompt_template.replace('{nl_problem}', nl_problem)
|
prompt = eng.draft_prompt_template.replace('{nl_problem}', nl_problem)
|
||||||
# Get all **completions** to single prompt, one (in) -> many (out)
|
# Get all **completions** to single prompt, one (in) -> many (out)
|
||||||
# ref: https://platform.openai.com/docs/api-reference/chat/object
|
# ref: https://platform.openai.com/docs/api-reference/chat/object
|
||||||
response: Any = eng.llm.chat.completions.create(
|
response: Any = eng.sample_draft(prompt)
|
||||||
model=eng.model,
|
|
||||||
messages=[
|
|
||||||
{"role": "system", "content": eng.draft_system_prompt},
|
|
||||||
{"role": "user", "content": prompt},
|
|
||||||
],
|
|
||||||
temperature=eng.draft_sampling_params.temperature,
|
|
||||||
top_p=eng.draft_sampling_params.top_p,
|
|
||||||
n=eng.draft_sampling_params.n,
|
|
||||||
stop=eng.draft_sampling_params.stop[:3],
|
|
||||||
)
|
|
||||||
# Get all completions for single prompt
|
# Get all completions for single prompt
|
||||||
completions: list[str] = [
|
completions: list[str] = [
|
||||||
completion.message.content
|
completion.message.content
|
||||||
|
|
@ -125,8 +150,8 @@ def draft(
|
||||||
drafts: list[str] = completions
|
drafts: list[str] = completions
|
||||||
return drafts
|
return drafts
|
||||||
|
|
||||||
@retry(stop=stop_after_attempt(15), wait=wait_exponential(multiplier=2, max=128))
|
#@retry(stop=stop_after_attempt(15), wait=wait_exponential(multiplier=2, max=128))
|
||||||
def sketch(
|
def step_sketch(
|
||||||
eng: Engine,
|
eng: Engine,
|
||||||
datum: Datum,
|
datum: Datum,
|
||||||
drafts: list[str],
|
drafts: list[str],
|
||||||
|
|
@ -149,29 +174,19 @@ def sketch(
|
||||||
x_fl_problem = datum.fl_problem if datum.fl_problem else autoformalize_prob(eng, datum)
|
x_fl_problem = datum.fl_problem if datum.fl_problem else autoformalize_prob(eng, datum)
|
||||||
prompt = eng.sketch_prompt_template.replace('{fl_problem}', x_nl_problem).replace('{fl_problem}', y_nl_solution)
|
prompt = eng.sketch_prompt_template.replace('{fl_problem}', x_nl_problem).replace('{fl_problem}', y_nl_solution)
|
||||||
# Get all **completions** to single prompt, one (in) -> many (out), ref: https://platform.openai.com/docs/api-reference/chat/object
|
# Get all **completions** to single prompt, one (in) -> many (out), ref: https://platform.openai.com/docs/api-reference/chat/object
|
||||||
response: Any = eng.llm.chat.completions.create(
|
response: Any = eng.sample_sketch(prompt)
|
||||||
model=eng.model,
|
|
||||||
messages=[
|
|
||||||
{"role": "system", "content": eng.sketch_system_prompt},
|
|
||||||
{"role": "user", "content": prompt},
|
|
||||||
],
|
|
||||||
temperature=eng.sketch_sampling_params.temperature,
|
|
||||||
top_p=eng.sketch_sampling_params.top_p,
|
|
||||||
n=eng.sketch_sampling_params.n,
|
|
||||||
# stop=eng.sketch_sampling_params.stop[:3],
|
|
||||||
)
|
|
||||||
# Get all completions for single prompt
|
# Get all completions for single prompt
|
||||||
completions: list[str] = [completion.message.content for completion in response.choices] # response.choices[i].message
|
completions: list[str] = [completion.message.content for completion in response.choices] # response.choices[i].message
|
||||||
sketches: list[str] = completions
|
sketches: list[str] = completions
|
||||||
# Return
|
# Return
|
||||||
return sketches, x_fl_problem
|
return sketches, x_fl_problem
|
||||||
|
|
||||||
def prove(
|
def step_prove(
|
||||||
eng: Engine,
|
eng: Engine,
|
||||||
server: Server,
|
server: Server,
|
||||||
fl_prob: str,
|
fl_prob: str,
|
||||||
fl_sketch: list[str],
|
fl_sketch: str,
|
||||||
):
|
) -> Union[SketchParseFailure, SearchFailure, SearchResult]:
|
||||||
"""
|
"""
|
||||||
|
|
||||||
Complete formal sketch and check if it proves the theorem.
|
Complete formal sketch and check if it proves the theorem.
|
||||||
|
|
@ -182,63 +197,135 @@ def prove(
|
||||||
"""
|
"""
|
||||||
# If this throws index out of bound errors it means the source doesn't contain walled off Lean sections.
|
# If this throws index out of bound errors it means the source doesn't contain walled off Lean sections.
|
||||||
print(colored("Sketch:", "yellow"), fl_sketch)
|
print(colored("Sketch:", "yellow"), fl_sketch)
|
||||||
lean_code, = [extract_lean_code(sketch)[0] for sketch in fl_sketch]
|
lean_code = "\n".join(extract_lean_code(fl_sketch))
|
||||||
print(colored("Lean code:", "light_grey"), lean_code)
|
print(colored("Lean code:", "light_grey", attrs=["bold"]), lean_code)
|
||||||
|
|
||||||
|
try:
|
||||||
states = server.load_sorry(lean_code)
|
states = server.load_sorry(lean_code)
|
||||||
|
except ServerError as e:
|
||||||
|
msg = f"Encountered exception: {e}"
|
||||||
|
print(colored(msg, "red"))
|
||||||
|
return SketchParseFailure(
|
||||||
|
sketch=fl_sketch,
|
||||||
|
error=msg,
|
||||||
|
)
|
||||||
|
|
||||||
if len(states) != 1:
|
if len(states) != 1:
|
||||||
print(colored("Model must output one compilation unit", "red"))
|
print(colored("Model must output one compilation unit", "red"))
|
||||||
raise NotImplemented
|
return SketchParseFailure(
|
||||||
|
sketch=fl_sketch,
|
||||||
|
error="Model must output one compilation unit",
|
||||||
|
)
|
||||||
|
|
||||||
state = states[0]
|
state = states[0]
|
||||||
|
|
||||||
if isinstance(state, list) and len(state) > 0:
|
if isinstance(state, list) and len(state) > 0:
|
||||||
print(colored("Sketch failed:", "red"), "\n".join(state))
|
# This means `state` contains error messages
|
||||||
# what should we do?
|
msg = "\n".join(state)
|
||||||
raise NotImplemented
|
print(colored("Sketch failed:", "red"), msg)
|
||||||
|
return SketchParseFailure(
|
||||||
|
sketch=fl_sketch,
|
||||||
|
error=f"Sketch failed: {msg}",
|
||||||
|
)
|
||||||
|
|
||||||
agent = HammerAgent()
|
agent = HammerAgent()
|
||||||
result = agent.search(server, state)
|
try:
|
||||||
|
result = agent.search(
|
||||||
|
server,
|
||||||
|
state,
|
||||||
|
max_steps=1000,
|
||||||
|
max_trials_per_goal=len(agent.tactics) + 1,
|
||||||
|
)
|
||||||
print(colored(f"Result: {result}", "blue"))
|
print(colored(f"Result: {result}", "blue"))
|
||||||
|
|
||||||
return result
|
return result
|
||||||
|
except Exception as e:
|
||||||
|
return SearchFailure(
|
||||||
|
error=f"Server threw exception",
|
||||||
|
sketch=fl_sketch,
|
||||||
|
message=str(e),
|
||||||
|
)
|
||||||
|
|
||||||
# -- DSP for Lean
|
# -- DSP for Lean
|
||||||
|
|
||||||
def single_proof_search_dsp_lean(
|
def single_proof_search_dsp_lean(
|
||||||
eng: Engine,
|
eng: Engine,
|
||||||
server: Server,
|
server_func,
|
||||||
datum: Datum,
|
datum: Datum,
|
||||||
) -> bool:
|
) -> DatumResult:
|
||||||
|
|
||||||
|
start_time = time.time()
|
||||||
# -- Draft: [y_nl_pred_draft]_n ~ draft(eng, x_nl_prob, P_draft)
|
# -- Draft: [y_nl_pred_draft]_n ~ draft(eng, x_nl_prob, P_draft)
|
||||||
y_nl_pred_drafts = draft(eng, datum)
|
y_nl_pred_drafts = step_draft(eng, datum)
|
||||||
|
|
||||||
# -- Sketch: z_fl_pred_sketch ~ sketch(eng, x_nl_prob, [y_nl_pred_draft]_n, x_fl_prob, P_sketch)
|
# -- Sketch: z_fl_pred_sketch ~ sketch(eng, x_nl_prob, [y_nl_pred_draft]_n, x_fl_prob, P_sketch)
|
||||||
z_fl_pred_sketches, x_fl_prob = sketch(eng, datum, y_nl_pred_drafts)
|
z_fl_pred_sketches, x_fl_prob = step_sketch(eng, datum, y_nl_pred_drafts)
|
||||||
|
|
||||||
|
assert len(z_fl_pred_sketches) == eng.sketch_sampling_params.n
|
||||||
|
|
||||||
|
|
||||||
|
results = []
|
||||||
|
success = False
|
||||||
|
for i_sketch, sketch in enumerate(z_fl_pred_sketches):
|
||||||
|
if len(z_fl_pred_sketches):
|
||||||
|
print(colored(f"Sketch {1+i_sketch}/{len(z_fl_pred_sketches)}", attrs=["bold", "underline"]))
|
||||||
|
|
||||||
|
try:
|
||||||
|
server = server_func()
|
||||||
|
except Exception as e:
|
||||||
|
print(colored("Failed to create server: {e}", "red"))
|
||||||
|
return DatumResult(
|
||||||
|
name=str(datum),
|
||||||
|
error=str(e),
|
||||||
|
)
|
||||||
# -- Prove: y_fl = prove(eng, x_fl_prob, z_fl_pred_sketches)
|
# -- Prove: y_fl = prove(eng, x_fl_prob, z_fl_pred_sketches)
|
||||||
result: bool = prove(eng, server, x_fl_prob, z_fl_pred_sketches)
|
prove_result = step_prove(eng, server, x_fl_prob, sketch)
|
||||||
|
results.append(prove_result)
|
||||||
|
if isinstance(prove_result, SearchResult) and prove_result.success:
|
||||||
|
success = True
|
||||||
|
break
|
||||||
|
duration = time.time() - start_time
|
||||||
|
|
||||||
# -- Return
|
return DatumResult(
|
||||||
return result
|
name=str(datum),
|
||||||
|
success=success,
|
||||||
|
proves=results,
|
||||||
|
duration=duration,
|
||||||
|
)
|
||||||
|
|
||||||
def full_proof_search_dsp_lean(
|
def full_proof_search_dsp_lean(
|
||||||
eng: Engine,
|
eng: Engine,
|
||||||
server: Server,
|
server_func,
|
||||||
data: list[Datum],
|
data: list[Datum],
|
||||||
path_output: Path,
|
path_output: Path,
|
||||||
):
|
):
|
||||||
print(colored(f"DSP on {len(data)} points", "blue", attrs=["bold", "underline"]))
|
n_success = 0
|
||||||
|
n_tried = 0
|
||||||
# -- Proof search by DSP over all eval data
|
# -- Proof search by DSP over all eval data
|
||||||
for i, datum in tqdm(enumerate(data), total=len(data), desc='DSP proof loop per data point in benchmark.'):
|
for i, datum in tqdm(enumerate(data), total=len(data), desc='DSP proof loop per data point in benchmark.'):
|
||||||
print(f"Problem {i}:", colored(str(datum), "cyan"))
|
output_path = path_output / f"{i:03}.json"
|
||||||
result = single_proof_search_dsp_lean(eng, server, datum)
|
key = str(datum)
|
||||||
file_name = path_output / f"{i:03}.json"
|
# Detect if file exists
|
||||||
with open(file_name, 'w') as f:
|
if output_path.is_file():
|
||||||
json.dump({ 'name': str(datum), 'success': result.success, 'steps': result.steps }, f)
|
obj = json.load(open(output_path, "r"))
|
||||||
#server.gc()
|
if obj['name'] != key:
|
||||||
|
print(colored(f"Existing datum name {obj['name']} does not match dataset {key}. The output directory may be wrong"))
|
||||||
return
|
return
|
||||||
|
|
||||||
|
print(f"Skipped {output_path.name}:", colored(key, "green"))
|
||||||
|
continue
|
||||||
|
|
||||||
|
n_tried += 1
|
||||||
|
print(f"Problem {output_path.name}:", colored(key, "cyan"))
|
||||||
|
|
||||||
|
result = single_proof_search_dsp_lean(eng, server_func, datum)
|
||||||
|
with open(output_path, 'w') as f:
|
||||||
|
json.dump(asdict(result), f)
|
||||||
|
if result.success:
|
||||||
|
n_success += 1
|
||||||
|
#server.gc()
|
||||||
|
print(f"Proved {n_success}/{n_tried} problems")
|
||||||
|
|
||||||
|
|
||||||
experiment_dir = Path(__file__).resolve().parent
|
experiment_dir = Path(__file__).resolve().parent
|
||||||
|
|
||||||
|
|
@ -269,7 +356,6 @@ def load_data(args) -> list[Datum]:
|
||||||
# -- Main
|
# -- Main
|
||||||
|
|
||||||
def main(args):
|
def main(args):
|
||||||
import time, datetime
|
|
||||||
start_time = time.time()
|
start_time = time.time()
|
||||||
|
|
||||||
# Setup paths and data
|
# Setup paths and data
|
||||||
|
|
@ -279,10 +365,12 @@ def main(args):
|
||||||
|
|
||||||
# Start server
|
# Start server
|
||||||
project_path, lean_path = get_project_and_lean_path()
|
project_path, lean_path = get_project_and_lean_path()
|
||||||
server = Server(
|
def server_func():
|
||||||
|
return Server(
|
||||||
imports=["Mathlib", "Aesop"],
|
imports=["Mathlib", "Aesop"],
|
||||||
project_path=project_path,
|
project_path=project_path,
|
||||||
lean_path=lean_path,
|
lean_path=lean_path,
|
||||||
|
core_options=DEFAULT_CORE_OPTIONS,
|
||||||
)
|
)
|
||||||
|
|
||||||
# - Start wandb run
|
# - Start wandb run
|
||||||
|
|
@ -300,7 +388,7 @@ def main(args):
|
||||||
# - Run DSP for Lean
|
# - Run DSP for Lean
|
||||||
api_key = os.environ['OPENAI_API_KEY']
|
api_key = os.environ['OPENAI_API_KEY']
|
||||||
draft_sampling_params = SamplingParams(
|
draft_sampling_params = SamplingParams(
|
||||||
n=args.n_samples,
|
n=1, #args.n_samples,
|
||||||
max_tokens=args.max_tokens,
|
max_tokens=args.max_tokens,
|
||||||
top_p=args.top_p,
|
top_p=args.top_p,
|
||||||
temperature=args.temperature,
|
temperature=args.temperature,
|
||||||
|
|
@ -321,8 +409,11 @@ def main(args):
|
||||||
sketch_sampling_params=sketch_sampling_params,
|
sketch_sampling_params=sketch_sampling_params,
|
||||||
)
|
)
|
||||||
|
|
||||||
|
print(colored(f"DSP on {len(data_eval)} points", "blue", attrs=["bold", "underline"]))
|
||||||
|
print(f"Draft={draft_sampling_params}")
|
||||||
|
print(f"Sketch={sketch_sampling_params}")
|
||||||
# - Full proof search with DSP
|
# - Full proof search with DSP
|
||||||
full_proof_search_dsp_lean(eng, server, data_eval, path_output)
|
full_proof_search_dsp_lean(eng, server_func, data_eval, path_output)
|
||||||
|
|
||||||
dt = datetime.timedelta(seconds=time.time() - start_time)
|
dt = datetime.timedelta(seconds=time.time() - start_time)
|
||||||
print(colored(f"Time elapsed: {dt}", "magenta"))
|
print(colored(f"Time elapsed: {dt}", "magenta"))
|
||||||
|
|
@ -332,6 +423,26 @@ def main(args):
|
||||||
# print(f"{wandb.config=}")
|
# print(f"{wandb.config=}")
|
||||||
# run.finish()
|
# run.finish()
|
||||||
|
|
||||||
|
def check(args):
|
||||||
|
path_output = Path(args.output)
|
||||||
|
data = load_data(args)
|
||||||
|
n_success = 0
|
||||||
|
n_tried = 0
|
||||||
|
for i, datum in tqdm(enumerate(data), total=len(data), desc='DSP proof loop per data point in benchmark.'):
|
||||||
|
file_name = path_output / f"{i:03}.json"
|
||||||
|
key = str(datum)
|
||||||
|
# Detect if file exists
|
||||||
|
obj = json.load(open(file_name, "r"))
|
||||||
|
if obj['name'] != key:
|
||||||
|
print(colored(f"Existing datum name {obj['name']} does not match dataset {key}. The output directory may be wrong", "red"))
|
||||||
|
return
|
||||||
|
|
||||||
|
n_tried += 1
|
||||||
|
if obj['success']:
|
||||||
|
n_success += 1
|
||||||
|
print(f"Proved {n_success}/{n_tried} problems")
|
||||||
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
if __name__ == "__main__":
|
||||||
import argparse
|
import argparse
|
||||||
|
|
||||||
|
|
@ -343,7 +454,7 @@ if __name__ == "__main__":
|
||||||
parser.add_argument(
|
parser.add_argument(
|
||||||
'mode',
|
'mode',
|
||||||
help="Function",
|
help="Function",
|
||||||
choices=['eval', 'prompts'],
|
choices=['prompts', 'eval', 'check'],
|
||||||
)
|
)
|
||||||
parser.add_argument(
|
parser.add_argument(
|
||||||
"--dataset",
|
"--dataset",
|
||||||
|
|
@ -359,7 +470,7 @@ if __name__ == "__main__":
|
||||||
"--model",
|
"--model",
|
||||||
help="Model",
|
help="Model",
|
||||||
default="gpt-4o",
|
default="gpt-4o",
|
||||||
choices=["gpt2", "gpt-3.5-turbo", "gpt-4o", "deepseek-ai/deepseek-math-7b-instruct"],
|
choices=["gpt2", "gpt-3.5-turbo", "gpt-4o", "deepseek-ai/deepseek-math-7b-instruct", "o1-preview"],
|
||||||
)
|
)
|
||||||
parser.add_argument(
|
parser.add_argument(
|
||||||
"--format",
|
"--format",
|
||||||
|
|
@ -369,18 +480,40 @@ if __name__ == "__main__":
|
||||||
)
|
)
|
||||||
parser.add_argument("--start", default=0)
|
parser.add_argument("--start", default=0)
|
||||||
parser.add_argument("--end", default=sys.maxsize)
|
parser.add_argument("--end", default=sys.maxsize)
|
||||||
parser.add_argument("--batchsize", default=10, help="putnam has 348")
|
parser.add_argument(
|
||||||
parser.add_argument("--n-samples", default=1, help="num seqs to return for given prompt")
|
"--batchsize",
|
||||||
parser.add_argument("--max-tokens", default=2048, help="Maximum number of tokens in one sample")
|
default=10, type=int,
|
||||||
parser.add_argument("--top-p", default=0.95, help="Sampling top p")
|
help="putnam has 348",
|
||||||
parser.add_argument("--temperature", default=0.8, help="Sampling temperature")
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--n-samples",
|
||||||
|
default=1, type=int,
|
||||||
|
help="Number of sketch samples for a draft",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--max-tokens",
|
||||||
|
default=2048, type=int,
|
||||||
|
help="Maximum number of tokens in one sample",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--top-p",
|
||||||
|
default=0.95, type=float,
|
||||||
|
help="Sampling top p via nucleus sampling",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--temperature",
|
||||||
|
default=0.8, type=float,
|
||||||
|
help="Sampling temperature",
|
||||||
|
)
|
||||||
parser.add_argument("--verbose", action='store_true')
|
parser.add_argument("--verbose", action='store_true')
|
||||||
args = parser.parse_args()
|
args = parser.parse_args()
|
||||||
|
|
||||||
if args.mode == "eval":
|
if args.mode == "prompts":
|
||||||
main(args)
|
|
||||||
elif args.mode == "prompts":
|
|
||||||
prompt = get_prompt_sketch_template_4_lean_v0(verbose=args.verbose)
|
prompt = get_prompt_sketch_template_4_lean_v0(verbose=args.verbose)
|
||||||
print(prompt)
|
print(prompt)
|
||||||
|
elif args.mode == "eval":
|
||||||
|
main(args)
|
||||||
|
elif args.mode == 'check':
|
||||||
|
check(args)
|
||||||
else:
|
else:
|
||||||
raise ValueError(f"Unknown mode: {args.mode}")
|
raise ValueError(f"Unknown mode: {args.mode}")
|
||||||
|
|
|
||||||
|
|
@ -0,0 +1,143 @@
|
||||||
|
import json
|
||||||
|
from pathlib import Path
|
||||||
|
from matplotlib import pyplot
|
||||||
|
from typing import Callable, Optional
|
||||||
|
from tqdm import tqdm
|
||||||
|
import seaborn
|
||||||
|
import pandas
|
||||||
|
from termcolor import colored
|
||||||
|
from solve.data import (
|
||||||
|
Datum,
|
||||||
|
SamplingParams,
|
||||||
|
SketchParseFailure,
|
||||||
|
SearchFailure,
|
||||||
|
DatumResult,
|
||||||
|
)
|
||||||
|
|
||||||
|
experiment_dir = Path(__file__).resolve().parent
|
||||||
|
|
||||||
|
def read_data(name: str, result_path: Path):
|
||||||
|
assert result_path.is_dir(), f"Result path is not a directory: {result_path}"
|
||||||
|
objs = [
|
||||||
|
DatumResult.parse(json.load(open(file_name, "r")))
|
||||||
|
for file_name in tqdm(result_path.glob("*"), desc="Reading results")
|
||||||
|
]
|
||||||
|
|
||||||
|
print(colored(f"{name}", attrs=["underline"]))
|
||||||
|
# Calculate the metrics
|
||||||
|
successes = sum(obj.success for obj in objs)
|
||||||
|
success_rate = successes / len(objs)
|
||||||
|
print(f"Success rate: {successes} / {len(objs)} = {success_rate:.3f}")
|
||||||
|
|
||||||
|
# Calculate hammer rates
|
||||||
|
hammer_invocations = [
|
||||||
|
obj.hammer_invocations
|
||||||
|
for obj in objs
|
||||||
|
if obj.hammer_invocations
|
||||||
|
]
|
||||||
|
if hammer_invocations:
|
||||||
|
avg_hammer_invocation = sum(hammer_invocations) / len(hammer_invocations)
|
||||||
|
print(f"Hammer invocations: {avg_hammer_invocation:.3f}")
|
||||||
|
else:
|
||||||
|
print("Hammer invocations cannot be calculated")
|
||||||
|
|
||||||
|
durations = [obj.duration for obj in objs if obj.duration and obj.duration > 0]
|
||||||
|
if durations:
|
||||||
|
avg_duration = sum(durations) / len(durations)
|
||||||
|
print(f"Durations: {avg_duration:.3f}")
|
||||||
|
else:
|
||||||
|
print("Durations cannot be calculated")
|
||||||
|
return objs
|
||||||
|
|
||||||
|
def differentiated_histogram(
|
||||||
|
path: Path,
|
||||||
|
data: dict[str, list[dict]],
|
||||||
|
key: str,
|
||||||
|
key_func: Callable[[DatumResult], Optional[float]],
|
||||||
|
xticks: list[float] = None,
|
||||||
|
**kwargs,
|
||||||
|
):
|
||||||
|
"""
|
||||||
|
Map objects using `key_func`, filtering o
|
||||||
|
"""
|
||||||
|
dfs = [
|
||||||
|
pandas.DataFrame({ 'name': name, key: [ key_func(obj) for obj in objs ]})
|
||||||
|
for name, objs in data.items()
|
||||||
|
]
|
||||||
|
df = pandas.concat(dfs).reset_index()
|
||||||
|
fig, ax = pyplot.subplots(figsize=(6,4))
|
||||||
|
seaborn.histplot(
|
||||||
|
df,
|
||||||
|
ax=ax,
|
||||||
|
x=key, hue="name",
|
||||||
|
multiple="stack",
|
||||||
|
**kwargs,
|
||||||
|
)
|
||||||
|
if xticks:
|
||||||
|
ax.set_xticks(xticks, labels=[str(t) for t in xticks])
|
||||||
|
fig.savefig(path, dpi=300)
|
||||||
|
|
||||||
|
|
||||||
|
def plot(args):
|
||||||
|
|
||||||
|
assert len(args.result) == len(args.names), "Names must have a 1-1 correspondence with results"
|
||||||
|
|
||||||
|
print(colored("Reading data ...", color="blue"))
|
||||||
|
data = {
|
||||||
|
name: read_data(name, Path(result_path))
|
||||||
|
for name, result_path in zip(args.names, args.result)
|
||||||
|
}
|
||||||
|
|
||||||
|
path_plot_output = Path(args.plot_output)
|
||||||
|
path_plot_output.mkdir(exist_ok=True, parents=True)
|
||||||
|
# Generate plots
|
||||||
|
differentiated_histogram(
|
||||||
|
path_plot_output / "hammer.jpg",
|
||||||
|
data,
|
||||||
|
key="Hammered Goals",
|
||||||
|
key_func=lambda obj: obj.hammer_invocations)
|
||||||
|
differentiated_histogram(
|
||||||
|
path_plot_output / "runtime.jpg",
|
||||||
|
data,
|
||||||
|
key="Runtime (s)",
|
||||||
|
key_func=lambda obj: obj.duration if obj.duration > 0.0 else None,
|
||||||
|
log_scale=True,
|
||||||
|
xticks=[5, 10, 20, 40, 80, 160, 320],
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
import argparse
|
||||||
|
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
prog='DSP Plot',
|
||||||
|
description="Generates plots for DSP",
|
||||||
|
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--result",
|
||||||
|
help="Result directory",
|
||||||
|
nargs="+",
|
||||||
|
default=experiment_dir / 'result',
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--names",
|
||||||
|
help="Experiment names",
|
||||||
|
nargs="+",
|
||||||
|
default=["unnamed"],
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--plot-output",
|
||||||
|
help="Plot generation directory",
|
||||||
|
default=experiment_dir / 'result-plot',
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--palette",
|
||||||
|
help="Colour palette",
|
||||||
|
default="Paired",
|
||||||
|
)
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
seaborn.set_palette(args.palette)
|
||||||
|
|
||||||
|
plot(args)
|
||||||
|
|
@ -1,6 +1,6 @@
|
||||||
import json
|
|
||||||
from typing import Union, Optional
|
from typing import Union, Optional
|
||||||
from dataclasses import dataclass
|
from dataclasses import dataclass, field
|
||||||
|
from pantograph.search import SearchResult
|
||||||
|
|
||||||
@dataclass
|
@dataclass
|
||||||
class Datum:
|
class Datum:
|
||||||
|
|
@ -68,3 +68,67 @@ class Datum:
|
||||||
return Datum.load_minif2f(obj)
|
return Datum.load_minif2f(obj)
|
||||||
else:
|
else:
|
||||||
raise ValueError(f"Invalid data format {data_format}")
|
raise ValueError(f"Invalid data format {data_format}")
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class SamplingParams:
|
||||||
|
n: int
|
||||||
|
max_tokens: int
|
||||||
|
top_p: int
|
||||||
|
temperature: float
|
||||||
|
stop: str
|
||||||
|
|
||||||
|
@dataclass(frozen=True)
|
||||||
|
class SketchParseFailure:
|
||||||
|
error: str
|
||||||
|
sketch: str
|
||||||
|
@dataclass(frozen=True)
|
||||||
|
class SearchFailure:
|
||||||
|
error: str
|
||||||
|
sketch: str
|
||||||
|
message: str
|
||||||
|
|
||||||
|
@dataclass(frozen=True)
|
||||||
|
class DatumResult:
|
||||||
|
"""
|
||||||
|
Result from one DSP data point
|
||||||
|
"""
|
||||||
|
name: str
|
||||||
|
error: Optional[str] = None
|
||||||
|
duration: float = -1.0
|
||||||
|
success: Optional[bool] = False
|
||||||
|
proves: list[Union[SearchResult, SearchFailure, SketchParseFailure]] = field(default_factory=list)
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def parse_result(obj: dict):
|
||||||
|
if "message" in obj:
|
||||||
|
return SearchFailure(**obj)
|
||||||
|
|
||||||
|
if "error" in obj:
|
||||||
|
return SketchParseFailure(**obj)
|
||||||
|
|
||||||
|
return SearchResult(**obj)
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def parse(obj: dict):
|
||||||
|
return DatumResult(
|
||||||
|
name=obj['name'],
|
||||||
|
error=obj.get('error'),
|
||||||
|
duration=obj.get('duration'),
|
||||||
|
success=obj['success'],
|
||||||
|
proves=[DatumResult.parse_result(o) for o in obj['proves']]
|
||||||
|
)
|
||||||
|
|
||||||
|
@property
|
||||||
|
def hammer_invocations(self) -> Optional[float]:
|
||||||
|
"""
|
||||||
|
Average number of hammer invocations required
|
||||||
|
"""
|
||||||
|
li = [
|
||||||
|
sr.n_goals_root
|
||||||
|
for sr in self.proves
|
||||||
|
if isinstance(sr, SearchResult)
|
||||||
|
]
|
||||||
|
if not li:
|
||||||
|
return None
|
||||||
|
return sum(li)
|
||||||
|
|
|
||||||
|
|
@ -143,13 +143,21 @@ prompt_sketch_template_lean4_v0 = get_prompt_sketch_template_4_lean_v0()
|
||||||
|
|
||||||
WALL = "```"
|
WALL = "```"
|
||||||
|
|
||||||
|
def postprocess_lean(
|
||||||
|
code,
|
||||||
|
placeholder: str = TOKEN_PLACEHOLDER,
|
||||||
|
):
|
||||||
|
return code.replace("ℕ", "Nat").replace(placeholder, "sorry")
|
||||||
|
|
||||||
def extract_lean_code(
|
def extract_lean_code(
|
||||||
sketch: str,
|
sketch: str,
|
||||||
placeholder: str = TOKEN_PLACEHOLDER,
|
|
||||||
strip_imports: bool = True) -> list[str]:
|
strip_imports: bool = True) -> list[str]:
|
||||||
lines = sketch.split("\n")
|
lines = sketch.split("\n")
|
||||||
# find backtick markers ```
|
# find backtick markers ```
|
||||||
|
if WALL not in sketch:
|
||||||
|
# No walls found. The whole thing must be code
|
||||||
|
lines = [line for line in lines if not line.startswith("import ")]
|
||||||
|
return [postprocess_lean("\n".join(lines))]
|
||||||
lean_codes = []
|
lean_codes = []
|
||||||
curr = []
|
curr = []
|
||||||
is_walled = False
|
is_walled = False
|
||||||
|
|
@ -168,8 +176,7 @@ def extract_lean_code(
|
||||||
if is_walled_lean:
|
if is_walled_lean:
|
||||||
# found wall
|
# found wall
|
||||||
code = "\n".join(curr) + "\n"
|
code = "\n".join(curr) + "\n"
|
||||||
code = code.replace("ℕ", "Nat").replace(placeholder, "sorry")
|
lean_codes.append(postprocess_lean(code))
|
||||||
lean_codes.append(code)
|
|
||||||
curr = []
|
curr = []
|
||||||
is_walled = False
|
is_walled = False
|
||||||
is_walled_lean = False
|
is_walled_lean = False
|
||||||
|
|
@ -196,5 +203,12 @@ class TestPrompts(unittest.TestCase):
|
||||||
codes = extract_lean_code(sketch)
|
codes = extract_lean_code(sketch)
|
||||||
self.assertEqual(len(codes), 1)
|
self.assertEqual(len(codes), 1)
|
||||||
|
|
||||||
|
def test_extract_sketch_no_wall(self):
|
||||||
|
payload = f"example : forall (n: Prop), n -> n := {TOKEN_PLACEHOLDER}"
|
||||||
|
payload1 = f"\nexample : forall (n: Prop), n -> n := sorry"
|
||||||
|
sketch = f"import Mathlib\n\n{payload}"
|
||||||
|
codes = extract_lean_code(sketch)
|
||||||
|
self.assertEqual(codes, [payload1])
|
||||||
|
|
||||||
if __name__ == '__main__':
|
if __name__ == '__main__':
|
||||||
unittest.main()
|
unittest.main()
|
||||||
|
|
|
||||||
|
|
@ -28,3 +28,6 @@ class HammerAgent(Agent):
|
||||||
|
|
||||||
self.goal_tactic_id_map[key] = i + 1
|
self.goal_tactic_id_map[key] = i + 1
|
||||||
return self.tactics[i]
|
return self.tactics[i]
|
||||||
|
|
||||||
|
def reset(self):
|
||||||
|
self.goal_tactic_id_map = collections.defaultdict(lambda : 0)
|
||||||
|
|
|
||||||
|
|
@ -1 +1 @@
|
||||||
from pantograph.server import Server
|
from pantograph.server import Server, ServerError, DEFAULT_CORE_OPTIONS
|
||||||
|
|
|
||||||
|
|
@ -1,9 +1,10 @@
|
||||||
from abc import abstractmethod
|
from abc import abstractmethod
|
||||||
|
import time
|
||||||
from dataclasses import dataclass
|
from dataclasses import dataclass
|
||||||
from typing import Optional
|
from typing import Optional
|
||||||
import collections, unittest
|
import collections, unittest
|
||||||
|
|
||||||
from pantograph.server import Server, TacticFailure
|
from pantograph.server import Server, TacticFailure, ServerError
|
||||||
from pantograph.expr import Expr, Tactic, GoalState
|
from pantograph.expr import Expr, Tactic, GoalState
|
||||||
|
|
||||||
|
|
||||||
|
|
@ -38,6 +39,8 @@ class SearchState:
|
||||||
@dataclass(frozen=True)
|
@dataclass(frozen=True)
|
||||||
class SearchResult:
|
class SearchResult:
|
||||||
|
|
||||||
|
n_goals_root: int
|
||||||
|
duration: float
|
||||||
success: bool
|
success: bool
|
||||||
steps: int
|
steps: int
|
||||||
|
|
||||||
|
|
@ -77,10 +80,14 @@ class Agent:
|
||||||
max_trials_per_goal: int = 5,
|
max_trials_per_goal: int = 5,
|
||||||
verbose: bool = False) -> SearchResult:
|
verbose: bool = False) -> SearchResult:
|
||||||
"""
|
"""
|
||||||
Searches using th
|
Executes proof search on this state
|
||||||
"""
|
"""
|
||||||
|
|
||||||
assert server.is_automatic(), "Search must be run in automatic mode"
|
assert server.is_automatic(), "Search must be run in automatic mode"
|
||||||
|
|
||||||
|
n_goals_root = len(goal_state.goals)
|
||||||
|
time_start = time.time()
|
||||||
|
|
||||||
initial_state = SearchState(
|
initial_state = SearchState(
|
||||||
state=goal_state,
|
state=goal_state,
|
||||||
parent=None,
|
parent=None,
|
||||||
|
|
@ -88,9 +95,6 @@ class Agent:
|
||||||
priorities=[0.0 for _ in goal_state.goals]
|
priorities=[0.0 for _ in goal_state.goals]
|
||||||
)
|
)
|
||||||
search_stack = [initial_state]
|
search_stack = [initial_state]
|
||||||
"""
|
|
||||||
Executes proof search on this state
|
|
||||||
"""
|
|
||||||
for i_step in range(max_steps):
|
for i_step in range(max_steps):
|
||||||
assert search_stack, "No states in search stack"
|
assert search_stack, "No states in search stack"
|
||||||
|
|
||||||
|
|
@ -101,7 +105,12 @@ class Agent:
|
||||||
assert isinstance(search_state, SearchState)
|
assert isinstance(search_state, SearchState)
|
||||||
|
|
||||||
if search_state.is_solved:
|
if search_state.is_solved:
|
||||||
return SearchResult(success=True, steps=i_step)
|
return SearchResult(
|
||||||
|
n_goals_root=n_goals_root,
|
||||||
|
duration=time.time() - time_start,
|
||||||
|
success=True,
|
||||||
|
steps=i_step,
|
||||||
|
)
|
||||||
|
|
||||||
# Find the unsolved goal with the highest priority
|
# Find the unsolved goal with the highest priority
|
||||||
goal_id = search_state.next_goal_id
|
goal_id = search_state.next_goal_id
|
||||||
|
|
@ -124,7 +133,12 @@ class Agent:
|
||||||
if verbose:
|
if verbose:
|
||||||
print("Search stack has been exhausted")
|
print("Search stack has been exhausted")
|
||||||
self.reset()
|
self.reset()
|
||||||
return SearchResult(success=False, steps=i_step)
|
return SearchResult(
|
||||||
|
n_goals_root=n_goals_root,
|
||||||
|
duration=time.time() - time_start,
|
||||||
|
success=False,
|
||||||
|
steps=i_step,
|
||||||
|
)
|
||||||
continue
|
continue
|
||||||
|
|
||||||
try:
|
try:
|
||||||
|
|
@ -151,12 +165,19 @@ class Agent:
|
||||||
print(f"Tactic failed: {t}")
|
print(f"Tactic failed: {t}")
|
||||||
self.tactic_feedback = str(t)
|
self.tactic_feedback = str(t)
|
||||||
# try the next tactic. this one failed
|
# try the next tactic. this one failed
|
||||||
|
except ServerError as e:
|
||||||
|
raise RuntimeError(f"While executing tactic: {tactic}") from e
|
||||||
|
|
||||||
if verbose:
|
if verbose:
|
||||||
print("Search iteration limit exhausted")
|
print("Search iteration limit exhausted")
|
||||||
|
|
||||||
self.reset()
|
self.reset()
|
||||||
return SearchResult(success=False, steps=max_steps)
|
return SearchResult(
|
||||||
|
n_goals_root=n_goals_root,
|
||||||
|
duration=time.time() - time_start,
|
||||||
|
success=False,
|
||||||
|
steps=max_steps,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
class DumbAgent(Agent):
|
class DumbAgent(Agent):
|
||||||
|
|
|
||||||
|
|
@ -19,7 +19,7 @@ class TacticFailure(Exception):
|
||||||
class ServerError(Exception):
|
class ServerError(Exception):
|
||||||
pass
|
pass
|
||||||
|
|
||||||
DEFAULT_CORE_OPTIONS=["maxHeartbeats=0", "maxRecDepth=10000"]
|
DEFAULT_CORE_OPTIONS=["maxHeartbeats=0", "maxRecDepth=100000"]
|
||||||
|
|
||||||
class Server:
|
class Server:
|
||||||
|
|
||||||
|
|
@ -31,7 +31,7 @@ class Server:
|
||||||
# Set `{ "automaticMode" : False }` to handle resumption by yourself.
|
# Set `{ "automaticMode" : False }` to handle resumption by yourself.
|
||||||
options={},
|
options={},
|
||||||
core_options=DEFAULT_CORE_OPTIONS,
|
core_options=DEFAULT_CORE_OPTIONS,
|
||||||
timeout=60,
|
timeout=120,
|
||||||
maxread=1000000):
|
maxread=1000000):
|
||||||
"""
|
"""
|
||||||
timeout: Amount of time to wait for execution
|
timeout: Amount of time to wait for execution
|
||||||
|
|
@ -72,8 +72,11 @@ class Server:
|
||||||
env=env,
|
env=env,
|
||||||
)
|
)
|
||||||
self.proc.setecho(False) # Do not send any command before this.
|
self.proc.setecho(False) # Do not send any command before this.
|
||||||
|
try:
|
||||||
ready = self.proc.readline() # Reads the "ready."
|
ready = self.proc.readline() # Reads the "ready."
|
||||||
assert ready == "ready.\r\n", f"Server failed to emit ready signal: {ready}; Maybe the project needs to be rebuilt"
|
assert ready.rstrip() == "ready.", f"Server failed to emit ready signal: {ready}; Maybe the project needs to be rebuilt"
|
||||||
|
except pexpect.exceptions.TIMEOUT as exc:
|
||||||
|
raise RuntimeError("Server failed to emit ready signal in time") from exc
|
||||||
|
|
||||||
if self.options:
|
if self.options:
|
||||||
self.run("options.set", self.options)
|
self.run("options.set", self.options)
|
||||||
|
|
@ -84,16 +87,25 @@ class Server:
|
||||||
"""
|
"""
|
||||||
Runs a raw JSON command. Preferably use one of the commands below.
|
Runs a raw JSON command. Preferably use one of the commands below.
|
||||||
"""
|
"""
|
||||||
|
assert self.proc
|
||||||
s = json.dumps(payload)
|
s = json.dumps(payload)
|
||||||
self.proc.sendline(f"{cmd} {s}")
|
self.proc.sendline(f"{cmd} {s}")
|
||||||
try:
|
try:
|
||||||
line = self.proc.readline()
|
line = self.proc.readline()
|
||||||
try:
|
try:
|
||||||
return json.loads(line)
|
obj = json.loads(line)
|
||||||
|
if obj.get("error") == "io":
|
||||||
|
# The server is dead
|
||||||
|
self.proc = None
|
||||||
|
return obj
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
raise ServerError(f"Cannot decode: {line}") from e
|
self.proc.sendeof()
|
||||||
|
remainder = self.proc.read()
|
||||||
|
self.proc = None
|
||||||
|
raise RuntimeError(f"Cannot decode: {line}\n{remainder}") from e
|
||||||
except pexpect.exceptions.TIMEOUT as exc:
|
except pexpect.exceptions.TIMEOUT as exc:
|
||||||
raise exc
|
self.proc = None
|
||||||
|
return {"error": "timeout", "message": str(exc)}
|
||||||
|
|
||||||
def gc(self):
|
def gc(self):
|
||||||
"""
|
"""
|
||||||
|
|
|
||||||
|
|
@ -455,6 +455,105 @@ traitlets = ">=4"
|
||||||
[package.extras]
|
[package.extras]
|
||||||
test = ["pytest"]
|
test = ["pytest"]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "contourpy"
|
||||||
|
version = "1.3.0"
|
||||||
|
description = "Python library for calculating contours of 2D quadrilateral grids"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=3.9"
|
||||||
|
files = [
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:880ea32e5c774634f9fcd46504bf9f080a41ad855f4fef54f5380f5133d343c7"},
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:76c905ef940a4474a6289c71d53122a4f77766eef23c03cd57016ce19d0f7b42"},
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:92f8557cbb07415a4d6fa191f20fd9d2d9eb9c0b61d1b2f52a8926e43c6e9af7"},
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:36f965570cff02b874773c49bfe85562b47030805d7d8360748f3eca570f4cab"},
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cacd81e2d4b6f89c9f8a5b69b86490152ff39afc58a95af002a398273e5ce589"},
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:69375194457ad0fad3a839b9e29aa0b0ed53bb54db1bfb6c3ae43d111c31ce41"},
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:7a52040312b1a858b5e31ef28c2e865376a386c60c0e248370bbea2d3f3b760d"},
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:3faeb2998e4fcb256542e8a926d08da08977f7f5e62cf733f3c211c2a5586223"},
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-win32.whl", hash = "sha256:36e0cff201bcb17a0a8ecc7f454fe078437fa6bda730e695a92f2d9932bd507f"},
|
||||||
|
{file = "contourpy-1.3.0-cp310-cp310-win_amd64.whl", hash = "sha256:87ddffef1dbe5e669b5c2440b643d3fdd8622a348fe1983fad7a0f0ccb1cd67b"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0fa4c02abe6c446ba70d96ece336e621efa4aecae43eaa9b030ae5fb92b309ad"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:834e0cfe17ba12f79963861e0f908556b2cedd52e1f75e6578801febcc6a9f49"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dbc4c3217eee163fa3984fd1567632b48d6dfd29216da3ded3d7b844a8014a66"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4865cd1d419e0c7a7bf6de1777b185eebdc51470800a9f42b9e9decf17762081"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:303c252947ab4b14c08afeb52375b26781ccd6a5ccd81abcdfc1fafd14cf93c1"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:637f674226be46f6ba372fd29d9523dd977a291f66ab2a74fbeb5530bb3f445d"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:76a896b2f195b57db25d6b44e7e03f221d32fe318d03ede41f8b4d9ba1bff53c"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:e1fd23e9d01591bab45546c089ae89d926917a66dceb3abcf01f6105d927e2cb"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-win32.whl", hash = "sha256:d402880b84df3bec6eab53cd0cf802cae6a2ef9537e70cf75e91618a3801c20c"},
|
||||||
|
{file = "contourpy-1.3.0-cp311-cp311-win_amd64.whl", hash = "sha256:6cb6cc968059db9c62cb35fbf70248f40994dfcd7aa10444bbf8b3faeb7c2d67"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:570ef7cf892f0afbe5b2ee410c507ce12e15a5fa91017a0009f79f7d93a1268f"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:da84c537cb8b97d153e9fb208c221c45605f73147bd4cadd23bdae915042aad6"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0be4d8425bfa755e0fd76ee1e019636ccc7c29f77a7c86b4328a9eb6a26d0639"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9c0da700bf58f6e0b65312d0a5e695179a71d0163957fa381bb3c1f72972537c"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:eb8b141bb00fa977d9122636b16aa67d37fd40a3d8b52dd837e536d64b9a4d06"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3634b5385c6716c258d0419c46d05c8aa7dc8cb70326c9a4fb66b69ad2b52e09"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:0dce35502151b6bd35027ac39ba6e5a44be13a68f55735c3612c568cac3805fd"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:aea348f053c645100612b333adc5983d87be69acdc6d77d3169c090d3b01dc35"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-win32.whl", hash = "sha256:90f73a5116ad1ba7174341ef3ea5c3150ddf20b024b98fb0c3b29034752c8aeb"},
|
||||||
|
{file = "contourpy-1.3.0-cp312-cp312-win_amd64.whl", hash = "sha256:b11b39aea6be6764f84360fce6c82211a9db32a7c7de8fa6dd5397cf1d079c3b"},
|
||||||
|
{file = "contourpy-1.3.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:3e1c7fa44aaae40a2247e2e8e0627f4bea3dd257014764aa644f319a5f8600e3"},
|
||||||
|
{file = "contourpy-1.3.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:364174c2a76057feef647c802652f00953b575723062560498dc7930fc9b1cb7"},
|
||||||
|
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{file = "contourpy-1.3.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:d78ab28a03c854a873787a0a42254a0ccb3cb133c672f645c9f9c8f3ae9d0800"},
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{file = "contourpy-1.3.0-cp39-cp39-win32.whl", hash = "sha256:81cb5ed4952aae6014bc9d0421dec7c5835c9c8c31cdf51910b708f548cf58e5"},
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{file = "contourpy-1.3.0-cp39-cp39-win_amd64.whl", hash = "sha256:14e262f67bd7e6eb6880bc564dcda30b15e351a594657e55b7eec94b6ef72843"},
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{file = "contourpy-1.3.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:fe41b41505a5a33aeaed2a613dccaeaa74e0e3ead6dd6fd3a118fb471644fd6c"},
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{file = "contourpy-1.3.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eca7e17a65f72a5133bdbec9ecf22401c62bcf4821361ef7811faee695799779"},
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{file = "contourpy-1.3.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:1ec4dc6bf570f5b22ed0d7efba0dfa9c5b9e0431aeea7581aa217542d9e809a4"},
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{file = "contourpy-1.3.0-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:00ccd0dbaad6d804ab259820fa7cb0b8036bda0686ef844d24125d8287178ce0"},
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||||||
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{file = "contourpy-1.3.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8ca947601224119117f7c19c9cdf6b3ab54c5726ef1d906aa4a69dfb6dd58102"},
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||||||
|
{file = "contourpy-1.3.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:c6ec93afeb848a0845a18989da3beca3eec2c0f852322efe21af1931147d12cb"},
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||||||
|
{file = "contourpy-1.3.0.tar.gz", hash = "sha256:7ffa0db17717a8ffb127efd0c95a4362d996b892c2904db72428d5b52e1938a4"},
|
||||||
|
]
|
||||||
|
|
||||||
|
[package.dependencies]
|
||||||
|
numpy = ">=1.23"
|
||||||
|
|
||||||
|
[package.extras]
|
||||||
|
bokeh = ["bokeh", "selenium"]
|
||||||
|
docs = ["furo", "sphinx (>=7.2)", "sphinx-copybutton"]
|
||||||
|
mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.11.1)", "types-Pillow"]
|
||||||
|
test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
|
||||||
|
test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist", "wurlitzer"]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "cycler"
|
||||||
|
version = "0.12.1"
|
||||||
|
description = "Composable style cycles"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=3.8"
|
||||||
|
files = [
|
||||||
|
{file = "cycler-0.12.1-py3-none-any.whl", hash = "sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30"},
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{file = "cycler-0.12.1.tar.gz", hash = "sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c"},
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||||||
|
]
|
||||||
|
|
||||||
|
[package.extras]
|
||||||
|
docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
|
||||||
|
tests = ["pytest", "pytest-cov", "pytest-xdist"]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "debugpy"
|
name = "debugpy"
|
||||||
version = "1.8.6"
|
version = "1.8.6"
|
||||||
|
|
@ -605,6 +704,77 @@ files = [
|
||||||
six = "*"
|
six = "*"
|
||||||
termcolor = "*"
|
termcolor = "*"
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "fonttools"
|
||||||
|
version = "4.54.1"
|
||||||
|
description = "Tools to manipulate font files"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=3.8"
|
||||||
|
files = [
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|
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||||||
|
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||||||
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|
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|
||||||
|
]
|
||||||
|
|
||||||
|
[package.extras]
|
||||||
|
all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "pycairo", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=15.1.0)", "xattr", "zopfli (>=0.1.4)"]
|
||||||
|
graphite = ["lz4 (>=1.7.4.2)"]
|
||||||
|
interpolatable = ["munkres", "pycairo", "scipy"]
|
||||||
|
lxml = ["lxml (>=4.0)"]
|
||||||
|
pathops = ["skia-pathops (>=0.5.0)"]
|
||||||
|
plot = ["matplotlib"]
|
||||||
|
repacker = ["uharfbuzz (>=0.23.0)"]
|
||||||
|
symfont = ["sympy"]
|
||||||
|
type1 = ["xattr"]
|
||||||
|
ufo = ["fs (>=2.2.0,<3)"]
|
||||||
|
unicode = ["unicodedata2 (>=15.1.0)"]
|
||||||
|
woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "fqdn"
|
name = "fqdn"
|
||||||
version = "1.5.1"
|
version = "1.5.1"
|
||||||
|
|
@ -1220,6 +1390,129 @@ docs = ["autodoc-traits", "jinja2 (<3.2.0)", "mistune (<4)", "myst-parser", "pyd
|
||||||
openapi = ["openapi-core (>=0.18.0,<0.19.0)", "ruamel-yaml"]
|
openapi = ["openapi-core (>=0.18.0,<0.19.0)", "ruamel-yaml"]
|
||||||
test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-validator (>=0.6.0,<0.8.0)", "pytest (>=7.0,<8)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "ruamel-yaml", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"]
|
test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-validator (>=0.6.0,<0.8.0)", "pytest (>=7.0,<8)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "ruamel-yaml", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "kiwisolver"
|
||||||
|
version = "1.4.7"
|
||||||
|
description = "A fast implementation of the Cassowary constraint solver"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=3.8"
|
||||||
|
files = [
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||||||
|
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||||||
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||||||
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||||||
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||||||
|
{file = "kiwisolver-1.4.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:08471d4d86cbaec61f86b217dd938a83d85e03785f51121e791a6e6689a3be95"},
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{file = "kiwisolver-1.4.7-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7bbfcb7165ce3d54a3dfbe731e470f65739c4c1f85bb1018ee912bae139e263b"},
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|
{file = "kiwisolver-1.4.7-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5d34eb8494bea691a1a450141ebb5385e4b69d38bb8403b5146ad279f4b30fa3"},
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||||||
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{file = "kiwisolver-1.4.7-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9242795d174daa40105c1d86aba618e8eab7bf96ba8c3ee614da8302a9f95503"},
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||||||
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{file = "kiwisolver-1.4.7-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:a0f64a48bb81af7450e641e3fe0b0394d7381e342805479178b3d335d60ca7cf"},
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||||||
|
{file = "kiwisolver-1.4.7-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:8e045731a5416357638d1700927529e2b8ab304811671f665b225f8bf8d8f933"},
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||||||
|
{file = "kiwisolver-1.4.7-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:4322872d5772cae7369f8351da1edf255a604ea7087fe295411397d0cfd9655e"},
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||||||
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{file = "kiwisolver-1.4.7-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:e1631290ee9271dffe3062d2634c3ecac02c83890ada077d225e081aca8aab89"},
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||||||
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{file = "kiwisolver-1.4.7-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:edcfc407e4eb17e037bca59be0e85a2031a2ac87e4fed26d3e9df88b4165f92d"},
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|
{file = "kiwisolver-1.4.7-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:4d05d81ecb47d11e7f8932bd8b61b720bf0b41199358f3f5e36d38e28f0532c5"},
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||||||
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{file = "kiwisolver-1.4.7-cp38-cp38-win32.whl", hash = "sha256:b38ac83d5f04b15e515fd86f312479d950d05ce2368d5413d46c088dda7de90a"},
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||||||
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{file = "kiwisolver-1.4.7-cp38-cp38-win_amd64.whl", hash = "sha256:d83db7cde68459fc803052a55ace60bea2bae361fc3b7a6d5da07e11954e4b09"},
|
||||||
|
{file = "kiwisolver-1.4.7-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:3f9362ecfca44c863569d3d3c033dbe8ba452ff8eed6f6b5806382741a1334bd"},
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|
{file = "kiwisolver-1.4.7-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:e8df2eb9b2bac43ef8b082e06f750350fbbaf2887534a5be97f6cf07b19d9583"},
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||||||
|
{file = "kiwisolver-1.4.7-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f32d6edbc638cde7652bd690c3e728b25332acbadd7cad670cc4a02558d9c417"},
|
||||||
|
{file = "kiwisolver-1.4.7-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:e2e6c39bd7b9372b0be21456caab138e8e69cc0fc1190a9dfa92bd45a1e6e904"},
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{file = "kiwisolver-1.4.7-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:dda56c24d869b1193fcc763f1284b9126550eaf84b88bbc7256e15028f19188a"},
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||||||
|
{file = "kiwisolver-1.4.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:79849239c39b5e1fd906556c474d9b0439ea6792b637511f3fe3a41158d89ca8"},
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|
{file = "kiwisolver-1.4.7-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5e3bc157fed2a4c02ec468de4ecd12a6e22818d4f09cde2c31ee3226ffbefab2"},
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|
{file = "kiwisolver-1.4.7-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3da53da805b71e41053dc670f9a820d1157aae77b6b944e08024d17bcd51ef88"},
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||||||
|
{file = "kiwisolver-1.4.7-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:8705f17dfeb43139a692298cb6637ee2e59c0194538153e83e9ee0c75c2eddde"},
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||||||
|
{file = "kiwisolver-1.4.7-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:82a5c2f4b87c26bb1a0ef3d16b5c4753434633b83d365cc0ddf2770c93829e3c"},
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|
{file = "kiwisolver-1.4.7-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:ce8be0466f4c0d585cdb6c1e2ed07232221df101a4c6f28821d2aa754ca2d9e2"},
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|
{file = "kiwisolver-1.4.7-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:409afdfe1e2e90e6ee7fc896f3df9a7fec8e793e58bfa0d052c8a82f99c37abb"},
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|
{file = "kiwisolver-1.4.7-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:5b9c3f4ee0b9a439d2415012bd1b1cc2df59e4d6a9939f4d669241d30b414327"},
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||||||
|
{file = "kiwisolver-1.4.7-cp39-cp39-win32.whl", hash = "sha256:a79ae34384df2b615eefca647a2873842ac3b596418032bef9a7283675962644"},
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||||||
|
{file = "kiwisolver-1.4.7-cp39-cp39-win_amd64.whl", hash = "sha256:cf0438b42121a66a3a667de17e779330fc0f20b0d97d59d2f2121e182b0505e4"},
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{file = "kiwisolver-1.4.7-cp39-cp39-win_arm64.whl", hash = "sha256:764202cc7e70f767dab49e8df52c7455e8de0df5d858fa801a11aa0d882ccf3f"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:94252291e3fe68001b1dd747b4c0b3be12582839b95ad4d1b641924d68fd4643"},
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||||||
|
{file = "kiwisolver-1.4.7-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:5b7dfa3b546da08a9f622bb6becdb14b3e24aaa30adba66749d38f3cc7ea9706"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp310-pypy310_pp73-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bd3de6481f4ed8b734da5df134cd5a6a64fe32124fe83dde1e5b5f29fe30b1e6"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a91b5f9f1205845d488c928e8570dcb62b893372f63b8b6e98b863ebd2368ff2"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:40fa14dbd66b8b8f470d5fc79c089a66185619d31645f9b0773b88b19f7223c4"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:eb542fe7933aa09d8d8f9d9097ef37532a7df6497819d16efe4359890a2f417a"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:bfa1acfa0c54932d5607e19a2c24646fb4c1ae2694437789129cf099789a3b00"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp38-pypy38_pp73-macosx_11_0_arm64.whl", hash = "sha256:eee3ea935c3d227d49b4eb85660ff631556841f6e567f0f7bda972df6c2c9935"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp38-pypy38_pp73-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:f3160309af4396e0ed04db259c3ccbfdc3621b5559b5453075e5de555e1f3a1b"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp38-pypy38_pp73-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:a17f6a29cf8935e587cc8a4dbfc8368c55edc645283db0ce9801016f83526c2d"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:10849fb2c1ecbfae45a693c070e0320a91b35dd4bcf58172c023b994283a124d"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:ac542bf38a8a4be2dc6b15248d36315ccc65f0743f7b1a76688ffb6b5129a5c2"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:8b01aac285f91ca889c800042c35ad3b239e704b150cfd3382adfc9dcc780e39"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:48be928f59a1f5c8207154f935334d374e79f2b5d212826307d072595ad76a2e"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp39-pypy39_pp73-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f37cfe618a117e50d8c240555331160d73d0411422b59b5ee217843d7b693608"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:599b5c873c63a1f6ed7eead644a8a380cfbdf5db91dcb6f85707aaab213b1674"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:801fa7802e5cfabe3ab0c81a34c323a319b097dfb5004be950482d882f3d7225"},
|
||||||
|
{file = "kiwisolver-1.4.7-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:0c6c43471bc764fad4bc99c5c2d6d16a676b1abf844ca7c8702bdae92df01ee0"},
|
||||||
|
{file = "kiwisolver-1.4.7.tar.gz", hash = "sha256:9893ff81bd7107f7b685d3017cc6583daadb4fc26e4a888350df530e41980a60"},
|
||||||
|
]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "markupsafe"
|
name = "markupsafe"
|
||||||
version = "2.1.5"
|
version = "2.1.5"
|
||||||
|
|
@ -1289,6 +1582,69 @@ files = [
|
||||||
{file = "MarkupSafe-2.1.5.tar.gz", hash = "sha256:d283d37a890ba4c1ae73ffadf8046435c76e7bc2247bbb63c00bd1a709c6544b"},
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{file = "MarkupSafe-2.1.5.tar.gz", hash = "sha256:d283d37a890ba4c1ae73ffadf8046435c76e7bc2247bbb63c00bd1a709c6544b"},
|
||||||
]
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "matplotlib"
|
||||||
|
version = "3.9.2"
|
||||||
|
description = "Python plotting package"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=3.9"
|
||||||
|
files = [
|
||||||
|
{file = "matplotlib-3.9.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:9d78bbc0cbc891ad55b4f39a48c22182e9bdaea7fc0e5dbd364f49f729ca1bbb"},
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{file = "matplotlib-3.9.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1d94ff717eb2bd0b58fe66380bd8b14ac35f48a98e7c6765117fe67fb7684e64"},
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|
{file = "matplotlib-3.9.2-cp310-cp310-win_amd64.whl", hash = "sha256:3fd595f34aa8a55b7fc8bf9ebea8aa665a84c82d275190a61118d33fbc82ccae"},
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{file = "matplotlib-3.9.2-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:d8dd059447824eec055e829258ab092b56bb0579fc3164fa09c64f3acd478772"},
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|
{file = "matplotlib-3.9.2-cp311-cp311-win_amd64.whl", hash = "sha256:ae82a14dab96fbfad7965403c643cafe6515e386de723e498cf3eeb1e0b70cc7"},
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||||||
|
{file = "matplotlib-3.9.2-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:ac43031375a65c3196bee99f6001e7fa5bdfb00ddf43379d3c0609bdca042df9"},
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||||||
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|
||||||
|
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|
||||||
|
{file = "matplotlib-3.9.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1cd93b91ab47a3616b4d3c42b52f8363b88ca021e340804c6ab2536344fad9ca"},
|
||||||
|
{file = "matplotlib-3.9.2-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:6d1ce5ed2aefcdce11904fc5bbea7d9c21fff3d5f543841edf3dea84451a09ea"},
|
||||||
|
{file = "matplotlib-3.9.2-cp39-cp39-win_amd64.whl", hash = "sha256:b2696efdc08648536efd4e1601b5fd491fd47f4db97a5fbfd175549a7365c1b2"},
|
||||||
|
{file = "matplotlib-3.9.2-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:d52a3b618cb1cbb769ce2ee1dcdb333c3ab6e823944e9a2d36e37253815f9556"},
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||||||
|
{file = "matplotlib-3.9.2-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:039082812cacd6c6bec8e17a9c1e6baca230d4116d522e81e1f63a74d01d2e21"},
|
||||||
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{file = "matplotlib-3.9.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6758baae2ed64f2331d4fd19be38b7b4eae3ecec210049a26b6a4f3ae1c85dcc"},
|
||||||
|
{file = "matplotlib-3.9.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:050598c2b29e0b9832cde72bcf97627bf00262adbc4a54e2b856426bb2ef0697"},
|
||||||
|
{file = "matplotlib-3.9.2.tar.gz", hash = "sha256:96ab43906269ca64a6366934106fa01534454a69e471b7bf3d79083981aaab92"},
|
||||||
|
]
|
||||||
|
|
||||||
|
[package.dependencies]
|
||||||
|
contourpy = ">=1.0.1"
|
||||||
|
cycler = ">=0.10"
|
||||||
|
fonttools = ">=4.22.0"
|
||||||
|
kiwisolver = ">=1.3.1"
|
||||||
|
numpy = ">=1.23"
|
||||||
|
packaging = ">=20.0"
|
||||||
|
pillow = ">=8"
|
||||||
|
pyparsing = ">=2.3.1"
|
||||||
|
python-dateutil = ">=2.7"
|
||||||
|
|
||||||
|
[package.extras]
|
||||||
|
dev = ["meson-python (>=0.13.1)", "numpy (>=1.25)", "pybind11 (>=2.6)", "setuptools (>=64)", "setuptools_scm (>=7)"]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "matplotlib-inline"
|
name = "matplotlib-inline"
|
||||||
version = "0.1.7"
|
version = "0.1.7"
|
||||||
|
|
@ -1713,6 +2069,92 @@ files = [
|
||||||
{file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"},
|
{file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"},
|
||||||
]
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "pandas"
|
||||||
|
version = "2.2.3"
|
||||||
|
description = "Powerful data structures for data analysis, time series, and statistics"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=3.9"
|
||||||
|
files = [
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||||||
|
{file = "pandas-2.2.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:1948ddde24197a0f7add2bdc4ca83bf2b1ef84a1bc8ccffd95eda17fd836ecb5"},
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{file = "pandas-2.2.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:381175499d3802cde0eabbaf6324cce0c4f5d52ca6f8c377c29ad442f50f6348"},
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{file = "pandas-2.2.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d9c45366def9a3dd85a6454c0e7908f2b3b8e9c138f5dc38fed7ce720d8453ed"},
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{file = "pandas-2.2.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:b8661b0238a69d7aafe156b7fa86c44b881387509653fdf857bebc5e4008ad42"},
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{file = "pandas-2.2.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:37e0aced3e8f539eccf2e099f65cdb9c8aa85109b0be6e93e2baff94264bdc6f"},
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{file = "pandas-2.2.3-cp310-cp310-win_amd64.whl", hash = "sha256:56534ce0746a58afaf7942ba4863e0ef81c9c50d3f0ae93e9497d6a41a057645"},
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{file = "pandas-2.2.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:66108071e1b935240e74525006034333f98bcdb87ea116de573a6a0dccb6c039"},
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{file = "pandas-2.2.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7c2875855b0ff77b2a64a0365e24455d9990730d6431b9e0ee18ad8acee13dbd"},
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{file = "pandas-2.2.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cd8d0c3be0515c12fed0bdbae072551c8b54b7192c7b1fda0ba56059a0179698"},
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{file = "pandas-2.2.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:63cc132e40a2e084cf01adf0775b15ac515ba905d7dcca47e9a251819c575ef3"},
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{file = "pandas-2.2.3-cp311-cp311-win_amd64.whl", hash = "sha256:3fc6873a41186404dad67245896a6e440baacc92f5b716ccd1bc9ed2995ab2c5"},
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{file = "pandas-2.2.3-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:b1d432e8d08679a40e2a6d8b2f9770a5c21793a6f9f47fdd52c5ce1948a5a8a9"},
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{file = "pandas-2.2.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a5a1595fe639f5988ba6a8e5bc9649af3baf26df3998a0abe56c02609392e0a4"},
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{file = "pandas-2.2.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5de54125a92bb4d1c051c0659e6fcb75256bf799a732a87184e5ea503965bce3"},
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{file = "pandas-2.2.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fffb8ae78d8af97f849404f21411c95062db1496aeb3e56f146f0355c9989319"},
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{file = "pandas-2.2.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:6dfcb5ee8d4d50c06a51c2fffa6cff6272098ad6540aed1a76d15fb9318194d8"},
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{file = "pandas-2.2.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:062309c1b9ea12a50e8ce661145c6aab431b1e99530d3cd60640e255778bd43a"},
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{file = "pandas-2.2.3-cp312-cp312-win_amd64.whl", hash = "sha256:59ef3764d0fe818125a5097d2ae867ca3fa64df032331b7e0917cf5d7bf66b13"},
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||||||
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{file = "pandas-2.2.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f00d1345d84d8c86a63e476bb4955e46458b304b9575dcf71102b5c705320015"},
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{file = "pandas-2.2.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:3508d914817e153ad359d7e069d752cdd736a247c322d932eb89e6bc84217f28"},
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||||||
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{file = "pandas-2.2.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:22a9d949bfc9a502d320aa04e5d02feab689d61da4e7764b62c30b991c42c5f0"},
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{file = "pandas-2.2.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f3a255b2c19987fbbe62a9dfd6cff7ff2aa9ccab3fc75218fd4b7530f01efa24"},
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{file = "pandas-2.2.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:800250ecdadb6d9c78eae4990da62743b857b470883fa27f652db8bdde7f6659"},
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{file = "pandas-2.2.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:6374c452ff3ec675a8f46fd9ab25c4ad0ba590b71cf0656f8b6daa5202bca3fb"},
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{file = "pandas-2.2.3-cp313-cp313-win_amd64.whl", hash = "sha256:61c5ad4043f791b61dd4752191d9f07f0ae412515d59ba8f005832a532f8736d"},
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{file = "pandas-2.2.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:3b71f27954685ee685317063bf13c7709a7ba74fc996b84fc6821c59b0f06468"},
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{file = "pandas-2.2.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:38cf8125c40dae9d5acc10fa66af8ea6fdf760b2714ee482ca691fc66e6fcb18"},
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||||||
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{file = "pandas-2.2.3-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:ba96630bc17c875161df3818780af30e43be9b166ce51c9a18c1feae342906c2"},
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{file = "pandas-2.2.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1db71525a1538b30142094edb9adc10be3f3e176748cd7acc2240c2f2e5aa3a4"},
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||||||
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{file = "pandas-2.2.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:15c0e1e02e93116177d29ff83e8b1619c93ddc9c49083f237d4312337a61165d"},
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||||||
|
{file = "pandas-2.2.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:ad5b65698ab28ed8d7f18790a0dc58005c7629f227be9ecc1072aa74c0c1d43a"},
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||||||
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{file = "pandas-2.2.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:bc6b93f9b966093cb0fd62ff1a7e4c09e6d546ad7c1de191767baffc57628f39"},
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||||||
|
{file = "pandas-2.2.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:5dbca4c1acd72e8eeef4753eeca07de9b1db4f398669d5994086f788a5d7cc30"},
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||||||
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{file = "pandas-2.2.3-cp39-cp39-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:8cd6d7cc958a3910f934ea8dbdf17b2364827bb4dafc38ce6eef6bb3d65ff09c"},
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||||||
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{file = "pandas-2.2.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:99df71520d25fade9db7c1076ac94eb994f4d2673ef2aa2e86ee039b6746d20c"},
|
||||||
|
{file = "pandas-2.2.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:31d0ced62d4ea3e231a9f228366919a5ea0b07440d9d4dac345376fd8e1477ea"},
|
||||||
|
{file = "pandas-2.2.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:7eee9e7cea6adf3e3d24e304ac6b8300646e2a5d1cd3a3c2abed9101b0846761"},
|
||||||
|
{file = "pandas-2.2.3-cp39-cp39-win_amd64.whl", hash = "sha256:4850ba03528b6dd51d6c5d273c46f183f39a9baf3f0143e566b89450965b105e"},
|
||||||
|
{file = "pandas-2.2.3.tar.gz", hash = "sha256:4f18ba62b61d7e192368b84517265a99b4d7ee8912f8708660fb4a366cc82667"},
|
||||||
|
]
|
||||||
|
|
||||||
|
[package.dependencies]
|
||||||
|
numpy = [
|
||||||
|
{version = ">=1.22.4", markers = "python_version < \"3.11\""},
|
||||||
|
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
|
||||||
|
{version = ">=1.26.0", markers = "python_version >= \"3.12\""},
|
||||||
|
]
|
||||||
|
python-dateutil = ">=2.8.2"
|
||||||
|
pytz = ">=2020.1"
|
||||||
|
tzdata = ">=2022.7"
|
||||||
|
|
||||||
|
[package.extras]
|
||||||
|
all = ["PyQt5 (>=5.15.9)", "SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)", "beautifulsoup4 (>=4.11.2)", "bottleneck (>=1.3.6)", "dataframe-api-compat (>=0.1.7)", "fastparquet (>=2022.12.0)", "fsspec (>=2022.11.0)", "gcsfs (>=2022.11.0)", "html5lib (>=1.1)", "hypothesis (>=6.46.1)", "jinja2 (>=3.1.2)", "lxml (>=4.9.2)", "matplotlib (>=3.6.3)", "numba (>=0.56.4)", "numexpr (>=2.8.4)", "odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "pandas-gbq (>=0.19.0)", "psycopg2 (>=2.9.6)", "pyarrow (>=10.0.1)", "pymysql (>=1.0.2)", "pyreadstat (>=1.2.0)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "qtpy (>=2.3.0)", "s3fs (>=2022.11.0)", "scipy (>=1.10.0)", "tables (>=3.8.0)", "tabulate (>=0.9.0)", "xarray (>=2022.12.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)", "zstandard (>=0.19.0)"]
|
||||||
|
aws = ["s3fs (>=2022.11.0)"]
|
||||||
|
clipboard = ["PyQt5 (>=5.15.9)", "qtpy (>=2.3.0)"]
|
||||||
|
compression = ["zstandard (>=0.19.0)"]
|
||||||
|
computation = ["scipy (>=1.10.0)", "xarray (>=2022.12.0)"]
|
||||||
|
consortium-standard = ["dataframe-api-compat (>=0.1.7)"]
|
||||||
|
excel = ["odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)"]
|
||||||
|
feather = ["pyarrow (>=10.0.1)"]
|
||||||
|
fss = ["fsspec (>=2022.11.0)"]
|
||||||
|
gcp = ["gcsfs (>=2022.11.0)", "pandas-gbq (>=0.19.0)"]
|
||||||
|
hdf5 = ["tables (>=3.8.0)"]
|
||||||
|
html = ["beautifulsoup4 (>=4.11.2)", "html5lib (>=1.1)", "lxml (>=4.9.2)"]
|
||||||
|
mysql = ["SQLAlchemy (>=2.0.0)", "pymysql (>=1.0.2)"]
|
||||||
|
output-formatting = ["jinja2 (>=3.1.2)", "tabulate (>=0.9.0)"]
|
||||||
|
parquet = ["pyarrow (>=10.0.1)"]
|
||||||
|
performance = ["bottleneck (>=1.3.6)", "numba (>=0.56.4)", "numexpr (>=2.8.4)"]
|
||||||
|
plot = ["matplotlib (>=3.6.3)"]
|
||||||
|
postgresql = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "psycopg2 (>=2.9.6)"]
|
||||||
|
pyarrow = ["pyarrow (>=10.0.1)"]
|
||||||
|
spss = ["pyreadstat (>=1.2.0)"]
|
||||||
|
sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)"]
|
||||||
|
test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
|
||||||
|
xml = ["lxml (>=4.9.2)"]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "pandocfilters"
|
name = "pandocfilters"
|
||||||
version = "1.5.1"
|
version = "1.5.1"
|
||||||
|
|
@ -1753,6 +2195,103 @@ files = [
|
||||||
[package.dependencies]
|
[package.dependencies]
|
||||||
ptyprocess = ">=0.5"
|
ptyprocess = ">=0.5"
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "pillow"
|
||||||
|
version = "10.4.0"
|
||||||
|
description = "Python Imaging Library (Fork)"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=3.8"
|
||||||
|
files = [
|
||||||
|
{file = "pillow-10.4.0-cp310-cp310-macosx_10_10_x86_64.whl", hash = "sha256:4d9667937cfa347525b319ae34375c37b9ee6b525440f3ef48542fcf66f2731e"},
|
||||||
|
{file = "pillow-10.4.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:543f3dc61c18dafb755773efc89aae60d06b6596a63914107f75459cf984164d"},
|
||||||
|
{file = "pillow-10.4.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7928ecbf1ece13956b95d9cbcfc77137652b02763ba384d9ab508099a2eca856"},
|
||||||
|
{file = "pillow-10.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e4d49b85c4348ea0b31ea63bc75a9f3857869174e2bf17e7aba02945cd218e6f"},
|
||||||
|
{file = "pillow-10.4.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:6c762a5b0997f5659a5ef2266abc1d8851ad7749ad9a6a5506eb23d314e4f46b"},
|
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{file = "pillow-10.4.0-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:02a2be69f9c9b8c1e97cf2713e789d4e398c751ecfd9967c18d0ce304efbf885"},
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{file = "pillow-10.4.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:0755ffd4a0c6f267cccbae2e9903d95477ca2f77c4fcf3a3a09570001856c8a5"},
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{file = "pillow-10.4.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:1b5dea9831a90e9d0721ec417a80d4cbd7022093ac38a568db2dd78363b00908"},
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{file = "pillow-10.4.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9b885f89040bb8c4a1573566bbb2f44f5c505ef6e74cec7ab9068c900047f04b"},
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{file = "pillow-10.4.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:87dd88ded2e6d74d31e1e0a99a726a6765cda32d00ba72dc37f0651f306daaa8"},
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||||||
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{file = "pillow-10.4.0-pp39-pypy39_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:2db98790afc70118bd0255c2eeb465e9767ecf1f3c25f9a1abb8ffc8cfd1fe0a"},
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||||||
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{file = "pillow-10.4.0-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:f7baece4ce06bade126fb84b8af1c33439a76d8a6fd818970215e0560ca28c27"},
|
||||||
|
{file = "pillow-10.4.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:cfdd747216947628af7b259d274771d84db2268ca062dd5faf373639d00113a3"},
|
||||||
|
{file = "pillow-10.4.0.tar.gz", hash = "sha256:166c1cd4d24309b30d61f79f4a9114b7b2313d7450912277855ff5dfd7cd4a06"},
|
||||||
|
]
|
||||||
|
|
||||||
|
[package.extras]
|
||||||
|
docs = ["furo", "olefile", "sphinx (>=7.3)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinxext-opengraph"]
|
||||||
|
fpx = ["olefile"]
|
||||||
|
mic = ["olefile"]
|
||||||
|
tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
|
||||||
|
typing = ["typing-extensions"]
|
||||||
|
xmp = ["defusedxml"]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "platformdirs"
|
name = "platformdirs"
|
||||||
version = "4.3.6"
|
version = "4.3.6"
|
||||||
|
|
@ -1897,8 +2436,8 @@ files = [
|
||||||
annotated-types = ">=0.6.0"
|
annotated-types = ">=0.6.0"
|
||||||
pydantic-core = "2.23.4"
|
pydantic-core = "2.23.4"
|
||||||
typing-extensions = [
|
typing-extensions = [
|
||||||
{version = ">=4.12.2", markers = "python_version >= \"3.13\""},
|
|
||||||
{version = ">=4.6.1", markers = "python_version < \"3.13\""},
|
{version = ">=4.6.1", markers = "python_version < \"3.13\""},
|
||||||
|
{version = ">=4.12.2", markers = "python_version >= \"3.13\""},
|
||||||
]
|
]
|
||||||
|
|
||||||
[package.extras]
|
[package.extras]
|
||||||
|
|
@ -2020,6 +2559,20 @@ files = [
|
||||||
[package.extras]
|
[package.extras]
|
||||||
windows-terminal = ["colorama (>=0.4.6)"]
|
windows-terminal = ["colorama (>=0.4.6)"]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "pyparsing"
|
||||||
|
version = "3.1.4"
|
||||||
|
description = "pyparsing module - Classes and methods to define and execute parsing grammars"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=3.6.8"
|
||||||
|
files = [
|
||||||
|
{file = "pyparsing-3.1.4-py3-none-any.whl", hash = "sha256:a6a7ee4235a3f944aa1fa2249307708f893fe5717dc603503c6c7969c070fb7c"},
|
||||||
|
{file = "pyparsing-3.1.4.tar.gz", hash = "sha256:f86ec8d1a83f11977c9a6ea7598e8c27fc5cddfa5b07ea2241edbbde1d7bc032"},
|
||||||
|
]
|
||||||
|
|
||||||
|
[package.extras]
|
||||||
|
diagrams = ["jinja2", "railroad-diagrams"]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "python-dateutil"
|
name = "python-dateutil"
|
||||||
version = "2.9.0.post0"
|
version = "2.9.0.post0"
|
||||||
|
|
@ -2045,6 +2598,17 @@ files = [
|
||||||
{file = "python_json_logger-2.0.7-py3-none-any.whl", hash = "sha256:f380b826a991ebbe3de4d897aeec42760035ac760345e57b812938dc8b35e2bd"},
|
{file = "python_json_logger-2.0.7-py3-none-any.whl", hash = "sha256:f380b826a991ebbe3de4d897aeec42760035ac760345e57b812938dc8b35e2bd"},
|
||||||
]
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "pytz"
|
||||||
|
version = "2024.2"
|
||||||
|
description = "World timezone definitions, modern and historical"
|
||||||
|
optional = false
|
||||||
|
python-versions = "*"
|
||||||
|
files = [
|
||||||
|
{file = "pytz-2024.2-py2.py3-none-any.whl", hash = "sha256:31c7c1817eb7fae7ca4b8c7ee50c72f93aa2dd863de768e1ef4245d426aa0725"},
|
||||||
|
{file = "pytz-2024.2.tar.gz", hash = "sha256:2aa355083c50a0f93fa581709deac0c9ad65cca8a9e9beac660adcbd493c798a"},
|
||||||
|
]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "pywin32"
|
name = "pywin32"
|
||||||
version = "307"
|
version = "307"
|
||||||
|
|
@ -2546,6 +3110,27 @@ files = [
|
||||||
{file = "rpds_py-0.20.0.tar.gz", hash = "sha256:d72a210824facfdaf8768cf2d7ca25a042c30320b3020de2fa04640920d4e121"},
|
{file = "rpds_py-0.20.0.tar.gz", hash = "sha256:d72a210824facfdaf8768cf2d7ca25a042c30320b3020de2fa04640920d4e121"},
|
||||||
]
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "seaborn"
|
||||||
|
version = "0.13.2"
|
||||||
|
description = "Statistical data visualization"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=3.8"
|
||||||
|
files = [
|
||||||
|
{file = "seaborn-0.13.2-py3-none-any.whl", hash = "sha256:636f8336facf092165e27924f223d3c62ca560b1f2bb5dff7ab7fad265361987"},
|
||||||
|
{file = "seaborn-0.13.2.tar.gz", hash = "sha256:93e60a40988f4d65e9f4885df477e2fdaff6b73a9ded434c1ab356dd57eefff7"},
|
||||||
|
]
|
||||||
|
|
||||||
|
[package.dependencies]
|
||||||
|
matplotlib = ">=3.4,<3.6.1 || >3.6.1"
|
||||||
|
numpy = ">=1.20,<1.24.0 || >1.24.0"
|
||||||
|
pandas = ">=1.2"
|
||||||
|
|
||||||
|
[package.extras]
|
||||||
|
dev = ["flake8", "flit", "mypy", "pandas-stubs", "pre-commit", "pytest", "pytest-cov", "pytest-xdist"]
|
||||||
|
docs = ["ipykernel", "nbconvert", "numpydoc", "pydata_sphinx_theme (==0.10.0rc2)", "pyyaml", "sphinx (<6.0.0)", "sphinx-copybutton", "sphinx-design", "sphinx-issues"]
|
||||||
|
stats = ["scipy (>=1.7)", "statsmodels (>=0.12)"]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "send2trash"
|
name = "send2trash"
|
||||||
version = "1.8.3"
|
version = "1.8.3"
|
||||||
|
|
@ -3125,6 +3710,17 @@ files = [
|
||||||
{file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
|
{file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
|
||||||
]
|
]
|
||||||
|
|
||||||
|
[[package]]
|
||||||
|
name = "tzdata"
|
||||||
|
version = "2024.2"
|
||||||
|
description = "Provider of IANA time zone data"
|
||||||
|
optional = false
|
||||||
|
python-versions = ">=2"
|
||||||
|
files = [
|
||||||
|
{file = "tzdata-2024.2-py2.py3-none-any.whl", hash = "sha256:a48093786cdcde33cad18c2555e8532f34422074448fbc874186f0abd79565cd"},
|
||||||
|
{file = "tzdata-2024.2.tar.gz", hash = "sha256:7d85cc416e9382e69095b7bdf4afd9e3880418a2413feec7069d533d6b4e31cc"},
|
||||||
|
]
|
||||||
|
|
||||||
[[package]]
|
[[package]]
|
||||||
name = "uri-template"
|
name = "uri-template"
|
||||||
version = "1.3.0"
|
version = "1.3.0"
|
||||||
|
|
@ -3254,4 +3850,4 @@ test = ["websockets"]
|
||||||
[metadata]
|
[metadata]
|
||||||
lock-version = "2.0"
|
lock-version = "2.0"
|
||||||
python-versions = "^3.10"
|
python-versions = "^3.10"
|
||||||
content-hash = "b198bb707b86539e6c8edfe2b7377d47387aaaf053bb68b135ccd15361736030"
|
content-hash = "24bc4bc85f985da47c5d432bbc29b6f859b409de794313d6f847cc3b9b3e7a28"
|
||||||
|
|
|
||||||
|
|
@ -27,6 +27,9 @@ torch = "2.2.1"
|
||||||
wandb = "0.17.0"
|
wandb = "0.17.0"
|
||||||
termcolor = "^2.4.0"
|
termcolor = "^2.4.0"
|
||||||
# vllm = "0.4.1"
|
# vllm = "0.4.1"
|
||||||
|
matplotlib = "^3.9.2"
|
||||||
|
seaborn = "^0.13.2"
|
||||||
|
pandas = "^2.2.3"
|
||||||
|
|
||||||
[build-system]
|
[build-system]
|
||||||
requires = ["poetry-core"]
|
requires = ["poetry-core"]
|
||||||
|
|
|
||||||
Loading…
Reference in New Issue