)\n",
+ "r2r_error=0.001 r2r_threshold=0.001\n",
+ "Parvars [v_68, v_145, v_119, v_144, v_186, v_133, v_213, v_138, v_219, v_88, v_152, v_74, v_218, v_142, v_209, v_62, v_172, v_102, v_169]\n",
+ "Detected 19 slice variables\n",
+ "P 0(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
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+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
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+ "(2, 2)\n",
+ "(2, 2)\n",
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+ "(2, 2)\n",
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+ "(2, 2)\n",
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+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
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+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
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+ "(2,)\n",
+ "(2, 2)\n",
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+ "(2,)\n",
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+ "(2,)\n",
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+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2,)\n",
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+ "(2, 2)\n",
+ "(2, 2)\n",
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+ "(2, 2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
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+ "(2, 2)\n",
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+ "(2, 2)\n",
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+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2,)\n",
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+ "(2, 2)\n",
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+ "(2, 2)\n",
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+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
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+ "(2, 2, 2, 2)\n",
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+ "(2, 2, 2)\n",
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+ "(2, 2)\n",
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+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
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+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
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+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
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+ "(2, 2)\n",
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+ "(2, 2)\n",
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+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
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+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 2.0 KB\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4.0 KB\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 2.0 KB\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4.0 KB\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4.0 KB\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4.0 KB\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4.0 KB\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 16.0 KB\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 2.0 KB\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4.0 KB\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4.0 KB\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4.0 KB\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 32.0 KB\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 16.0 KB\n",
+ "(2,)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 32.0 KB\n",
+ "(2,)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 64.0 KB\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 128.0 KB\n",
+ "CuPy memory usage 1.0859375 MB. Total MB: 1.38623046875\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 256.0 KB\n",
+ "CuPy memory usage 1.3330078125 MB. Total MB: 1.88623046875\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 512.0 KB\n",
+ "Total memory usage 1.0467376708984375 MB\n",
+ "CuPy memory usage 1.8125 MB. Total MB: 1.82421875\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 512.0 KB\n",
+ "Total memory usage 1.4207611083984375 MB\n",
+ "CuPy memory usage 2.1865234375 MB. Total MB: 2.1982421875\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 256.0 KB\n",
+ "Total memory usage 1.623870849609375 MB\n",
+ "CuPy memory usage 2.38916015625 MB. Total MB: 2.40087890625\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 256.0 KB\n",
+ "Total memory usage 1.373870849609375 MB\n",
+ "CuPy memory usage 2.13916015625 MB. Total MB: 2.40087890625\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 512.0 KB\n",
+ "Total memory usage 1.83868408203125 MB\n",
+ "CuPy memory usage 2.603515625 MB. Total MB: 2.853515625\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 256.0 KB\n",
+ "Total memory usage 1.83843994140625 MB\n",
+ "CuPy memory usage 2.60302734375 MB. Total MB: 2.60302734375\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4096.0 KB\n",
+ "Total memory usage 5.58837890625 MB\n",
+ "CuPy memory usage 6.3525390625 MB. Total MB: 6.6025390625\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4096.0 KB\n",
+ "Total memory usage 9.52197265625 MB\n",
+ "CuPy memory usage 10.2861328125 MB. Total MB: 10.5361328125\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4096.0 KB\n",
+ "Total memory usage 13.26806640625 MB\n",
+ "CuPy memory usage 14.0322265625 MB. Total MB: 14.2822265625\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Need compression: [v_278]\n",
+ "Chunk indices: [v_275, v_273, v_272, v_271, v_270, v_269, v_268, v_267, v_266, v_265, v_264, v_263, v_259, v_257, v_255, v_254, v_253, v_246, v_245, v_244, v_243, v_242, v_241, v_240], remove_compress: set()\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 0\n",
+ "6.410203313675585\n",
+ "Compress: Measure: 0.021s, 128.00MB -> 15.97MB (8.016 in/out ratio)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 0\n",
+ "Compression end timestamp: 3.584000 ms\n",
+ "CUDA Error: no error\n",
+ "8.64202456792365\n",
+ "Compress: Measure: 0.017s, 128.00MB -> 10.81MB (11.839 in/out ratio)\n",
+ "Return C239{v_278}(v_275,v_273,v_272,v_271,v_270,v_269,v_268,v_267,v_266,v_265,v_264,v_263,v_259,v_257,v_255,v_254,v_253,v_246,v_245,v_244,v_243,v_242,v_241,v_240)\n",
+ "Total memory usage 12.764175415039062 MB\n",
+ "Compression end timestamp: 3.343360 ms\n",
+ "CUDA Error: no error\n",
+ "CuPy memory usage 77.5283203125 MB. Total MB: 141.7783203125\n",
+ "Need compression: []\n",
+ "Chunk indices: [v_278, v_275, v_273, v_272, v_271, v_270, v_269, v_268, v_267, v_266, v_265, v_264, v_263, v_259, v_257, v_255, v_254, v_253, v_246, v_245, v_244, v_243, v_242, v_241], remove_compress: {v_278}\n",
+ "Decompress: Measure: 0.017s, 15.97MB -> 128.00MB (0.125 in/out ratio)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 1\n",
+ "Decompress: Measure: 0.004s, 10.81MB -> 128.00MB (0.084 in/out ratio)\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 1\n",
+ "Return C240(v_278,v_275,v_273,v_272,v_271,v_270,v_269,v_268,v_267,v_266,v_265,v_264,v_263,v_259,v_257,v_255,v_254,v_253,v_246,v_245,v_244,v_243,v_242,v_241)\n",
+ "Cleanup 0\n",
+ "Added tensor with data size 131072.0 KB\n",
+ "Total memory usage 136.26417541503906 MB\n",
+ "CuPy memory usage 201.0283203125 MB. Total MB: 265.2783203125\n",
+ "Added tensor with data size 65536.0 KB\n",
+ "Total memory usage 200.26416015625 MB\n",
+ "CuPy memory usage 201.0283203125 MB. Total MB: 265.2783203125\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 32768.0 KB\n",
+ "Total memory usage 104.26416015625 MB\n",
+ "CuPy memory usage 105.0283203125 MB. Total MB: 137.2783203125\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 16384.0 KB\n",
+ "Total memory usage 56.26416015625 MB\n",
+ "CuPy memory usage 57.0283203125 MB. Total MB: 137.2783203125\n",
+ "Added tensor with data size 8192.0 KB\n",
+ "Total memory usage 32.26414489746094 MB\n",
+ "CuPy memory usage 33.02783203125 MB. Total MB: 137.27783203125\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4096.0 KB\n",
+ "Total memory usage 20.264144897460938 MB\n",
+ "CuPy memory usage 21.02783203125 MB. Total MB: 137.27783203125\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 2048.0 KB\n",
+ "Total memory usage 14.264129638671875 MB\n",
+ "CuPy memory usage 15.02734375 MB. Total MB: 137.27734375\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Need compression: [v_278]\n",
+ "Chunk indices: [v_277, v_276, v_274, v_272, v_271, v_270, v_267, v_266, v_265, v_264, v_263, v_262, v_261, v_260, v_258, v_257, v_256, v_255, v_254, v_252, v_251, v_250, v_249, v_248], remove_compress: set()\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 0\n",
+ "7.519503755893795\n",
+ "Compress: Measure: 0.022s, 128.00MB -> 13.02MB (9.829 in/out ratio)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 0\n",
+ "Compression end timestamp: 3.551232 ms\n",
+ "CUDA Error: no error\n",
+ "8.043144391747434\n",
+ "Compress: Measure: 0.017s, 128.00MB -> 11.91MB (10.744 in/out ratio)\n",
+ "Return C247{v_278}(v_277,v_276,v_274,v_272,v_271,v_270,v_267,v_266,v_265,v_264,v_263,v_262,v_261,v_260,v_258,v_257,v_256,v_255,v_254,v_252,v_251,v_250,v_249,v_248)\n",
+ "Total memory usage 10.264114379882812 MB\n",
+ "Compression end timestamp: 3.323904 ms\n",
+ "CUDA Error: no error\n",
+ "CuPy memory usage 75.0263671875 MB. Total MB: 137.2763671875\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "Need compression: []\n",
+ "Chunk indices: [v_278, v_277, v_276, v_274, v_272, v_271, v_270, v_267, v_266, v_265, v_264, v_263, v_262, v_261, v_260, v_258, v_257, v_256, v_255, v_254, v_252, v_251, v_250, v_249], remove_compress: {v_278}\n",
+ "Decompress: Measure: 0.017s, 13.02MB -> 128.00MB (0.102 in/out ratio)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 1\n",
+ "Decompress: Measure: 0.004s, 11.91MB -> 128.00MB (0.093 in/out ratio)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 1\n",
+ "Return C248(v_278,v_277,v_276,v_274,v_272,v_271,v_270,v_267,v_266,v_265,v_264,v_263,v_262,v_261,v_260,v_258,v_257,v_256,v_255,v_254,v_252,v_251,v_250,v_249)\n",
+ "Cleanup 0\n",
+ "Added tensor with data size 131072.0 KB\n",
+ "Total memory usage 134.0140838623047 MB\n",
+ "CuPy memory usage 198.77587890625 MB. Total MB: 260.77587890625\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 65536.0 KB\n",
+ "Total memory usage 198.01380920410156 MB\n",
+ "CuPy memory usage 198.77490234375 MB. Total MB: 260.77490234375\n",
+ "Added tensor with data size 32768.0 KB\n",
+ "Total memory usage 102.0137939453125 MB\n",
+ "CuPy memory usage 102.7744140625 MB. Total MB: 132.7744140625\n",
+ "Added tensor with data size 16384.0 KB\n",
+ "Total memory usage 54.0137939453125 MB\n",
+ "CuPy memory usage 54.7744140625 MB. Total MB: 132.7744140625\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 8192.0 KB\n",
+ "Total memory usage 30.0137939453125 MB\n",
+ "CuPy memory usage 30.7744140625 MB. Total MB: 132.7744140625\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Need compression: [v_278]\n",
+ "Chunk indices: [v_277, v_276, v_275, v_274, v_273, v_272, v_271, v_270, v_269, v_268, v_267, v_266, v_265, v_264, v_263, v_262, v_261, v_260, v_259, v_258, v_257, v_256, v_255, v_254], remove_compress: set()\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 0\n",
+ "8.999867769038374\n",
+ "Compress: Measure: 0.021s, 128.00MB -> 10.22MB (12.521 in/out ratio)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 0\n",
+ "Compression end timestamp: 3.295232 ms\n",
+ "CUDA Error: no error\n",
+ "9.739610706496558\n",
+ "Compress: Measure: 0.017s, 128.00MB -> 9.14MB (14.001 in/out ratio)\n",
+ "Return C253{v_278}(v_277,v_276,v_275,v_274,v_273,v_272,v_271,v_270,v_269,v_268,v_267,v_266,v_265,v_264,v_263,v_262,v_261,v_260,v_259,v_258,v_257,v_256,v_255,v_254)\n",
+ "Total memory usage 14.013809204101562 MB\n",
+ "Compression end timestamp: 3.274752 ms\n",
+ "CUDA Error: no error\n",
+ "CuPy memory usage 78.7744140625 MB. Total MB: 132.7744140625\n",
+ "Need compression: []\n",
+ "Chunk indices: [v_278, v_277, v_276, v_275, v_274, v_273, v_272, v_271, v_270, v_269, v_268, v_267, v_266, v_265, v_264, v_263, v_262, v_261, v_260, v_259, v_258, v_257, v_256, v_255], remove_compress: {v_278}\n",
+ "Decompress: Measure: 0.016s, 10.22MB -> 128.00MB (0.080 in/out ratio)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 1\n",
+ "Decompress: Measure: 0.003s, 9.14MB -> 128.00MB (0.071 in/out ratio)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Cleanup 1\n",
+ "Return C254(v_278,v_277,v_276,v_275,v_274,v_273,v_272,v_271,v_270,v_269,v_268,v_267,v_266,v_265,v_264,v_263,v_262,v_261,v_260,v_259,v_258,v_257,v_256,v_255)\n",
+ "Cleanup 0\n",
+ "Added tensor with data size 131072.0 KB\n",
+ "Total memory usage 136.0137939453125 MB\n",
+ "CuPy memory usage 200.77392578125 MB. Total MB: 256.77392578125\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 65536.0 KB\n",
+ "Total memory usage 192.01377868652344 MB\n",
+ "CuPy memory usage 192.77392578125 MB. Total MB: 256.77392578125\n",
+ "(2, 2)\n",
+ "(2, 2)\n",
+ "(2, 2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 32768.0 KB\n",
+ "Total memory usage 96.01376342773438 MB\n",
+ "CuPy memory usage 96.7734375 MB. Total MB: 128.7734375\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 16384.0 KB\n",
+ "Total memory usage 48.013763427734375 MB\n",
+ "CuPy memory usage 48.7734375 MB. Total MB: 128.7734375\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 8192.0 KB\n",
+ "Total memory usage 24.013763427734375 MB\n",
+ "CuPy memory usage 24.7734375 MB. Total MB: 128.7734375\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 4096.0 KB\n",
+ "Total memory usage 12.013763427734375 MB\n",
+ "CuPy memory usage 12.7734375 MB. Total MB: 128.7734375\n",
+ "Added tensor with data size 2048.0 KB\n",
+ "Total memory usage 6.013763427734375 MB\n",
+ "CuPy memory usage 6.7734375 MB. Total MB: 128.7734375\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 1024.0 KB\n",
+ "Total memory usage 3.013763427734375 MB\n",
+ "CuPy memory usage 3.7734375 MB. Total MB: 128.7734375\n",
+ "Added tensor with data size 512.0 KB\n",
+ "Total memory usage 1.513763427734375 MB\n",
+ "CuPy memory usage 2.2734375 MB. Total MB: 128.7734375\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 256.0 KB\n",
+ "CuPy memory usage 1.5234375 MB. Total MB: 128.7734375\n",
+ "Added tensor with data size 128.0 KB\n",
+ "CuPy memory usage 1.1484375 MB. Total MB: 128.7734375\n",
+ "(2, 2)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 64.0 KB\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 32.0 KB\n",
+ "Added tensor with data size 16.0 KB\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 8.0 KB\n",
+ "Added tensor with data size 4.0 KB\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2, 2, 2)\n",
+ "Added tensor with data size 2.0 KB\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2, 2)\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2, 2)\n",
+ "(2,)\n",
+ "(2, 2, 2, 2, 2)\n",
+ "(2,)\n",
+ "(2, 2, 2, 2)\n",
+ "(2,)\n",
+ "(2, 2)\n",
+ "(2,)\n",
+ "(2,)\n",
+ "Result (9.678148e-08+3.217218e-07j)\n",
+ "Simulation result: (9.678148e-08+3.217218e-07j)\n",
+ "Elapsed 0.7305455207824707\n"
+ ]
+ }
+ ],
+ "source": [
+ "info = qtensor_simulate(prep_data,\n",
+ " backend='cupy',\n",
+ " compress='szx',\n",
+ " mem_target=24\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Benchmarking setup"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pickle\n",
+ "ex = caex.Explorer(cache=caex.caches.JobLibCache('/tmp/qtensor/bench'))\n",
+ "\n",
+ "@ex.provider\n",
+ "def circuit(circ_f, sim='qtensor'):\n",
+ " return qtensor_read_circ(circ_f)\n",
+ "\n",
+ "@ex.provider\n",
+ "def preprocess(circuit, mem_target, hardest_edges, sim_prep_args, number_edges=10, sim='qtensor'):\n",
+ " if sim_prep_args.get('prep_file') is not None:\n",
+ " with open(sim_prep_args['prep_file'], 'rb') as f:\n",
+ " prep_data = pickle.load(f)\n",
+ " print(\"Loaded prep data from\", sim_prep_args['prep_file'])\n",
+ " return prep_data\n",
+ " return qtensor_preprocess(circuit, mem_target,\n",
+ " hardest_edges=hardest_edges,\n",
+ " number_edges=number_edges,\n",
+ " after_slice=sim_prep_args.get('after_slice', 'TD-reuse'),\n",
+ " ordering_algo=sim_prep_args.get('ordering_algo', 'greedy'),\n",
+ " )\n",
+ "\n",
+ "@ex.provider\n",
+ "def sim_info(preprocess, sim_mem_target, sim_sim_args={}, sim='qtensor'):\n",
+ " res = qtensor_simulate(preprocess,\n",
+ " mem_target=sim_mem_target,\n",
+ " backend=sim_sim_args.get('backend', 'cupy'),\n",
+ " compress=sim_sim_args.get('compress', 'szx'),\n",
+ " r2r_error=sim_sim_args.get('r2r_error', 1e-3),\n",
+ " r2r_threshold=sim_sim_args.get('r2r_threshold', 1e-3),\n",
+ " )\n",
+ " #print(preprocess)\n",
+ " for i in preprocess:\n",
+ " i[2].backend = None\n",
+ " return [res]\n",
+ "\n",
+ "\n",
+ "@ex.provider\n",
+ "def memory(sim_info):\n",
+ " return sim_info[0]['memory']\n",
+ "\n",
+ "@ex.provider\n",
+ "def time(sim_info):\n",
+ " return sim_info[0]['time']\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\n",
+ "@ex.provider\n",
+ "def nvmem(sim_info):\n",
+ " return sim_info[0]['nvmemory']\n",
+ "\n",
+ "@ex.provider\n",
+ "def result(sim_info):\n",
+ " return sim_info[0]['result']['Re'] + 1j*sim_info[0]['result']['Im']\n",
+ "\n",
+ "@ex.provider\n",
+ "def total_slices(preprocess):\n",
+ " return sum([len(k[1]) for k in preprocess])\n",
+ "\n",
+ "@ex.provider\n",
+ "def width(sim_info):\n",
+ " w = max([max(s['tensors_sizes']) for s in sim_info[0]['memory_history']])\n",
+ " return w"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "8a86fd251f5c4ac0b0442245956a5b31",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ " 0%| | 0/12 [00:00\n",
+ "<xarray.DataArray (mem_target: 2, sim_mem_target: 3, sim_prep_args: 2)>\n",
+ "array([[[5.43685171e+09+0.j, 5.43685171e+09+0.j],\n",
+ " [2.75249715e+09+0.j, 2.75249715e+09+0.j],\n",
+ " [1.14188442e+09+0.j, 1.14188442e+09+0.j]],\n",
+ "\n",
+ " [[5.43685171e+09+0.j, 5.43685171e+09+0.j],\n",
+ " [2.75249715e+09+0.j, 2.75249715e+09+0.j],\n",
+ " [1.14188442e+09+0.j, 1.14188442e+09+0.j]]])\n",
+ "Coordinates:\n",
+ " varname <U12 'memory'\n",
+ " * mem_target (mem_target) int64 29 28\n",
+ " * sim_mem_target (sim_mem_target) int64 28 27 25\n",
+ " * sim_prep_args (sim_prep_args) object {'after_slice': 'TD-reuse', 'order...\n",
+ "Attributes:\n",
+ " preprocess_data: /home/danlkv/qsim/QTensor/bench/qc_simulation/data/prep...(5436851712+0j) (5436851712+0j) ... (1141884416+0j) (1141884416+0j)
array([[[5.43685171e+09+0.j, 5.43685171e+09+0.j],\n",
+ " [2.75249715e+09+0.j, 2.75249715e+09+0.j],\n",
+ " [1.14188442e+09+0.j, 1.14188442e+09+0.j]],\n",
+ "\n",
+ " [[5.43685171e+09+0.j, 5.43685171e+09+0.j],\n",
+ " [2.75249715e+09+0.j, 2.75249715e+09+0.j],\n",
+ " [1.14188442e+09+0.j, 1.14188442e+09+0.j]]])
PandasIndex
PandasIndex(Index([29, 28], dtype='int64', name='mem_target'))
PandasIndex
PandasIndex(Index([28, 27, 25], dtype='int64', name='sim_mem_target'))
PandasIndex
PandasIndex(Index([{'after_slice': 'TD-reuse', 'ordering_algo': 'rgreedy_0.02_10', 'prep_file': '/home/danlkv/qsim/QTensor/bench/qc_simulation/data/preprocess/compress/qaoa_e/3regfix_N54_p4.jsonterms_Ogreedy_M29'}, {'after_slice': 'run-again', 'ordering_algo': 'rgreedy_0.02_10', 'prep_file': '/home/danlkv/qsim/QTensor/bench/qc_simulation/data/preprocess/compress/qaoa_e/3regfix_N54_p4.jsonterms_Ogreedy_M29'}], dtype='object', name='sim_prep_args'))
- preprocess_data :
- /home/danlkv/qsim/QTensor/bench/qc_simulation/data/preprocess/compress/qaoa_e/3regfix_N54_p4.jsonterms_Ogreedy_M29
\n",
+ "
<xarray.DataArray (varname: 4, mem_target: 4)>\n",
+ "array([[2.80000000e+01, 2.80000000e+01, 2.80000000e+01, 2.80000000e+01],\n",
+ " [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+ " [7.58433536e+09, 7.58433536e+09, 7.58433536e+09, 7.58433536e+09],\n",
+ " [4.17125225e+00, 4.17125225e+00, 4.17125225e+00, 4.17125225e+00]])\n",
+ "Coordinates:\n",
+ " * varname (varname) <U12 'width' 'total_slices' 'memory' 'time'\n",
+ " * mem_target (mem_target) int64 28 27 26 25
28.0 28.0 28.0 28.0 0.0 0.0 ... 7.584e+09 4.171 4.171 4.171 4.171
array([[2.80000000e+01, 2.80000000e+01, 2.80000000e+01, 2.80000000e+01],\n",
+ " [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+ " [7.58433536e+09, 7.58433536e+09, 7.58433536e+09, 7.58433536e+09],\n",
+ " [4.17125225e+00, 4.17125225e+00, 4.17125225e+00, 4.17125225e+00]])
PandasIndex
PandasIndex(Index(['width', 'total_slices', 'memory', 'time'], dtype='object', name='varname'))
PandasIndex
PandasIndex(Index([28, 27, 26, 25], dtype='int64', name='mem_target'))