diff --git a/.ipynb_checkpoints/raremodel-nb-checkpoint.ipynb b/.ipynb_checkpoints/raremodel-nb-checkpoint.ipynb index 517891a..1d5b994 100644 --- a/.ipynb_checkpoints/raremodel-nb-checkpoint.ipynb +++ b/.ipynb_checkpoints/raremodel-nb-checkpoint.ipynb @@ -267,6 +267,34 @@ ] }, { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def G(y):\n", + " \n", + " def inner_rect_bracket(q):\n", + " return tf.log(ztf.to_complex((1+tf.sqrt(q))/(1-tf.sqrt(q)))-tf.complex(ztf.constant(0), -1*ztf.constant(np.pi))) \n", + " \n", + " def inner_right(q):\n", + " return ztf.to_complex(2 * tf.atan(1/tf.sqrt(-q)))\n", + " \n", + " big_bracket = tf.where(y > ztf.const(0.0), inner_rect_bracket(y), inner_right(y))\n", + " \n", + " return ztf.to_complex(tf.sqrt(tf.abs(y))) * big_bracket\n", + "\n", + "def h_S(m, q):\n", + " \n", + " return tf.constant(2) - G(tf.constant(1) - 4*tf.pow(m, 2) / tf.pow(q, 2))\n", + "\n", + "def h_P(m,q):\n", + " \n", + " return 2/3 + (1 - (tf.constant(1) - 4*tf.pow(m, 2) / tf.pow(q, 2))) * h_S(m,q)\n", + "\n" + ] + }, + { "cell_type": "markdown", "metadata": {}, "source": [ @@ -275,7 +303,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -287,6 +315,8 @@ " ] # the name of the parameters\n", "\n", " def _unnormalized_pdf(self, x):\n", + " \n", + " x = x.unstack_x()\n", "\n", " def jpsi_res(q):\n", " return resonance(q, _mass = self.params['jpsi_mass'], scale = self.params['jpsi_scale'], phase = self.params['jpsi_phase'], width = self.params['jpsi_width'])\n", @@ -317,7 +347,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -345,7 +375,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -379,7 +409,7 @@ "\n", "#cusp\n", "\n", - "cusp_mass, sigma_R, sigma_L, cusp_scale = 3550, 3e-7, 200, 7\n", + "cusp_mass, sigma_R, sigma_L, cusp_scale = 3550, 3e-7, 200, 0\n", "\n", "cusp_m = zfit.Parameter(\"cusp_m\", ztf.constant(cusp_mass))\n", "sig_L = zfit.Parameter(\"sig_L\", ztf.constant(sigma_L))\n", @@ -396,7 +426,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -411,7 +441,7 @@ " def cusp(q):\n", " return bifur_gauss(q, cusp_m, sig_L, sig_R, cusp_s)\n", "\n", - " funcs = jpsi_res(xq) + psi2s_res(xq)# + cusp(xq)\n", + " funcs = jpsi_res(xq) + psi2s_res(xq) + cusp(xq)\n", "\n", " vec_f = vec(xq, funcs)\n", "\n", @@ -423,19 +453,26 @@ "\n", "calcs = zfit.run(total_test_tf(x_part))\n", "\n", - "test_q = np.linspace(x_min, x_max, 1000000)\n", + "test_q = np.linspace(x_min, x_max,20000000)\n", "\n", "calcs_test = zfit.run(total_test_tf(test_q))" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.09\n" + ] + }, + { "data": { - "image/png": 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pCawoqnK6FK9Rj12kjbaX13HR1Hnsqm7g+WsU6sFkUGYCa0sU7CIhZfOuWi6eOo+qvc288NOxjO6Z4nRJ4kWDMhLZWdVAeW2j06V4hYJd5CA2lFZz8dR51De7eenasQzvnux0SeJlAzMTAFgTJL12BbvID1ixo5KLpn6DBV6ePI4h3ZKcLkl8YGBGIgBriqsdrsQ7FOwi32PhlnImTfuGmIgwXr1uPP3TE5wuSXwkLSGK1PjIoOmxa1aMyAF8traU61/Ip1tyDC9cM5ZuyTFOlyQ+NjAjkTUl6rGLBKV3lhdz7XOL6J0az6vXjVeoh4iBGQmsLamm2eV2upTDpmAX2c+rC7dzy4zFDM9OZsbkcaTGRzldknSQgZmJNDS72bK7zulSDpuCXcTjqa82c/fry5nQN5XnrhlDUkyE0yVJBxqYETwzYxTsEvKstfx9zjoenL2KU3MzePLKPGIjdfkp1PTtGk9YJxMUM2P0v1dCmtttefCdVTz99RYuHJ3Nn84bSniY+juhKDoijJ5dYllfqmAXCVjNLje/nFXAzPxCrpqQw32nD6ZTJ+N0WeKgvmnxrC+tcbqMw6auiYSk+iYXN720mJn5hdx+Qj9+c4ZCXVqGY7burqOxObBnxijYJeRU7m3Z9eiDlTv57ZmDuf2E/hijUBfolx6Py23ZurvW6VIOi4JdQsrOqnounjqPJdv28I9JI7lqQi+nSxI/0jetZWbMhgAfjtEYu4SMTWU1XDF9AeW1jUz/yRH8qF+a0yWJn+nTNQ5QsIsEhGXbK7jqmYVAy2Jew7K1QqP8r9jIcLKSY9hQpmAX8Wtfri/juufzSYmL5Lmrx9A7Ld7pksSP9ekaH/A99oOOsRtjoo0xC4wxy4wxK40xD3REYSLe8NbSHVz9zEJ6pMQy64YjFepyUH3T4tlYVoPbbZ0u5ZC15eJpA3CctXY4MAI4xRgzzrdliRy+6V9t5raXlzKqR2devX48XROjnS5JAkDfrvHUN7nZUbHX6VIO2UGD3bZo/b0kwvMRuD/KJOhZa/nz+2v43exVnDIkg2evHkNitNZ9kbbpl97yW10gD8e0abqjMSbMGLMUKAXmWGvnH+A5k40xi4wxi8rKyrxdp0ibNDS7uP2Vpfz7s41cMrYHj106iuiIMKfLkgDSNy1Egt1a67LWjgCygTHGmNwDPGeatTbPWpuXlqZpZNLxKuuauHL6At5aWsRdJw/gD+fkEqa7SaWdOsdF0jk2gk27AvcmpXbNirHWVhhjPgNOAVb4pCKRQ1C4p46rnl7Ilt21PDpxBGePyHK6JAlgOalxbAngYG/LrJg0Y0yy53EMcAKwxteFibTVih2VnPv4XEqq6nnu6rEKdTlsvbrEsSWAlxVoy1BMJvCpMWY5sJCWMfbZvi1LpG0+XVvKRVPnERnWiddvOJLxfbo4XZIEgZzUOIor69nb6HK6lENy0KEYa+1yYGQH1CLSLi/N38Z9b61gYEYCT//kCE1nFK/JSW1ZWmBreS0DMxIdrqb9tAiYBBxrLX/5YA33vlHAj/ql8up1mqMu3tWrS0uwB+o4u5YUkIBS3+Til68v582lRUwa050Hz87VjkfidTmpsQABu7G1gl0Cxq6aBq57Pp/8rXu46+QB3HhMH62jLj6REB1BanykeuwivrRuZzVXP7OQXTUNPH7pKE4bmul0SRLkenaJY3OABrt+hxW/99naUs57fC6NzW5evW68Ql06RE4AT3lUsItfe+brzftWZ3zr5glaR106TK/UWHZWNVDX2Ox0Ke2moRjxS80uNw/8ZxXPf7OVEwen88jFI4iL0n9X6TitUx637KpjcLfAmvKod4r4ncq9Tdz80mK+XL+L637cm1+cPJBOWvNFOlhO65TH3bUKdpHDsW13HVc/u5Atu2p56PxhXHREd6dLkhDVy9NjD8QLqAp28RtzN+zixpcWA/D8NWO1PIA4Ki4qnNT4SAr3BN5cdgW7OM5ayzNzt/D7d1bTOzWOJ67I2ze+KeKk7M6xbCtXsIu0S32Ti1+/uYKZ+YWcNDidhy8eQbwukoqf6J4Sy7LtFU6X0W56B4ljdlbVc93z+SzdXsFtx/fjtuP76SKp+JXunWN4r6AYl9sG1KYtCnZxxOJte7j++XxqGpqZctkoTsnVTUfif3qkxNLsthRX7iW7c6zT5bSZblCSDvfqou1MnPoN0RFhzLrxSIW6+K3uKS1hvr18r8OVtI+CXTpMk8vN/W+v5O6ZyxnTK4W3b54QkGtdS+jo3rk12APrAqqGYqRDlFU3cMuMxXyzqZxrjurFPacO1HK74vcyk6PpZGB7gE15VLCLz+Vv3cONL+ZTUdfE3y4czvmjs50uSaRNIsI6kZkUox67SCtrLc/N28rv31lFZlIMs248giHdkpwuS6RdeqTEsn1PYI2xK9jFJ+oam7l3VgFvLi3i+IFdefiiESTFRjhdlki7dU+J4dO1ZU6X0S4KdvG6zbtqueGFfNburObOE/tz07F9NT9dAlb3zrGUVTdQ3+QiOiLM6XLaRMEuXvXhyhLufHUZYWGGZ64aw4/7pzldkshhaZ3yWLinjr5dExyupm0U7OIVLrflbx+u5fHPNjIsO4nHLx0VUDd0iHyf7ikxQMtcdgW7hIyy6gZuf2UJX2/YzaQx3fntmUMC5ldWkYPZd5NSAE15VLDLYZm7YRe3vbKU6vomrZ8uQSktPoroiE5s261glyDnclv++cl6Hv14Pb1T43jhmrEMyAiMX1NF2sMYQ7fkGIoqA2fKo4Jd2q20up7bX17K3I27OW9kFg+ek6v9SCWoZSXHsKOi3uky2uyg70ZjTHfgOSADcAPTrLWP+row8U9fb9jFbS8vpaahiYcuGMaFo7MxRlMZJbh1S4phTUmp02W0WVu6Wc3AndbaxcaYBCDfGDPHWrvKx7WJH3G5LY9+vJ5/frKePmnxvHTtWPqna+hFQkNW5xjKqhtoaHYRFe7/EwMOGuzW2mKg2PO42hizGsgCFOwhorSqntteXsq8Tbs5f1Q2D54zhNhIDb1I6OiW3DLlsaSynp5d/H/bxna9O40xOcBIYL4vihH/8+maUu6auYyahmb+csEwLszTrBcJPd2SowHYUbE3uILdGBMPvA7cbq2tOsD3JwOTAXr06OG1AsUZ9U0u/vz+Gp7+egsDMxJ46dpxGnqRkJXl6bEXBcgF1DYFuzEmgpZQf9FaO+tAz7HWTgOmAeTl5VmvVSgdbv3Oam6ZsYQ1JdX85MgcfnnqQN1wJCEtI6mlx15UERhTHtsyK8YATwGrrbUP+74kcYq1lhfmb+P3s1cRHxXO9J/kcdzAdKfLEnFcVHgYaQlR7AiQ5Xvb0mOfAFwOFBhjlnqO3Wutfdd3ZUlHK69t5O6Zy/lo9U6O7p/GXy8cRteEaKfLEvEbgXSTUltmxXwFaKJyEPt6wy5+9spSKuqauO+MwVx1ZI6W2RX5jqzkaNaUVDtdRptozloIa2x28/CcdUz9YiO9U+OY/pMjyM3SDkciB9ItKYZP1pRirfX7m/IU7CFqbUk1t7+ylNXFVVwytgf3nT6YmEhdIBX5Pt2SY6hvcrOnromUuEiny/lBCvYQ43JbnvpqE3/9YB2JMeE8cUUeJw7WBVKRg+m2b8rjXgW7+I/t5XXc+doyFmwu56TB6fzpvKF0iY9yuiyRgNA6l31HxV6/H7JUsIcAay2vLSrkgf+sxBjDXy4YxgVavEukXVrvPg2EuewK9iBXVt3APbMK+Gj1Tsb1TuGvFw7XlnUihyAlLpKo8E4KdnHWBytLuHdWAdUNzfz69EFcPaGXpjGKHCJjDFnJMQGxrICCPQhV1jXxwOyVzFq8gyHdEplx8Qit8yLiBd2SYyhUj1062kerdnLvGwXsrm3k5mP7cuvx/YgM7+R0WSJBITMpmvXry5wu46AU7EFiT20jD/xnJW8uLWJgRgJPXXkEQ7P9+8q9SKDJSIqmrLqBZpeb8DD/7TAp2IPABytL+NUbK6ioa+TW4/tx87F91UsX8YGMpGjcFspqGshMinG6nO+lYA9g5bWN/PbtlfxnWRGDMxN59uojGNJNvXQRX8n0LN9bXFmvYBfve7egmPveXEFVfRN3nNifG47pQ4Qf/2ooEgzSE1uCfWelf8+MUbAHmF01Dfz2rZW8U1BMblYiL144loEZiU6XJRISWnvpxQp28QZrLTPzC/nDu6upa3Bx18kDmHx0b/XSRTpQ59gIIsM7UVKlYJfDtGVXLfe+UcDcjbvJ69mZP503lH6aly7S4YwxZCRGU6IeuxyqJpebJ77cxKMfrScyrBN/ODeXSUf00N2jIg7KSFKwyyFasm0P98wqYE1JNafmZnD/WUP2XbgREedkJkWzeNsep8v4QQp2P1PT0MxfP1jLs/O2kJ4QzbTLR3PSkAynyxIRj4zEaHZWNvj1TkoKdj/y8eqd3PfmCoqr6rl8XE/uOnkACdERTpclIvvJSIqm0eWmvLbRb/czULD7gaKKvTw4exXvrSihf3o8My85ktE9OztdlogcwP43KSnY5X80udw8/fVmHvloPS635ecn9Wfy0X20HICIH9t3k1JVvd/upKRgd8iCzeX8+s0C1u2s4fiBXbn/rCF0T9EGGCL+LhBuUlKwd7BdNQ386d01vL64kKzkGG0mLRJg0hKiCOtk/HrKo4K9g7jclhkLtvHQ+2vY2+TixmP6cPNxfYmN1D+BSCAJ62RIi4/y67tPlSodoKCwkl+/WcCywkrG9+7Cg+cMoW9X3TkqEqj8/SYlBbsPldc28rcP1/LSgm10iYvi0YkjOGt4N7+d+yoibZOZFM26ndVOl/G9FOw+0Oxy8+L8bTw8Zx01Dc1cOT6HO07qT6LmpIsEhfTEaL5cv8vpMr7XQYPdGDMdOAMotdbm+r6kwDZ34y4eeHsVa3dWM6FvF35zxhAGZGjYRSSYZCZFU9PQTHV9k1/eRNiWHvszwL+A53xbSmDbXl7HH99dzXsrSsjuHMOUy0Zz8pB0DbuIBKEMz01KJZX1gRns1tovjDE5vi8lMO1tdPHvzzcy9fONdDKGO0/sz7VH9yY6Iszp0kTER1rnspdU1fvlEtpeG2M3xkwGJgP06NHDW6f1W9Za3iko5o/vrKaosp4zh3fjnlMH0i3Zf/dBFBHvyEj8dlkBf+S1YLfWTgOmAeTl5VlvndcfLS+s4PfvrGbB5nIGZybyyMSRjOmV4nRZItJBuia2rBHjr1MeNSumHXZU7OUv76/hzaVFpMZH8odzc5l4RA/CtPGFSEiJjgijS1xk8PfYg1l1fROPf7aRp77ajAFuOrYP1/+4j19eNBGRjpGRFM1OP737tC3THWcAxwCpxphC4LfW2qd8XZg/aHa5mbFwO4/MWcfu2kbOHZnFz08eQJbG0UVCXmZSNDsqAjTYrbWTOqIQf2Kt5ZM1pfzx3dVsLKtlTK8Unj59EMOyk50uTUT8REZSNIu2+ucWeRqK+Y4VOyr547urmbtxN71S45h6+WhOGqz56CLy3zKTYqioa2Jvo4uYSP+a3qxg99hQWsPf56zjnYJikmMj+O2Zg7l0bE9teiEiB9Q65bGkqp5eqXEOV/PfQj7YC/fU8Y+P1zMzv5DoiDBuPa4vPz26t9Z1EZEf9O0WeXsV7P6irLqBxz7dwEvzt4GBqyb04oZj+pDqp3sYioh/yfRMovDHuewhF+yVe5uY9sVGpn+1hUaXmwtHZ3Pr8f10x6iItIs/330aMsFe19jMM3O3MOWzjVTVN3PGsEzuOLE/vdPinS5NRAJQTGQYybERFFfudbqU/xH0wd7Y7GbGgm3885MN7Kpp4LiBXbnzpP4M6eafu4uLSODISPTPnZSCNthdbssbS3bwyEfrKNyzlzG9Uphy2SjycrSmi4h4R2ZStIZiOoK1lvdXlPC3OevYUFpDblYifzh3KEf3S9VcdBHxqszkGJYXVjpdxv8ImmC31vLl+l385YO1FOyopE9aHP++dBSn5GYo0EXEJzITo9ld20h9k8uv9mAIimBfvG0Pf35vDfM3l5OVHMNfLhjGuSOzCA/TzUUi4jutOyntrKqnZxf/mcse0MG+obSah95fy4erdpIaH8n9Zw5m0tgeRIX7z09IP/M7AAAHxklEQVROEQlerTspFVcq2A9bSWU9D89Zy8z8QmIjw7njxP5cc1Qv4qIC8uWISIDaf+9TfxJQSdjY7Obprzfz6MfraXZZrprQi5uO7UtKXKTTpYlICPp2WQEF+yFZXljBHa8uY0NpDScM6spvzhhCjy6xTpclIiEsLiqcxOhwSvzsJiW/D3ZrLVM+38TfPlxLWkIUT12Zx/GD0p0uS0QEaBlnL1KPve0am9388vXlzFqyg9OHZvLHc4eSFKtVF0XEf2Qk+d/dp34b7C635fZXlvBuQQl3ntifm4/rq/noIuJ3MpOiWVlU5XQZ/8Vvg/2vH67l3YISfn36IH76o95OlyMickCZSTHsqmmgsdntNxvz+EcV37FwSzlTPt/IpDHdFeoi4tcy97tJyV/4XbBba3lw9iq6JcXw69MHO12OiMgP2jeXXcH+/b5Yv4vlhZXcdnw/3XAkIn6vtcdeVOE/Ux79Lthn5hfSOTaCc0ZmOV2KiMhBZXVuWVZge3mdw5V8y6+Cvb7JxZxVJZwxrJvfXIQQEfkhsZHhpCdGsWW3gv2AlhdWUt/k5uj+aU6XIiLSZjld4ti6u9bpMvbxq2BftLUcgNE9OztciYhI2+V0iVOP/ftsKqslPTFKi3qJSEDpmRpLWXUDtQ3NTpcC+Fmwbyuvo0eKFvYSkcCS41mLfauf9NrbFOzGmFOMMWuNMRuMMb/0VTGlVfVkeBauFxEJFK3BvqGsxuFKWhw02I0xYcBjwKnAYGCSMcYndw7VNrqIi9TuRyISWPqlxxMd0Ykl2/Y4XQrQth77GGCDtXaTtbYReBk42xfF7G10EaNgF5EAExHWiWFZyczdsBtrrdPltCnYs4Dt+31d6Dn2X4wxk40xi4wxi8rKyg6pmBMGdWVoVtIh/VkRESdNHNOdcb1TaGh2O11Km1Z3PNBauf/zI8laOw2YBpCXl3dIP7IemTjyUP6YiIjjzhuVzXmjsp0uA2hbj70Q6L7f19lAkW/KERGRw9WWYF8I9DPG9DLGRAITgbd9W5aIiByqgw7FWGubjTE3Ax8AYcB0a+1Kn1cmIiKHpE3r4lpr3wXe9XEtIiLiBX5156mIiBw+BbuISJBRsIuIBBkFu4hIkDG+uP3VGFMG1AK7vH7ywJOK2qGV2uJbaosWaodvDbDWJnjjRD7ZLdpam2aMWWStzfPF+QOJ2uFbaotvqS1aqB2+ZYxZ5K1zaShGRCTIKNhFRIKML4N9mg/PHUjUDt9SW3xLbdFC7fAtr7WFTy6eioiIczQUIyISZBTsIiJBxuvB3lEbXzvJGDPdGFNqjFmx37EUY8wcY8x6z+fOnuPGGPMPT3ssN8aM2u/PXOl5/npjzJVOvJbDYYzpboz51Biz2hiz0hhzm+d4KLZFtDFmgTFmmactHvAc72WMme95Xa94lr7GGBPl+XqD5/s5+53rHs/xtcaYk515RYfHGBNmjFlijJnt+TpU22GLMabAGLO0dTpjh7w/rLVe+6BlWd+NQG8gElgGDPbm3+EPH8DRwChgxX7HHgJ+6Xn8S+DPnsenAe/RshPVOGC+53gKsMnzubPncWenX1s72yETGOV5nACso2XD81BsCwPEex5HAPM9r/FVYKLn+BTgBs/jG4EpnscTgVc8jwd73jdRQC/P+ynM6dd3CO1xB/ASMNvzdai2wxYg9TvHfP7+8PaLGA98sN/X9wD3ON24PvoHy/lOsK8FMj2PM4G1nsdTgUnffR4wCZi63/H/el4gfgBvASeGelsAscBiYCwtd1WGe47ve3/Qsr/BeM/jcM/zzHffM/s/L1A+aNll7WPgOGC253WFXDt46j5QsPv8/eHtoZg2bXwdpNKttcUAns9dPce/r02Cqq08v0KPpKWnGpJt4Rl+WAqUAnNo6WVWWGubPU/Z/3Xte82e71cCXQiOtngEuBto3dW5C6HZDtCyP/SHxph8Y8xkzzGfvz+8vaRAmza+DjHf1yZB01bGmHjgdeB2a22VMQd6aS1PPcCxoGkLa60LGGGMSQbeAAYd6Gmez0HZFsaYM4BSa22+MeaY1sMHeGpQt8N+Jlhri4wxXYE5xpg1P/Bcr7WFt3vsobzx9U5jTCaA53Op5/j3tUlQtJUxJoKWUH/RWjvLczgk26KVtbYC+IyWcdJkY0xrB2r/17XvNXu+nwSUE/htMQE4yxizBXiZluGYRwi9dgDAWlvk+VxKyw/7MXTA+8PbwR7KG1+/DbRerb6SlvHm1uNXeK54jwMqPb9+fQCcZIzp7LkqfpLnWMAwLV3zp4DV1tqH9/tWKLZFmqenjjEmBjgBWA18Clzgedp326K1jS4APrEtA6hvAxM9s0V6Af2ABR3zKg6ftfYea222tTaHlvf/J9baSwmxdgAwxsQZYxJaH9Py/3oFHfH+8MHFgtNomR2xEfiV0xcvfHRBZAZQDDTR8tP0GlrGBT8G1ns+p3iea4DHPO1RAOTtd56rgQ2ej6ucfl2H0A5H0fIr4XJgqefjtBBti2HAEk9brAB+4znem5ZA2gC8BkR5jkd7vt7g+X7v/c71K08brQVOdfq1HUabHMO3s2JCrh08r3mZ52Nlax52xPtDSwqIiAQZ3XkqIhJkFOwiIkFGwS4iEmQU7CIiQUbBLiISZBTsIiJBRsEuIhJk/h+viDsvJqipOwAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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" ] @@ -449,9 +486,10 @@ "source": [ "# plt.plot(x_part, calcs, '.')\n", "plt.plot(test_q, calcs_test)\n", - "# plt.ylim(0, 0.0000007)\n", - "# plt.xlim(3000, 3750)\n", - "plt.savefig('test.png')" + "plt.ylim(3.5e-7, 5.5e-7)\n", + "plt.xlim(3050, 3150)\n", + "plt.savefig('test.png')\n", + "print(jpsi_width)" ] }, { @@ -463,7 +501,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -484,38 +522,60 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 10, "metadata": {}, "outputs": [ { - "ename": "ResourceExhaustedError", - "evalue": "OOM when allocating tensor with shape[380152,380152] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_5/sample/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n\nCaused by op 'ZPDF_5/sample/while/Greater_1', defined at:\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 193, in _run_module_as_main\n \"__main__\", mod_spec)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 85, in _run_code\n exec(code, run_globals)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel_launcher.py\", line 16, in \n app.launch_new_instance()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\traitlets\\config\\application.py\", line 658, in launch_instance\n app.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 505, in start\n self.io_loop.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 148, in start\n self.asyncio_loop.run_forever()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 539, in run_forever\n self._run_once()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 1775, in _run_once\n handle._run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\events.py\", line 88, in _run\n self._context.run(self._callback, *self._args)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 690, in \n lambda f: self._run_callback(functools.partial(callback, future))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 743, in _run_callback\n ret = callback()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 781, in inner\n self.run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 742, in run\n yielded = self.gen.send(value)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 357, in process_one\n yield gen.maybe_future(dispatch(*args))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 267, in dispatch_shell\n yield gen.maybe_future(handler(stream, idents, msg))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in execute_request\n user_expressions, allow_stdin,\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 294, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 536, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2848, in run_cell\n raw_cell, store_history, silent, shell_futures)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2874, in _run_cell\n return runner(coro)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 67, in _pseudo_sync_runner\n coro.send(None)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3049, in run_cell_async\n interactivity=interactivity, compiler=compiler, result=result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3220, in run_ast_nodes\n if (yield from self.run_code(code, result)):\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3296, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)\n File \"\", line 3, in \n total_f.sample(n=nevents)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 871, in sample\n sample = self._single_hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 877, in _single_hook_sample\n return self._hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basepdf.py\", line 489, in _hook_sample\n samples = super()._hook_sample(limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 880, in _hook_sample\n return self._norm_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 884, in _norm_sample\n return self._limits_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 887, in _limits_sample\n return self._call_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 901, in _call_sample\n return self._fallback_sample(n=n, limits=limits)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 934, in _fallback_sample\n sample_and_weights_factory=self._sample_and_weights)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 174, in accept_reject_sample\n back_prop=False)[1] # backprop not needed here\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3556, in while_loop\n return_same_structure)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3087, in BuildLoop\n pred, body, original_loop_vars, loop_vars, shape_invariants)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3022, in _BuildLoop\n body_result = body(*packed_vars_for_body)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 154, in sample_body\n take_or_not = probabilities > random_thresholds\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\gen_math_ops.py\", line 3922, in greater\n \"Greater\", x=x, y=y, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py\", line 788, in _apply_op_helper\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 507, in new_func\n return func(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 3300, in create_op\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 1801, in __init__\n self._traceback = tf_stack.extract_stack()\n\nResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[380152,380152] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_5/sample/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mResourceExhaustedError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_call\u001b[1;34m(self, fn, *args)\u001b[0m\n\u001b[0;32m 1333\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1334\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1335\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mOpError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_run_fn\u001b[1;34m(feed_dict, fetch_list, target_list, options, run_metadata)\u001b[0m\n\u001b[0;32m 1318\u001b[0m return self._call_tf_sessionrun(\n\u001b[1;32m-> 1319\u001b[1;33m options, feed_dict, fetch_list, target_list, run_metadata)\n\u001b[0m\u001b[0;32m 1320\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_call_tf_sessionrun\u001b[1;34m(self, options, feed_dict, fetch_list, target_list, run_metadata)\u001b[0m\n\u001b[0;32m 1406\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_session\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfeed_dict\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfetch_list\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtarget_list\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1407\u001b[1;33m run_metadata)\n\u001b[0m\u001b[0;32m 1408\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m: OOM when allocating tensor with shape[380152,380152] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[{{node ZPDF_5/sample/while/Greater_1}}]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mnevents\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1000\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mtotal_f\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnevents\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\u001b[0m in \u001b[0;36msample\u001b[1;34m(self, n, limits, name)\u001b[0m\n\u001b[0;32m 870\u001b[0m \u001b[0mlimits\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_check_input_limits\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlimits\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlimits\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcaller_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnone_is_error\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 871\u001b[0m \u001b[0msample\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_single_hook_sample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlimits\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlimits\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 872\u001b[1;33m \u001b[0msample_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSampleData\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfrom_sample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mspace\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 873\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 874\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0msample_data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\data.py\u001b[0m in \u001b[0;36mfrom_sample\u001b[1;34m(cls, sample, obs, name, weights)\u001b[0m\n\u001b[0;32m 528\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mfrom_sample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msample\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mtf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTensor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobs\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mztyping\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mObsTypeInput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mweights\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 529\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mzfit\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 530\u001b[1;33m \u001b[0msample\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzfit\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 531\u001b[0m sample_holder = tf.Variable(initial_value=sample, trainable=False, collections=(\"zfit_sample_cache\",),\n\u001b[0;32m 532\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"sample_data_holder_{}\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_cache_counting\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\util\\execution.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 75\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 76\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 77\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msess\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 78\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 79\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mcreate_session\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36mrun\u001b[1;34m(self, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 927\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 928\u001b[0m result = self._run(None, fetches, feed_dict, options_ptr,\n\u001b[1;32m--> 929\u001b[1;33m run_metadata_ptr)\n\u001b[0m\u001b[0;32m 930\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mrun_metadata\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 931\u001b[0m \u001b[0mproto_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtf_session\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTF_GetBuffer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrun_metadata_ptr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_run\u001b[1;34m(self, handle, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 1150\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mfinal_fetches\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mfinal_targets\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mfeed_dict_tensor\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1151\u001b[0m results = self._do_run(handle, final_targets, final_fetches,\n\u001b[1;32m-> 1152\u001b[1;33m feed_dict_tensor, options, run_metadata)\n\u001b[0m\u001b[0;32m 1153\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1154\u001b[0m \u001b[0mresults\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_run\u001b[1;34m(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 1326\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mhandle\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1327\u001b[0m return self._do_call(_run_fn, feeds, fetches, targets, options,\n\u001b[1;32m-> 1328\u001b[1;33m run_metadata)\n\u001b[0m\u001b[0;32m 1329\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1330\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_do_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_prun_fn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhandle\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfeeds\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfetches\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_call\u001b[1;34m(self, fn, *args)\u001b[0m\n\u001b[0;32m 1346\u001b[0m \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1347\u001b[0m \u001b[0mmessage\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0merror_interpolation\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minterpolate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_graph\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1348\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnode_def\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmessage\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1349\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1350\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_extend_graph\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m: OOM when allocating tensor with shape[380152,380152] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_5/sample/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n\nCaused by op 'ZPDF_5/sample/while/Greater_1', defined at:\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 193, in _run_module_as_main\n \"__main__\", mod_spec)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 85, in _run_code\n exec(code, run_globals)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel_launcher.py\", line 16, in \n app.launch_new_instance()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\traitlets\\config\\application.py\", line 658, in launch_instance\n app.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 505, in start\n self.io_loop.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 148, in start\n self.asyncio_loop.run_forever()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 539, in run_forever\n self._run_once()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 1775, in _run_once\n handle._run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\events.py\", line 88, in _run\n self._context.run(self._callback, *self._args)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 690, in \n lambda f: self._run_callback(functools.partial(callback, future))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 743, in _run_callback\n ret = callback()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 781, in inner\n self.run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 742, in run\n yielded = self.gen.send(value)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 357, in process_one\n yield gen.maybe_future(dispatch(*args))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 267, in dispatch_shell\n yield gen.maybe_future(handler(stream, idents, msg))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in execute_request\n user_expressions, allow_stdin,\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 294, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 536, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2848, in run_cell\n raw_cell, store_history, silent, shell_futures)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2874, in _run_cell\n return runner(coro)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 67, in _pseudo_sync_runner\n coro.send(None)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3049, in run_cell_async\n interactivity=interactivity, compiler=compiler, result=result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3220, in run_ast_nodes\n if (yield from self.run_code(code, result)):\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3296, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)\n File \"\", line 3, in \n total_f.sample(n=nevents)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 871, in sample\n sample = self._single_hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 877, in _single_hook_sample\n return self._hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basepdf.py\", line 489, in _hook_sample\n samples = super()._hook_sample(limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 880, in _hook_sample\n return self._norm_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 884, in _norm_sample\n return self._limits_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 887, in _limits_sample\n return self._call_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 901, in _call_sample\n return self._fallback_sample(n=n, limits=limits)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 934, in _fallback_sample\n sample_and_weights_factory=self._sample_and_weights)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 174, in accept_reject_sample\n back_prop=False)[1] # backprop not needed here\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3556, in while_loop\n return_same_structure)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3087, in BuildLoop\n pred, body, original_loop_vars, loop_vars, shape_invariants)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3022, in _BuildLoop\n body_result = body(*packed_vars_for_body)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 154, in sample_body\n take_or_not = probabilities > random_thresholds\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\gen_math_ops.py\", line 3922, in greater\n \"Greater\", x=x, y=y, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py\", line 788, in _apply_op_helper\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 507, in new_func\n return func(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 3300, in create_op\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 1801, in __init__\n self._traceback = tf_stack.extract_stack()\n\nResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[380152,380152] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_5/sample/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n" + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:From c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:98: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n", + "Instructions for updating:\n", + "Use tf.cast instead.\n" ] } ], "source": [ - "nevents = 1000\n", + "nevents = 440000\n", "\n", - "total_f.sample(n=nevents)" + "samp = total_f.sample(n=nevents)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sam = samp.unstack_x()\n", + "\n", + "sam = zfit.run(sam)\n", + "\n", + "bins = int((x_max-x_min)/7)\n", + "\n", + "calcs = zfit.run(total_test_tf(samp))\n", + "\n", + "plt.hist(sam, bins = bins, range = (x_min,x_max))\n", + "\n", + "# plt.plot(sam, calcs, '.')\n", + "# plt.plot(test_q, calcs_test)\n", + "# plt.ylim(0, 0.0000007)\n", + "# plt.xlim(3000, 3750)\n", + "\n", + "plt.savefig('test.png')" ] }, { @@ -527,30 +587,1622 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": {}, "outputs": [ { - "ename": "ResourceExhaustedError", - "evalue": "OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_4/create_sampler/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n\nCaused by op 'ZPDF_4/create_sampler/while/Greater_1', defined at:\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 193, in _run_module_as_main\n \"__main__\", mod_spec)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 85, in _run_code\n exec(code, run_globals)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel_launcher.py\", line 16, in \n app.launch_new_instance()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\traitlets\\config\\application.py\", line 658, in launch_instance\n app.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 505, in start\n self.io_loop.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 148, in start\n self.asyncio_loop.run_forever()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 539, in run_forever\n self._run_once()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 1775, in _run_once\n handle._run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\events.py\", line 88, in _run\n self._context.run(self._callback, *self._args)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 690, in \n lambda f: self._run_callback(functools.partial(callback, future))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 743, in _run_callback\n ret = callback()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 781, in inner\n self.run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 742, in run\n yielded = self.gen.send(value)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 357, in process_one\n yield gen.maybe_future(dispatch(*args))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 267, in dispatch_shell\n yield gen.maybe_future(handler(stream, idents, msg))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in execute_request\n user_expressions, allow_stdin,\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 294, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 536, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2848, in run_cell\n raw_cell, store_history, silent, shell_futures)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2874, in _run_cell\n return runner(coro)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 67, in _pseudo_sync_runner\n coro.send(None)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3049, in run_cell_async\n interactivity=interactivity, compiler=compiler, result=result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3214, in run_ast_nodes\n if (yield from self.run_code(code, result)):\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3296, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)\n File \"\", line 1, in \n sampler = total_f.create_sampler(n=nevents)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 814, in create_sampler\n limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 835, in _create_sampler_tensor\n sample = self._single_hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 877, in _single_hook_sample\n return self._hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basepdf.py\", line 489, in _hook_sample\n samples = super()._hook_sample(limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 880, in _hook_sample\n return self._norm_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 884, in _norm_sample\n return self._limits_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 887, in _limits_sample\n return self._call_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 901, in _call_sample\n return self._fallback_sample(n=n, limits=limits)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 934, in _fallback_sample\n sample_and_weights_factory=self._sample_and_weights)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 174, in accept_reject_sample\n back_prop=False)[1] # backprop not needed here\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3556, in while_loop\n return_same_structure)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3087, in BuildLoop\n pred, body, original_loop_vars, loop_vars, shape_invariants)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3022, in _BuildLoop\n body_result = body(*packed_vars_for_body)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 154, in sample_body\n take_or_not = probabilities > random_thresholds\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\gen_math_ops.py\", line 3922, in greater\n \"Greater\", x=x, y=y, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py\", line 788, in _apply_op_helper\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 507, in new_func\n return func(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 3300, in create_op\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 1801, in __init__\n self._traceback = tf_stack.extract_stack()\n\nResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_4/create_sampler/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mResourceExhaustedError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_call\u001b[1;34m(self, fn, *args)\u001b[0m\n\u001b[0;32m 1333\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1334\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1335\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mOpError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_run_fn\u001b[1;34m(feed_dict, fetch_list, target_list, options, run_metadata)\u001b[0m\n\u001b[0;32m 1318\u001b[0m return self._call_tf_sessionrun(\n\u001b[1;32m-> 1319\u001b[1;33m options, feed_dict, fetch_list, target_list, run_metadata)\n\u001b[0m\u001b[0;32m 1320\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_call_tf_sessionrun\u001b[1;34m(self, options, feed_dict, fetch_list, target_list, run_metadata)\u001b[0m\n\u001b[0;32m 1406\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_session\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfeed_dict\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfetch_list\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtarget_list\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1407\u001b[1;33m run_metadata)\n\u001b[0m\u001b[0;32m 1408\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m: OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[{{node ZPDF_4/create_sampler/while/Greater_1}}]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;31m# param.set_value(initial_value)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0msampler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnevents\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 8\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[1;31m# Randomise initial values\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\data.py\u001b[0m in \u001b[0;36mresample\u001b[1;34m(self, param_values, n)\u001b[0m\n\u001b[0;32m 624\u001b[0m \u001b[1;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Cannot set a new `n` if not a Tensor-like object was given\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 625\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn_samples\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msession\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msess\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 626\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msess\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msample_holder\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minitializer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 627\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initial_resampled\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 628\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36mrun\u001b[1;34m(self, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 927\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 928\u001b[0m result = self._run(None, fetches, feed_dict, options_ptr,\n\u001b[1;32m--> 929\u001b[1;33m run_metadata_ptr)\n\u001b[0m\u001b[0;32m 930\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mrun_metadata\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 931\u001b[0m \u001b[0mproto_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtf_session\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTF_GetBuffer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrun_metadata_ptr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_run\u001b[1;34m(self, handle, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 1150\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mfinal_fetches\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mfinal_targets\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mfeed_dict_tensor\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1151\u001b[0m results = self._do_run(handle, final_targets, final_fetches,\n\u001b[1;32m-> 1152\u001b[1;33m feed_dict_tensor, options, run_metadata)\n\u001b[0m\u001b[0;32m 1153\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1154\u001b[0m \u001b[0mresults\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_run\u001b[1;34m(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 1326\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mhandle\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1327\u001b[0m return self._do_call(_run_fn, feeds, fetches, targets, options,\n\u001b[1;32m-> 1328\u001b[1;33m run_metadata)\n\u001b[0m\u001b[0;32m 1329\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1330\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_do_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_prun_fn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhandle\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfeeds\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfetches\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_call\u001b[1;34m(self, fn, *args)\u001b[0m\n\u001b[0;32m 1346\u001b[0m \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1347\u001b[0m \u001b[0mmessage\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0merror_interpolation\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minterpolate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_graph\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1348\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnode_def\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmessage\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1349\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1350\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_extend_graph\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m: OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_4/create_sampler/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n\nCaused by op 'ZPDF_4/create_sampler/while/Greater_1', defined at:\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 193, in _run_module_as_main\n \"__main__\", mod_spec)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 85, in _run_code\n exec(code, run_globals)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel_launcher.py\", line 16, in \n app.launch_new_instance()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\traitlets\\config\\application.py\", line 658, in launch_instance\n app.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 505, in start\n self.io_loop.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 148, in start\n self.asyncio_loop.run_forever()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 539, in run_forever\n self._run_once()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 1775, in _run_once\n handle._run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\events.py\", line 88, in _run\n self._context.run(self._callback, *self._args)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 690, in \n lambda f: self._run_callback(functools.partial(callback, future))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 743, in _run_callback\n ret = callback()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 781, in inner\n self.run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 742, in run\n yielded = self.gen.send(value)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 357, in process_one\n yield gen.maybe_future(dispatch(*args))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 267, in dispatch_shell\n yield gen.maybe_future(handler(stream, idents, msg))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in execute_request\n user_expressions, allow_stdin,\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 294, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 536, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2848, in run_cell\n raw_cell, store_history, silent, shell_futures)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2874, in _run_cell\n return runner(coro)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 67, in _pseudo_sync_runner\n coro.send(None)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3049, in run_cell_async\n interactivity=interactivity, compiler=compiler, result=result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3214, in run_ast_nodes\n if (yield from self.run_code(code, result)):\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3296, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)\n File \"\", line 1, in \n sampler = total_f.create_sampler(n=nevents)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 814, in create_sampler\n limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 835, in _create_sampler_tensor\n sample = self._single_hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 877, in _single_hook_sample\n return self._hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basepdf.py\", line 489, in _hook_sample\n samples = super()._hook_sample(limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 880, in _hook_sample\n return self._norm_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 884, in _norm_sample\n return self._limits_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 887, in _limits_sample\n return self._call_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 901, in _call_sample\n return self._fallback_sample(n=n, limits=limits)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 934, in _fallback_sample\n sample_and_weights_factory=self._sample_and_weights)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 174, in accept_reject_sample\n back_prop=False)[1] # backprop not needed here\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3556, in while_loop\n return_same_structure)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3087, in BuildLoop\n pred, body, original_loop_vars, loop_vars, shape_invariants)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3022, in _BuildLoop\n body_result = body(*packed_vars_for_body)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 154, in sample_body\n take_or_not = probabilities > random_thresholds\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\gen_math_ops.py\", line 3922, in greater\n \"Greater\", x=x, y=y, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py\", line 788, in _apply_op_helper\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 507, in new_func\n return func(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 3300, in create_op\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 1801, in __init__\n self._traceback = tf_stack.extract_stack()\n\nResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_4/create_sampler/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n" + "name": "stdout", + "output_type": "stream", + "text": [ + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0 |\n", + "+-----------+--------+\n", + "+-----------+----------+\n", + "| Parameter | Gradient |\n", + "+===========+==========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+----------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+----------+\n", + "| sig_R | 0.000 |\n", + "+-----------+----------+\n", + "| cusp_m | 3550 |\n", + "+-----------+----------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+----------+\n", + "| sig_L | 200 |\n", + "+-----------+----------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+----------+\n", + "| cusp_s | 0 |\n", + "+-----------+----------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+----------+\n", + "| Parameter | Gradient |\n", + "+===========+==========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+----------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+----------+\n", + "| sig_R | 0.000 |\n", + "+-----------+----------+\n", + "| cusp_m | 3550 |\n", + "+-----------+----------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+----------+\n", + "| sig_L | 200 |\n", + "+-----------+----------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+----------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+----------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.499 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.501 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.490 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.510 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.021 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.019 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.030 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.010 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + 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Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | -0.010 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+----------+\n", + "| Parameter | Value |\n", + "+===========+==========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+----------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+----------+\n", + "| sig_R | 0.000 |\n", + "+-----------+----------+\n", + "| cusp_m | 3550.002 |\n", + "+-----------+----------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+----------+\n", + "| sig_L | 200 |\n", + "+-----------+----------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+----------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+----------+\n", + "+-----------+----------+\n", + "| Parameter | Value |\n", + "+===========+==========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+----------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+----------+\n", + "| sig_R | 0.000 |\n", + "+-----------+----------+\n", + "| cusp_m | 3549.998 |\n", + "+-----------+----------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+----------+\n", + "| sig_L | 200 |\n", + "+-----------+----------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+----------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+----------+\n", + "+-----------+----------+\n", + "| Parameter | Value |\n", + "+===========+==========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+----------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+----------+\n", + "| sig_R | 0.000 |\n", + "+-----------+----------+\n", + "| cusp_m | 3550.022 |\n", + "+-----------+----------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+----------+\n", 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cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.004 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.002 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + 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psi2s_p | -1.500 |\n", + "+-----------+---------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+---------+\n", + "| sig_R | 0.000 |\n", + "+-----------+---------+\n", + "| cusp_m | 3550 |\n", + "+-----------+---------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+---------+\n", + "| sig_L | 200.001 |\n", + "+-----------+---------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+---------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+---------+\n", + "+-----------+---------+\n", + "| Parameter | Value |\n", + "+===========+=========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+---------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+---------+\n", + "| sig_R | 0.000 |\n", + "+-----------+---------+\n", + "| cusp_m | 3550 |\n", + "+-----------+---------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+---------+\n", + "| sig_L | 199.999 |\n", + "+-----------+---------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+---------+\n", + "| cusp_s | 0.000 |\n", + 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psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.501 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.490 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + 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| -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.510 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+--------+\n", + "| sig_L | 200 |\n", + "+-----------+--------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+--------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+--------+\n", + "+-----------+--------+\n", + "| Parameter | Value |\n", + "+===========+========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+--------+\n", + "| jpsi_s | 0.030 |\n", + "+-----------+--------+\n", + "| sig_R | 0.000 |\n", + "+-----------+--------+\n", + "| cusp_m | 3550 |\n", + "+-----------+--------+\n", + "| psi2s_s | 0.003 |\n", + 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|\n", + "+-----------+------------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+------------+\n", + "+-----------+-------------+\n", + "| Parameter | Value |\n", + "+===========+=============+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+-------------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+-------------+\n", + "| sig_R | -100000.005 |\n", + "+-----------+-------------+\n", + "| cusp_m | 3550 |\n", + "+-----------+-------------+\n", + "| psi2s_s | 0.003 |\n", + "+-----------+-------------+\n", + "| sig_L | 200 |\n", + "+-----------+-------------+\n", + "| jpsi_p | -1.500 |\n", + "+-----------+-------------+\n", + "| cusp_s | 0.000 |\n", + "+-----------+-------------+\n", + "+-----------+----------+\n", + "| Parameter | Value |\n", + "+===========+==========+\n", + "| psi2s_p | -1.500 |\n", + "+-----------+----------+\n", + "| jpsi_s | 0.020 |\n", + "+-----------+----------+\n", + "| sig_R | 0.000 |\n", + "+-----------+----------+\n", + "| cusp_m | 3550.022 |\n", + 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FCN = 3629121.653405886TOTAL NCALL = 71NCALLS = 71
EDM = 1.716336526500257e-07GOAL EDM = 5e-06\n", + " UP = 0.5
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ValidValid ParamAccurate CovarPosDefMade PosDef
FalseTrueFalseFalseFalse
Hesse FailHasCovAbove EDMReach calllim
TrueTrueFalseFalse
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+NameValueHesse ErrorMinos Error-Minos Error+Limit-Limit+Fixed?
0psi2s_p-1.500030No
1jpsi_s0.02018150No
2sig_R3e-070No
3cusp_m35500No
4psi2s_s0.002597960No
5sig_L2000No
6jpsi_p-1.499970No
7cusp_s7.51955e-100No
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" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -567,7 +2219,7 @@ "# param.set_value(random value here)\n", "\n", "# Minimise the NLL\n", - "minimizer = zfit.minimize.MinuitMinimizer()\n", + "minimizer = zfit.minimize.MinuitMinimizer(verbosity = 10)\n", "minimum = minimizer.minimize(nll)" ] }, @@ -580,14 +2232,234 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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FCN = 2069227.784921124TOTAL NCALL = 1700NCALLS = 1689
EDM = 0.29410277187207523GOAL EDM = 5e-06\n", + " UP = 0.5
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ValidValid ParamAccurate CovarPosDefMade PosDef
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Hesse FailHasCovAbove EDMReach calllim
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+NameValueHesse ErrorMinos Error-Minos Error+Limit-Limit+Fixed?
0psi2s_p-50.26584.8059e+07No
1jpsi_s559850162.861No
2sig_R4888044.8059e+07No
3cusp_m-3965604.8059e+07No
4psi2s_s98059.84.73152e+07No
5sig_L0.7362434.8059e+07No
6jpsi_p-232.4784.8059e+07No
7cusp_s13254.84.80455e+07No
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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "ename": "RuntimeError", + "evalue": "Function mimimum is not valid. Make sure migrad converge first", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mRuntimeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mminimizer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mminimize\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnll\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0mparam_errors\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0merror\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 8\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mvar\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mparam_errors\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\minimizers\\fitresult.py\u001b[0m in \u001b[0;36merror\u001b[1;34m(self, params, method, error_name, sigma)\u001b[0m\n\u001b[0;32m 227\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 228\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0muncached_params\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 229\u001b[1;33m \u001b[0merror_dict\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_error\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0muncached_params\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msigma\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msigma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 230\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_cache_errors\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merror_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0merror_name\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0merror_dict\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 231\u001b[0m \u001b[0mall_errors\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mOrderedDict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0merror_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\minimizers\\fitresult.py\u001b[0m in \u001b[0;36m_error\u001b[1;34m(self, params, method, sigma)\u001b[0m\n\u001b[0;32m 238\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 239\u001b[0m \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"The following method is not a valid, implemented method: {}\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 240\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mmethod\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msigma\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msigma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 241\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 242\u001b[0m \u001b[1;31m# def set_error_method(self, method):\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\minimizers\\fitresult.py\u001b[0m in \u001b[0;36m_minos_minuit\u001b[1;34m(result, params, sigma)\u001b[0m\n\u001b[0;32m 46\u001b[0m \"`MinuitMinimizer`.\")\n\u001b[0;32m 47\u001b[0m result = [minimizer._minuit_minimizer.minos(var=p.name, sigma=sigma)\n\u001b[1;32m---> 48\u001b[1;33m for p in params][-1] # returns every var\n\u001b[0m\u001b[0;32m 49\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mOrderedDict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 50\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\minimizers\\fitresult.py\u001b[0m in \u001b[0;36m\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m 46\u001b[0m \"`MinuitMinimizer`.\")\n\u001b[0;32m 47\u001b[0m result = [minimizer._minuit_minimizer.minos(var=p.name, sigma=sigma)\n\u001b[1;32m---> 48\u001b[1;33m for p in params][-1] # returns every var\n\u001b[0m\u001b[0;32m 49\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mOrderedDict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 50\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32miminuit\\_libiminuit.pyx\u001b[0m in \u001b[0;36miminuit._libiminuit.Minuit.minos\u001b[1;34m()\u001b[0m\n", + "\u001b[1;31mRuntimeError\u001b[0m: Function mimimum is not valid. Make sure migrad converge first" + ] + } + ], "source": [ "nll = zfit.loss.UnbinnedNLL(model=total_f, data=data, fit_range = (x_min, x_max))\n", "\n", "minimizer = zfit.minimize.MinuitMinimizer()\n", - "# minimizer._use_tfgrad = False\n", + "minimizer._use_tfgrad = False\n", "result = minimizer.minimize(nll)\n", "\n", "param_errors = result.error()\n", diff --git a/__pycache__/pdg_const.cpython-37.pyc b/__pycache__/pdg_const.cpython-37.pyc index e6658ee..28c51ae 100644 --- a/__pycache__/pdg_const.cpython-37.pyc +++ b/__pycache__/pdg_const.cpython-37.pyc Binary files differ diff --git a/raremodel-nb.ipynb b/raremodel-nb.ipynb index 522e520..bc43dea 100644 --- a/raremodel-nb.ipynb +++ b/raremodel-nb.ipynb @@ -267,6 +267,34 @@ ] }, { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def G(y):\n", + " \n", + " def inner_rect_bracket(q):\n", + " return tf.log(ztf.to_complex((1+tf.sqrt(q))/(1-tf.sqrt(q)))-tf.complex(ztf.constant(0), -1*ztf.constant(np.pi))) \n", + " \n", + " def inner_right(q):\n", + " return ztf.to_complex(2 * tf.atan(1/tf.sqrt(-q)))\n", + " \n", + " big_bracket = tf.where(y > ztf.const(0.0), inner_rect_bracket(y), inner_right(y))\n", + " \n", + " return ztf.to_complex(tf.sqrt(tf.abs(y))) * big_bracket\n", + "\n", + "def h_S(m, q):\n", + " \n", + " return tf.constant(2) - G(tf.constant(1) - 4*tf.pow(m, 2) / tf.pow(q, 2))\n", + "\n", + "def h_P(m,q):\n", + " \n", + " return 2/3 + (1 - (tf.constant(1) - 4*tf.pow(m, 2) / tf.pow(q, 2))) * h_S(m,q)\n", + "\n" + ] + }, + { "cell_type": "markdown", "metadata": {}, "source": [ @@ -275,7 +303,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -287,6 +315,8 @@ " ] # the name of the parameters\n", "\n", " def _unnormalized_pdf(self, x):\n", + " \n", + " x = x.unstack_x()\n", "\n", " def jpsi_res(q):\n", " return resonance(q, _mass = self.params['jpsi_mass'], scale = self.params['jpsi_scale'], phase = self.params['jpsi_phase'], width = self.params['jpsi_width'])\n", @@ -317,7 +347,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -345,7 +375,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -379,7 +409,7 @@ "\n", "#cusp\n", "\n", - "cusp_mass, sigma_R, sigma_L, cusp_scale = 3550, 3e-7, 200, 7\n", + "cusp_mass, sigma_R, sigma_L, cusp_scale = 3550, 3e-7, 200, 0\n", "\n", "cusp_m = zfit.Parameter(\"cusp_m\", ztf.constant(cusp_mass))\n", "sig_L = zfit.Parameter(\"sig_L\", ztf.constant(sigma_L))\n", @@ -396,7 +426,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -411,7 +441,7 @@ " def cusp(q):\n", " return bifur_gauss(q, cusp_m, sig_L, sig_R, cusp_s)\n", "\n", - " funcs = jpsi_res(xq) + psi2s_res(xq)# + cusp(xq)\n", + " funcs = jpsi_res(xq) + psi2s_res(xq) + cusp(xq)\n", "\n", " vec_f = vec(xq, funcs)\n", "\n", @@ -423,35 +453,23 @@ "\n", "calcs = zfit.run(total_test_tf(x_part))\n", "\n", - "test_q = np.linspace(x_min, x_max, 1000000)\n", + "test_q = np.linspace(x_min, x_max,20000000)\n", "\n", "calcs_test = zfit.run(total_test_tf(test_q))" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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pCawoqnK6FK9Rj12kjbaX13HR1Hnsqm7g+WsU6sFkUGYCa0sU7CIhZfOuWi6eOo+qvc288NOxjO6Z4nRJ4kWDMhLZWdVAeW2j06V4hYJd5CA2lFZz8dR51De7eenasQzvnux0SeJlAzMTAFgTJL12BbvID1ixo5KLpn6DBV6ePI4h3ZKcLkl8YGBGIgBriqsdrsQ7FOwi32PhlnImTfuGmIgwXr1uPP3TE5wuSXwkLSGK1PjIoOmxa1aMyAF8traU61/Ip1tyDC9cM5ZuyTFOlyQ+NjAjkTUl6rGLBKV3lhdz7XOL6J0az6vXjVeoh4iBGQmsLamm2eV2upTDpmAX2c+rC7dzy4zFDM9OZsbkcaTGRzldknSQgZmJNDS72bK7zulSDpuCXcTjqa82c/fry5nQN5XnrhlDUkyE0yVJBxqYETwzYxTsEvKstfx9zjoenL2KU3MzePLKPGIjdfkp1PTtGk9YJxMUM2P0v1dCmtttefCdVTz99RYuHJ3Nn84bSniY+juhKDoijJ5dYllfqmAXCVjNLje/nFXAzPxCrpqQw32nD6ZTJ+N0WeKgvmnxrC+tcbqMw6auiYSk+iYXN720mJn5hdx+Qj9+c4ZCXVqGY7burqOxObBnxijYJeRU7m3Z9eiDlTv57ZmDuf2E/hijUBfolx6Py23ZurvW6VIOi4JdQsrOqnounjqPJdv28I9JI7lqQi+nSxI/0jetZWbMhgAfjtEYu4SMTWU1XDF9AeW1jUz/yRH8qF+a0yWJn+nTNQ5QsIsEhGXbK7jqmYVAy2Jew7K1QqP8r9jIcLKSY9hQpmAX8Wtfri/juufzSYmL5Lmrx9A7Ld7pksSP9ekaH/A99oOOsRtjoo0xC4wxy4wxK40xD3REYSLe8NbSHVz9zEJ6pMQy64YjFepyUH3T4tlYVoPbbZ0u5ZC15eJpA3CctXY4MAI4xRgzzrdliRy+6V9t5raXlzKqR2devX48XROjnS5JAkDfrvHUN7nZUbHX6VIO2UGD3bZo/b0kwvMRuD/KJOhZa/nz+2v43exVnDIkg2evHkNitNZ9kbbpl97yW10gD8e0abqjMSbMGLMUKAXmWGvnH+A5k40xi4wxi8rKyrxdp0ibNDS7uP2Vpfz7s41cMrYHj106iuiIMKfLkgDSNy1Egt1a67LWjgCygTHGmNwDPGeatTbPWpuXlqZpZNLxKuuauHL6At5aWsRdJw/gD+fkEqa7SaWdOsdF0jk2gk27AvcmpXbNirHWVhhjPgNOAVb4pCKRQ1C4p46rnl7Ilt21PDpxBGePyHK6JAlgOalxbAngYG/LrJg0Y0yy53EMcAKwxteFibTVih2VnPv4XEqq6nnu6rEKdTlsvbrEsSWAlxVoy1BMJvCpMWY5sJCWMfbZvi1LpG0+XVvKRVPnERnWiddvOJLxfbo4XZIEgZzUOIor69nb6HK6lENy0KEYa+1yYGQH1CLSLi/N38Z9b61gYEYCT//kCE1nFK/JSW1ZWmBreS0DMxIdrqb9tAiYBBxrLX/5YA33vlHAj/ql8up1mqMu3tWrS0uwB+o4u5YUkIBS3+Til68v582lRUwa050Hz87VjkfidTmpsQABu7G1gl0Cxq6aBq57Pp/8rXu46+QB3HhMH62jLj6REB1BanykeuwivrRuZzVXP7OQXTUNPH7pKE4bmul0SRLkenaJY3OABrt+hxW/99naUs57fC6NzW5evW68Ql06RE4AT3lUsItfe+brzftWZ3zr5glaR106TK/UWHZWNVDX2Ox0Ke2moRjxS80uNw/8ZxXPf7OVEwen88jFI4iL0n9X6TitUx637KpjcLfAmvKod4r4ncq9Tdz80mK+XL+L637cm1+cPJBOWvNFOlhO65TH3bUKdpHDsW13HVc/u5Atu2p56PxhXHREd6dLkhDVy9NjD8QLqAp28RtzN+zixpcWA/D8NWO1PIA4Ki4qnNT4SAr3BN5cdgW7OM5ayzNzt/D7d1bTOzWOJ67I2ze+KeKk7M6xbCtXsIu0S32Ti1+/uYKZ+YWcNDidhy8eQbwukoqf6J4Sy7LtFU6X0W56B4ljdlbVc93z+SzdXsFtx/fjtuP76SKp+JXunWN4r6AYl9sG1KYtCnZxxOJte7j++XxqGpqZctkoTsnVTUfif3qkxNLsthRX7iW7c6zT5bSZblCSDvfqou1MnPoN0RFhzLrxSIW6+K3uKS1hvr18r8OVtI+CXTpMk8vN/W+v5O6ZyxnTK4W3b54QkGtdS+jo3rk12APrAqqGYqRDlFU3cMuMxXyzqZxrjurFPacO1HK74vcyk6PpZGB7gE15VLCLz+Vv3cONL+ZTUdfE3y4czvmjs50uSaRNIsI6kZkUox67SCtrLc/N28rv31lFZlIMs248giHdkpwuS6RdeqTEsn1PYI2xK9jFJ+oam7l3VgFvLi3i+IFdefiiESTFRjhdlki7dU+J4dO1ZU6X0S4KdvG6zbtqueGFfNburObOE/tz07F9NT9dAlb3zrGUVTdQ3+QiOiLM6XLaRMEuXvXhyhLufHUZYWGGZ64aw4/7pzldkshhaZ3yWLinjr5dExyupm0U7OIVLrflbx+u5fHPNjIsO4nHLx0VUDd0iHyf7ikxQMtcdgW7hIyy6gZuf2UJX2/YzaQx3fntmUMC5ldWkYPZd5NSAE15VLDLYZm7YRe3vbKU6vomrZ8uQSktPoroiE5s261glyDnclv++cl6Hv14Pb1T43jhmrEMyAiMX1NF2sMYQ7fkGIoqA2fKo4Jd2q20up7bX17K3I27OW9kFg+ek6v9SCWoZSXHsKOi3uky2uyg70ZjTHfgOSADcAPTrLWP+row8U9fb9jFbS8vpaahiYcuGMaFo7MxRlMZJbh1S4phTUmp02W0WVu6Wc3AndbaxcaYBCDfGDPHWrvKx7WJH3G5LY9+vJ5/frKePmnxvHTtWPqna+hFQkNW5xjKqhtoaHYRFe7/EwMOGuzW2mKg2PO42hizGsgCFOwhorSqntteXsq8Tbs5f1Q2D54zhNhIDb1I6OiW3DLlsaSynp5d/H/bxna9O40xOcBIYL4vihH/8+maUu6auYyahmb+csEwLszTrBcJPd2SowHYUbE3uILdGBMPvA7cbq2tOsD3JwOTAXr06OG1AsUZ9U0u/vz+Gp7+egsDMxJ46dpxGnqRkJXl6bEXBcgF1DYFuzEmgpZQf9FaO+tAz7HWTgOmAeTl5VmvVSgdbv3Oam6ZsYQ1JdX85MgcfnnqQN1wJCEtI6mlx15UERhTHtsyK8YATwGrrbUP+74kcYq1lhfmb+P3s1cRHxXO9J/kcdzAdKfLEnFcVHgYaQlR7AiQ5Xvb0mOfAFwOFBhjlnqO3Wutfdd3ZUlHK69t5O6Zy/lo9U6O7p/GXy8cRteEaKfLEvEbgXSTUltmxXwFaKJyEPt6wy5+9spSKuqauO+MwVx1ZI6W2RX5jqzkaNaUVDtdRptozloIa2x28/CcdUz9YiO9U+OY/pMjyM3SDkciB9ItKYZP1pRirfX7m/IU7CFqbUk1t7+ylNXFVVwytgf3nT6YmEhdIBX5Pt2SY6hvcrOnromUuEiny/lBCvYQ43JbnvpqE3/9YB2JMeE8cUUeJw7WBVKRg+m2b8rjXgW7+I/t5XXc+doyFmwu56TB6fzpvKF0iY9yuiyRgNA6l31HxV6/H7JUsIcAay2vLSrkgf+sxBjDXy4YxgVavEukXVrvPg2EuewK9iBXVt3APbMK+Gj1Tsb1TuGvFw7XlnUihyAlLpKo8E4KdnHWBytLuHdWAdUNzfz69EFcPaGXpjGKHCJjDFnJMQGxrICCPQhV1jXxwOyVzFq8gyHdEplx8Qit8yLiBd2SYyhUj1062kerdnLvGwXsrm3k5mP7cuvx/YgM7+R0WSJBITMpmvXry5wu46AU7EFiT20jD/xnJW8uLWJgRgJPXXkEQ7P9+8q9SKDJSIqmrLqBZpeb8DD/7TAp2IPABytL+NUbK6ioa+TW4/tx87F91UsX8YGMpGjcFspqGshMinG6nO+lYA9g5bWN/PbtlfxnWRGDMxN59uojGNJNvXQRX8n0LN9bXFmvYBfve7egmPveXEFVfRN3nNifG47pQ4Qf/2ooEgzSE1uCfWelf8+MUbAHmF01Dfz2rZW8U1BMblYiL144loEZiU6XJRISWnvpxQp28QZrLTPzC/nDu6upa3Bx18kDmHx0b/XSRTpQ59gIIsM7UVKlYJfDtGVXLfe+UcDcjbvJ69mZP503lH6aly7S4YwxZCRGU6IeuxyqJpebJ77cxKMfrScyrBN/ODeXSUf00N2jIg7KSFKwyyFasm0P98wqYE1JNafmZnD/WUP2XbgREedkJkWzeNsep8v4QQp2P1PT0MxfP1jLs/O2kJ4QzbTLR3PSkAynyxIRj4zEaHZWNvj1TkoKdj/y8eqd3PfmCoqr6rl8XE/uOnkACdERTpclIvvJSIqm0eWmvLbRb/czULD7gaKKvTw4exXvrSihf3o8My85ktE9OztdlogcwP43KSnY5X80udw8/fVmHvloPS635ecn9Wfy0X20HICIH9t3k1JVvd/upKRgd8iCzeX8+s0C1u2s4fiBXbn/rCF0T9EGGCL+LhBuUlKwd7BdNQ386d01vL64kKzkGG0mLRJg0hKiCOtk/HrKo4K9g7jclhkLtvHQ+2vY2+TixmP6cPNxfYmN1D+BSCAJ62RIi4/y67tPlSodoKCwkl+/WcCywkrG9+7Cg+cMoW9X3TkqEqj8/SYlBbsPldc28rcP1/LSgm10iYvi0YkjOGt4N7+d+yoibZOZFM26ndVOl/G9FOw+0Oxy8+L8bTw8Zx01Dc1cOT6HO07qT6LmpIsEhfTEaL5cv8vpMr7XQYPdGDMdOAMotdbm+r6kwDZ34y4eeHsVa3dWM6FvF35zxhAGZGjYRSSYZCZFU9PQTHV9k1/eRNiWHvszwL+A53xbSmDbXl7HH99dzXsrSsjuHMOUy0Zz8pB0DbuIBKEMz01KJZX1gRns1tovjDE5vi8lMO1tdPHvzzcy9fONdDKGO0/sz7VH9yY6Iszp0kTER1rnspdU1fvlEtpeG2M3xkwGJgP06NHDW6f1W9Za3iko5o/vrKaosp4zh3fjnlMH0i3Zf/dBFBHvyEj8dlkBf+S1YLfWTgOmAeTl5VlvndcfLS+s4PfvrGbB5nIGZybyyMSRjOmV4nRZItJBuia2rBHjr1MeNSumHXZU7OUv76/hzaVFpMZH8odzc5l4RA/CtPGFSEiJjgijS1xk8PfYg1l1fROPf7aRp77ajAFuOrYP1/+4j19eNBGRjpGRFM1OP737tC3THWcAxwCpxphC4LfW2qd8XZg/aHa5mbFwO4/MWcfu2kbOHZnFz08eQJbG0UVCXmZSNDsqAjTYrbWTOqIQf2Kt5ZM1pfzx3dVsLKtlTK8Unj59EMOyk50uTUT8REZSNIu2+ucWeRqK+Y4VOyr547urmbtxN71S45h6+WhOGqz56CLy3zKTYqioa2Jvo4uYSP+a3qxg99hQWsPf56zjnYJikmMj+O2Zg7l0bE9teiEiB9Q65bGkqp5eqXEOV/PfQj7YC/fU8Y+P1zMzv5DoiDBuPa4vPz26t9Z1EZEf9O0WeXsV7P6irLqBxz7dwEvzt4GBqyb04oZj+pDqp3sYioh/yfRMovDHuewhF+yVe5uY9sVGpn+1hUaXmwtHZ3Pr8f10x6iItIs/330aMsFe19jMM3O3MOWzjVTVN3PGsEzuOLE/vdPinS5NRAJQTGQYybERFFfudbqU/xH0wd7Y7GbGgm3885MN7Kpp4LiBXbnzpP4M6eafu4uLSODISPTPnZSCNthdbssbS3bwyEfrKNyzlzG9Uphy2SjycrSmi4h4R2ZStIZiOoK1lvdXlPC3OevYUFpDblYifzh3KEf3S9VcdBHxqszkGJYXVjpdxv8ImmC31vLl+l385YO1FOyopE9aHP++dBSn5GYo0EXEJzITo9ld20h9k8uv9mAIimBfvG0Pf35vDfM3l5OVHMNfLhjGuSOzCA/TzUUi4jutOyntrKqnZxf/mcse0MG+obSah95fy4erdpIaH8n9Zw5m0tgeRIX7z09IP/M7AAAHxklEQVROEQlerTspFVcq2A9bSWU9D89Zy8z8QmIjw7njxP5cc1Qv4qIC8uWISIDaf+9TfxJQSdjY7Obprzfz6MfraXZZrprQi5uO7UtKXKTTpYlICPp2WQEF+yFZXljBHa8uY0NpDScM6spvzhhCjy6xTpclIiEsLiqcxOhwSvzsJiW/D3ZrLVM+38TfPlxLWkIUT12Zx/GD0p0uS0QEaBlnL1KPve0am9388vXlzFqyg9OHZvLHc4eSFKtVF0XEf2Qk+d/dp34b7C635fZXlvBuQQl3ntifm4/rq/noIuJ3MpOiWVlU5XQZ/8Vvg/2vH67l3YISfn36IH76o95OlyMickCZSTHsqmmgsdntNxvz+EcV37FwSzlTPt/IpDHdFeoi4tcy97tJyV/4XbBba3lw9iq6JcXw69MHO12OiMgP2jeXXcH+/b5Yv4vlhZXcdnw/3XAkIn6vtcdeVOE/Ux79Lthn5hfSOTaCc0ZmOV2KiMhBZXVuWVZge3mdw5V8y6+Cvb7JxZxVJZwxrJvfXIQQEfkhsZHhpCdGsWW3gv2AlhdWUt/k5uj+aU6XIiLSZjld4ti6u9bpMvbxq2BftLUcgNE9OztciYhI2+V0iVOP/ftsKqslPTFKi3qJSEDpmRpLWXUDtQ3NTpcC+Fmwbyuvo0eKFvYSkcCS41mLfauf9NrbFOzGmFOMMWuNMRuMMb/0VTGlVfVkeBauFxEJFK3BvqGsxuFKWhw02I0xYcBjwKnAYGCSMcYndw7VNrqIi9TuRyISWPqlxxMd0Ykl2/Y4XQrQth77GGCDtXaTtbYReBk42xfF7G10EaNgF5EAExHWiWFZyczdsBtrrdPltCnYs4Dt+31d6Dn2X4wxk40xi4wxi8rKyg6pmBMGdWVoVtIh/VkRESdNHNOdcb1TaGh2O11Km1Z3PNBauf/zI8laOw2YBpCXl3dIP7IemTjyUP6YiIjjzhuVzXmjsp0uA2hbj70Q6L7f19lAkW/KERGRw9WWYF8I9DPG9DLGRAITgbd9W5aIiByqgw7FWGubjTE3Ax8AYcB0a+1Kn1cmIiKHpE3r4lpr3wXe9XEtIiLiBX5156mIiBw+BbuISJBRsIuIBBkFu4hIkDG+uP3VGFMG1AK7vH7ywJOK2qGV2uJbaosWaodvDbDWJnjjRD7ZLdpam2aMWWStzfPF+QOJ2uFbaotvqS1aqB2+ZYxZ5K1zaShGRCTIKNhFRIKML4N9mg/PHUjUDt9SW3xLbdFC7fAtr7WFTy6eioiIczQUIyISZBTsIiJBxuvB3lEbXzvJGDPdGFNqjFmx37EUY8wcY8x6z+fOnuPGGPMPT3ssN8aM2u/PXOl5/npjzJVOvJbDYYzpboz51Biz2hiz0hhzm+d4KLZFtDFmgTFmmactHvAc72WMme95Xa94lr7GGBPl+XqD5/s5+53rHs/xtcaYk515RYfHGBNmjFlijJnt+TpU22GLMabAGLO0dTpjh7w/rLVe+6BlWd+NQG8gElgGDPbm3+EPH8DRwChgxX7HHgJ+6Xn8S+DPnsenAe/RshPVOGC+53gKsMnzubPncWenX1s72yETGOV5nACso2XD81BsCwPEex5HAPM9r/FVYKLn+BTgBs/jG4EpnscTgVc8jwd73jdRQC/P+ynM6dd3CO1xB/ASMNvzdai2wxYg9TvHfP7+8PaLGA98sN/X9wD3ON24PvoHy/lOsK8FMj2PM4G1nsdTgUnffR4wCZi63/H/el4gfgBvASeGelsAscBiYCwtd1WGe47ve3/Qsr/BeM/jcM/zzHffM/s/L1A+aNll7WPgOGC253WFXDt46j5QsPv8/eHtoZg2bXwdpNKttcUAns9dPce/r02Cqq08v0KPpKWnGpJt4Rl+WAqUAnNo6WVWWGubPU/Z/3Xte82e71cCXQiOtngEuBto3dW5C6HZDtCyP/SHxph8Y8xkzzGfvz+8vaRAmza+DjHf1yZB01bGmHjgdeB2a22VMQd6aS1PPcCxoGkLa60LGGGMSQbeAAYd6Gmez0HZFsaYM4BSa22+MeaY1sMHeGpQt8N+Jlhri4wxXYE5xpg1P/Bcr7WFt3vsobzx9U5jTCaA53Op5/j3tUlQtJUxJoKWUH/RWjvLczgk26KVtbYC+IyWcdJkY0xrB2r/17XvNXu+nwSUE/htMQE4yxizBXiZluGYRwi9dgDAWlvk+VxKyw/7MXTA+8PbwR7KG1+/DbRerb6SlvHm1uNXeK54jwMqPb9+fQCcZIzp7LkqfpLnWMAwLV3zp4DV1tqH9/tWKLZFmqenjjEmBjgBWA18Clzgedp326K1jS4APrEtA6hvAxM9s0V6Af2ABR3zKg6ftfYea222tTaHlvf/J9baSwmxdgAwxsQZYxJaH9Py/3oFHfH+8MHFgtNomR2xEfiV0xcvfHRBZAZQDDTR8tP0GlrGBT8G1ns+p3iea4DHPO1RAOTtd56rgQ2ej6ucfl2H0A5H0fIr4XJgqefjtBBti2HAEk9brAB+4znem5ZA2gC8BkR5jkd7vt7g+X7v/c71K08brQVOdfq1HUabHMO3s2JCrh08r3mZ52Nlax52xPtDSwqIiAQZ3XkqIhJkFOwiIkFGwS4iEmQU7CIiQUbBLiISZBTsIiJBRsEuIhJk/h+viDsvJqipOwAAAABJRU5ErkJggg==\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# plt.plot(x_part, calcs, '.')\n", "plt.plot(test_q, calcs_test)\n", - "# plt.ylim(0, 0.0000007)\n", - "# plt.xlim(3000, 3750)\n", - "plt.savefig('test.png')" + "plt.ylim(3.5e-7, 5.5e-7)\n", + "plt.xlim(3050, 3150)\n", + "plt.savefig('test.png')\n", + "print(jpsi_width)" ] }, { @@ -463,7 +481,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -484,38 +502,37 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "ResourceExhaustedError", - "evalue": "OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_6/sample/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n\nCaused by op 'ZPDF_6/sample/while/Greater_1', defined at:\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 193, in _run_module_as_main\n \"__main__\", mod_spec)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 85, in _run_code\n exec(code, run_globals)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel_launcher.py\", line 16, in \n app.launch_new_instance()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\traitlets\\config\\application.py\", line 658, in launch_instance\n app.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 505, in start\n self.io_loop.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 148, in start\n self.asyncio_loop.run_forever()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 539, in run_forever\n self._run_once()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 1775, in _run_once\n handle._run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\events.py\", line 88, in _run\n self._context.run(self._callback, *self._args)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 690, in \n lambda f: self._run_callback(functools.partial(callback, future))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 743, in _run_callback\n ret = callback()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 781, in inner\n self.run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 742, in run\n yielded = self.gen.send(value)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 357, in process_one\n yield gen.maybe_future(dispatch(*args))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 267, in dispatch_shell\n yield gen.maybe_future(handler(stream, idents, msg))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in execute_request\n user_expressions, allow_stdin,\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 294, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 536, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2848, in run_cell\n raw_cell, store_history, silent, shell_futures)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2874, in _run_cell\n return runner(coro)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 67, in _pseudo_sync_runner\n coro.send(None)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3049, in run_cell_async\n interactivity=interactivity, compiler=compiler, result=result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3220, in run_ast_nodes\n if (yield from self.run_code(code, result)):\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3296, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)\n File \"\", line 3, in \n total_f.sample(n=nevents)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 871, in sample\n sample = self._single_hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 877, in _single_hook_sample\n return self._hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basepdf.py\", line 489, in _hook_sample\n samples = super()._hook_sample(limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 880, in _hook_sample\n return self._norm_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 884, in _norm_sample\n return self._limits_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 887, in _limits_sample\n return self._call_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 901, in _call_sample\n return self._fallback_sample(n=n, limits=limits)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 934, in _fallback_sample\n sample_and_weights_factory=self._sample_and_weights)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 174, in accept_reject_sample\n back_prop=False)[1] # backprop not needed here\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3556, in while_loop\n return_same_structure)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3087, in BuildLoop\n pred, body, original_loop_vars, loop_vars, shape_invariants)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3022, in _BuildLoop\n body_result = body(*packed_vars_for_body)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 154, in sample_body\n take_or_not = probabilities > random_thresholds\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\gen_math_ops.py\", line 3922, in greater\n \"Greater\", x=x, y=y, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py\", line 788, in _apply_op_helper\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 507, in new_func\n return func(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 3300, in create_op\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 1801, in __init__\n self._traceback = tf_stack.extract_stack()\n\nResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_6/sample/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mResourceExhaustedError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_call\u001b[1;34m(self, fn, *args)\u001b[0m\n\u001b[0;32m 1333\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1334\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1335\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mOpError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_run_fn\u001b[1;34m(feed_dict, fetch_list, target_list, options, run_metadata)\u001b[0m\n\u001b[0;32m 1318\u001b[0m return self._call_tf_sessionrun(\n\u001b[1;32m-> 1319\u001b[1;33m options, feed_dict, fetch_list, target_list, run_metadata)\n\u001b[0m\u001b[0;32m 1320\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_call_tf_sessionrun\u001b[1;34m(self, options, feed_dict, fetch_list, target_list, run_metadata)\u001b[0m\n\u001b[0;32m 1406\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_session\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfeed_dict\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfetch_list\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtarget_list\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1407\u001b[1;33m run_metadata)\n\u001b[0m\u001b[0;32m 1408\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m: OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[{{node ZPDF_6/sample/while/Greater_1}}]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mnevents\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1000\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mtotal_f\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnevents\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\u001b[0m in \u001b[0;36msample\u001b[1;34m(self, n, limits, name)\u001b[0m\n\u001b[0;32m 870\u001b[0m \u001b[0mlimits\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_check_input_limits\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlimits\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlimits\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcaller_name\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnone_is_error\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 871\u001b[0m \u001b[0msample\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_single_hook_sample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlimits\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlimits\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 872\u001b[1;33m \u001b[0msample_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSampleData\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfrom_sample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mspace\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 873\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 874\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0msample_data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\data.py\u001b[0m in \u001b[0;36mfrom_sample\u001b[1;34m(cls, sample, obs, name, weights)\u001b[0m\n\u001b[0;32m 528\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mfrom_sample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msample\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mtf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTensor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mobs\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mztyping\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mObsTypeInput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mweights\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 529\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mzfit\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 530\u001b[1;33m \u001b[0msample\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mzfit\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msample\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 531\u001b[0m sample_holder = tf.Variable(initial_value=sample, trainable=False, collections=(\"zfit_sample_cache\",),\n\u001b[0;32m 532\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"sample_data_holder_{}\"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_cache_counting\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\util\\execution.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 75\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 76\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 77\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msess\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 78\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 79\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mcreate_session\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36mrun\u001b[1;34m(self, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 927\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 928\u001b[0m result = self._run(None, fetches, feed_dict, options_ptr,\n\u001b[1;32m--> 929\u001b[1;33m run_metadata_ptr)\n\u001b[0m\u001b[0;32m 930\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mrun_metadata\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 931\u001b[0m \u001b[0mproto_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtf_session\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTF_GetBuffer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrun_metadata_ptr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_run\u001b[1;34m(self, handle, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 1150\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mfinal_fetches\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mfinal_targets\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mfeed_dict_tensor\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1151\u001b[0m results = self._do_run(handle, final_targets, final_fetches,\n\u001b[1;32m-> 1152\u001b[1;33m feed_dict_tensor, options, run_metadata)\n\u001b[0m\u001b[0;32m 1153\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1154\u001b[0m \u001b[0mresults\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_run\u001b[1;34m(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 1326\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mhandle\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1327\u001b[0m return self._do_call(_run_fn, feeds, fetches, targets, options,\n\u001b[1;32m-> 1328\u001b[1;33m run_metadata)\n\u001b[0m\u001b[0;32m 1329\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1330\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_do_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_prun_fn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhandle\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfeeds\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfetches\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_call\u001b[1;34m(self, fn, *args)\u001b[0m\n\u001b[0;32m 1346\u001b[0m \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1347\u001b[0m \u001b[0mmessage\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0merror_interpolation\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minterpolate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_graph\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1348\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnode_def\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmessage\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1349\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1350\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_extend_graph\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m: OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_6/sample/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n\nCaused by op 'ZPDF_6/sample/while/Greater_1', defined at:\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 193, in _run_module_as_main\n \"__main__\", mod_spec)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 85, in _run_code\n exec(code, run_globals)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel_launcher.py\", line 16, in \n app.launch_new_instance()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\traitlets\\config\\application.py\", line 658, in launch_instance\n app.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 505, in start\n self.io_loop.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 148, in start\n self.asyncio_loop.run_forever()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 539, in run_forever\n self._run_once()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 1775, in _run_once\n handle._run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\events.py\", line 88, in _run\n self._context.run(self._callback, *self._args)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 690, in \n lambda f: self._run_callback(functools.partial(callback, future))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 743, in _run_callback\n ret = callback()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 781, in inner\n self.run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 742, in run\n yielded = self.gen.send(value)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 357, in process_one\n yield gen.maybe_future(dispatch(*args))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 267, in dispatch_shell\n yield gen.maybe_future(handler(stream, idents, msg))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in execute_request\n user_expressions, allow_stdin,\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 294, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 536, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2848, in run_cell\n raw_cell, store_history, silent, shell_futures)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2874, in _run_cell\n return runner(coro)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 67, in _pseudo_sync_runner\n coro.send(None)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3049, in run_cell_async\n interactivity=interactivity, compiler=compiler, result=result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3220, in run_ast_nodes\n if (yield from self.run_code(code, result)):\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3296, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)\n File \"\", line 3, in \n total_f.sample(n=nevents)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 871, in sample\n sample = self._single_hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 877, in _single_hook_sample\n return self._hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basepdf.py\", line 489, in _hook_sample\n samples = super()._hook_sample(limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 880, in _hook_sample\n return self._norm_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 884, in _norm_sample\n return self._limits_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 887, in _limits_sample\n return self._call_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 901, in _call_sample\n return self._fallback_sample(n=n, limits=limits)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 934, in _fallback_sample\n sample_and_weights_factory=self._sample_and_weights)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 174, in accept_reject_sample\n back_prop=False)[1] # backprop not needed here\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3556, in while_loop\n return_same_structure)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3087, in BuildLoop\n pred, body, original_loop_vars, loop_vars, shape_invariants)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3022, in _BuildLoop\n body_result = body(*packed_vars_for_body)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 154, in sample_body\n take_or_not = probabilities > random_thresholds\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\gen_math_ops.py\", line 3922, in greater\n \"Greater\", x=x, y=y, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py\", line 788, in _apply_op_helper\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 507, in new_func\n return func(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 3300, in create_op\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 1801, in __init__\n self._traceback = tf_stack.extract_stack()\n\nResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_6/sample/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n" - ] - } - ], + "outputs": [], "source": [ - "nevents = 1000\n", + "nevents = 440000\n", "\n", - "total_f.sample(n=nevents)" + "samp = total_f.sample(n=nevents)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sam = samp.unstack_x()\n", + "\n", + "sam = zfit.run(sam)\n", + "\n", + "bins = int((x_max-x_min)/7)\n", + "\n", + "calcs = zfit.run(total_test_tf(samp))\n", + "\n", + "plt.hist(sam, bins = bins, range = (x_min,x_max))\n", + "\n", + "# plt.plot(sam, calcs, '.')\n", + "# plt.plot(test_q, calcs_test)\n", + "# plt.ylim(0, 0.0000007)\n", + "# plt.xlim(3000, 3750)\n", + "\n", + "plt.savefig('test.png')" ] }, { @@ -527,32 +544,9 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "ResourceExhaustedError", - "evalue": "OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_7/create_sampler/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n\nCaused by op 'ZPDF_7/create_sampler/while/Greater_1', defined at:\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 193, in _run_module_as_main\n \"__main__\", mod_spec)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 85, in _run_code\n exec(code, run_globals)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel_launcher.py\", line 16, in \n app.launch_new_instance()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\traitlets\\config\\application.py\", line 658, in launch_instance\n app.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 505, in start\n self.io_loop.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 148, in start\n self.asyncio_loop.run_forever()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 539, in run_forever\n self._run_once()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 1775, in _run_once\n handle._run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\events.py\", line 88, in _run\n self._context.run(self._callback, *self._args)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 690, in \n lambda f: self._run_callback(functools.partial(callback, future))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 743, in _run_callback\n ret = callback()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 781, in inner\n self.run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 742, in run\n yielded = self.gen.send(value)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 357, in process_one\n yield gen.maybe_future(dispatch(*args))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 267, in dispatch_shell\n yield gen.maybe_future(handler(stream, idents, msg))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in execute_request\n user_expressions, allow_stdin,\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 294, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 536, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2848, in run_cell\n raw_cell, store_history, silent, shell_futures)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2874, in _run_cell\n return runner(coro)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 67, in _pseudo_sync_runner\n coro.send(None)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3049, in run_cell_async\n interactivity=interactivity, compiler=compiler, result=result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3214, in run_ast_nodes\n if (yield from self.run_code(code, result)):\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3296, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)\n File \"\", line 1, in \n sampler = total_f.create_sampler(n=nevents)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 814, in create_sampler\n limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 835, in _create_sampler_tensor\n sample = self._single_hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 877, in _single_hook_sample\n return self._hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basepdf.py\", line 489, in _hook_sample\n samples = super()._hook_sample(limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 880, in _hook_sample\n return self._norm_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 884, in _norm_sample\n return self._limits_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 887, in _limits_sample\n return self._call_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 901, in _call_sample\n return self._fallback_sample(n=n, limits=limits)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 934, in _fallback_sample\n sample_and_weights_factory=self._sample_and_weights)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 174, in accept_reject_sample\n back_prop=False)[1] # backprop not needed here\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3556, in while_loop\n return_same_structure)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3087, in BuildLoop\n pred, body, original_loop_vars, loop_vars, shape_invariants)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3022, in _BuildLoop\n body_result = body(*packed_vars_for_body)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 154, in sample_body\n take_or_not = probabilities > random_thresholds\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\gen_math_ops.py\", line 3922, in greater\n \"Greater\", x=x, y=y, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py\", line 788, in _apply_op_helper\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 507, in new_func\n return func(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 3300, in create_op\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 1801, in __init__\n self._traceback = tf_stack.extract_stack()\n\nResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_7/create_sampler/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mResourceExhaustedError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_call\u001b[1;34m(self, fn, *args)\u001b[0m\n\u001b[0;32m 1333\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1334\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1335\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mOpError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_run_fn\u001b[1;34m(feed_dict, fetch_list, target_list, options, run_metadata)\u001b[0m\n\u001b[0;32m 1318\u001b[0m return self._call_tf_sessionrun(\n\u001b[1;32m-> 1319\u001b[1;33m options, feed_dict, fetch_list, target_list, run_metadata)\n\u001b[0m\u001b[0;32m 1320\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_call_tf_sessionrun\u001b[1;34m(self, options, feed_dict, fetch_list, target_list, run_metadata)\u001b[0m\n\u001b[0;32m 1406\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_session\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfeed_dict\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfetch_list\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtarget_list\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1407\u001b[1;33m run_metadata)\n\u001b[0m\u001b[0;32m 1408\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m: OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[{{node ZPDF_7/create_sampler/while/Greater_1}}]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[1;31m# param.set_value(initial_value)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0msampler\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresample\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnevents\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 8\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[1;31m# Randomise initial values\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\data.py\u001b[0m in \u001b[0;36mresample\u001b[1;34m(self, param_values, n)\u001b[0m\n\u001b[0;32m 624\u001b[0m \u001b[1;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Cannot set a new `n` if not a Tensor-like object was given\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 625\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn_samples\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mload\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msession\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msess\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 626\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msess\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msample_holder\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minitializer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 627\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_initial_resampled\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 628\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36mrun\u001b[1;34m(self, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 927\u001b[0m \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 928\u001b[0m result = self._run(None, fetches, feed_dict, options_ptr,\n\u001b[1;32m--> 929\u001b[1;33m run_metadata_ptr)\n\u001b[0m\u001b[0;32m 930\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mrun_metadata\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 931\u001b[0m \u001b[0mproto_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtf_session\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTF_GetBuffer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrun_metadata_ptr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_run\u001b[1;34m(self, handle, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 1150\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mfinal_fetches\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mfinal_targets\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mhandle\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mfeed_dict_tensor\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1151\u001b[0m results = self._do_run(handle, final_targets, final_fetches,\n\u001b[1;32m-> 1152\u001b[1;33m feed_dict_tensor, options, run_metadata)\n\u001b[0m\u001b[0;32m 1153\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1154\u001b[0m \u001b[0mresults\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_run\u001b[1;34m(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)\u001b[0m\n\u001b[0;32m 1326\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mhandle\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1327\u001b[0m return self._do_call(_run_fn, feeds, fetches, targets, options,\n\u001b[1;32m-> 1328\u001b[1;33m run_metadata)\n\u001b[0m\u001b[0;32m 1329\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1330\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_do_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_prun_fn\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhandle\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfeeds\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfetches\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\client\\session.py\u001b[0m in \u001b[0;36m_do_call\u001b[1;34m(self, fn, *args)\u001b[0m\n\u001b[0;32m 1346\u001b[0m \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1347\u001b[0m \u001b[0mmessage\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0merror_interpolation\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minterpolate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_graph\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1348\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnode_def\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmessage\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1349\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1350\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_extend_graph\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mResourceExhaustedError\u001b[0m: OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_7/create_sampler/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n\nCaused by op 'ZPDF_7/create_sampler/while/Greater_1', defined at:\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 193, in _run_module_as_main\n \"__main__\", mod_spec)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\runpy.py\", line 85, in _run_code\n exec(code, run_globals)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel_launcher.py\", line 16, in \n app.launch_new_instance()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\traitlets\\config\\application.py\", line 658, in launch_instance\n app.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 505, in start\n self.io_loop.start()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 148, in start\n self.asyncio_loop.run_forever()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 539, in run_forever\n self._run_once()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\base_events.py\", line 1775, in _run_once\n handle._run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\asyncio\\events.py\", line 88, in _run\n self._context.run(self._callback, *self._args)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 690, in \n lambda f: self._run_callback(functools.partial(callback, future))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\ioloop.py\", line 743, in _run_callback\n ret = callback()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 781, in inner\n self.run()\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 742, in run\n yielded = self.gen.send(value)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 357, in process_one\n yield gen.maybe_future(dispatch(*args))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 267, in dispatch_shell\n yield gen.maybe_future(handler(stream, idents, msg))\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in execute_request\n user_expressions, allow_stdin,\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tornado\\gen.py\", line 209, in wrapper\n yielded = next(result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 294, in do_execute\n res = shell.run_cell(code, store_history=store_history, silent=silent)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 536, in run_cell\n return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2848, in run_cell\n raw_cell, store_history, silent, shell_futures)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2874, in _run_cell\n return runner(coro)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 67, in _pseudo_sync_runner\n coro.send(None)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3049, in run_cell_async\n interactivity=interactivity, compiler=compiler, result=result)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3214, in run_ast_nodes\n if (yield from self.run_code(code, result)):\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3296, in run_code\n exec(code_obj, self.user_global_ns, self.user_ns)\n File \"\", line 1, in \n sampler = total_f.create_sampler(n=nevents)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 814, in create_sampler\n limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 835, in _create_sampler_tensor\n sample = self._single_hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 877, in _single_hook_sample\n return self._hook_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basepdf.py\", line 489, in _hook_sample\n samples = super()._hook_sample(limits=limits, n=n, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 880, in _hook_sample\n return self._norm_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 884, in _norm_sample\n return self._limits_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 887, in _limits_sample\n return self._call_sample(n=n, limits=limits, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 901, in _call_sample\n return self._fallback_sample(n=n, limits=limits)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\basemodel.py\", line 934, in _fallback_sample\n sample_and_weights_factory=self._sample_and_weights)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 174, in accept_reject_sample\n back_prop=False)[1] # backprop not needed here\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3556, in while_loop\n return_same_structure)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3087, in BuildLoop\n pred, body, original_loop_vars, loop_vars, shape_invariants)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 3022, in _BuildLoop\n body_result = body(*packed_vars_for_body)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py\", line 154, in sample_body\n take_or_not = probabilities > random_thresholds\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\ops\\gen_math_ops.py\", line 3922, in greater\n \"Greater\", x=x, y=y, name=name)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py\", line 788, in _apply_op_helper\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 507, in new_func\n return func(*args, **kwargs)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 3300, in create_op\n op_def=op_def)\n File \"c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\tensorflow\\python\\framework\\ops.py\", line 1801, in __init__\n self._traceback = tf_stack.extract_stack()\n\nResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[500000,500000] and type bool on /job:localhost/replica:0/task:0/device:CPU:0 by allocator cpu\n\t [[node ZPDF_7/create_sampler/while/Greater_1 (defined at c:\\users\\sa_li\\.conda\\envs\\rmd\\lib\\site-packages\\zfit\\core\\sample.py:154) ]]\nHint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.\n\n" - ] - } - ], + "outputs": [], "source": [ "sampler = total_f.create_sampler(n=nevents)\n", "nll = zfit.loss.UnbinnedNLL(model=total_f, data=sampler, fit_range = (x_min, x_max))\n", @@ -567,7 +561,7 @@ "# param.set_value(random value here)\n", "\n", "# Minimise the NLL\n", - "minimizer = zfit.minimize.MinuitMinimizer()\n", + "minimizer = zfit.minimize.MinuitMinimizer(verbosity = 10)\n", "minimum = minimizer.minimize(nll)" ] }, diff --git a/test.png b/test.png index 6ad92c2..03d1d54 100644 --- a/test.png +++ b/test.png Binary files differ