{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Optimal Transport\n", "\n", "We develop a deep declarative node for solving and back-propagating through an [optimal transport (OT)](https://en.wikipedia.org/wiki/Transportation_theory_(mathematics)) problem. We make use of Sinkhorn normalization ([Cuturi, NeurIPS 2013](https://papers.nips.cc/paper/2013/hash/af21d0c97db2e27e13572cbf59eb343d-Abstract.html)) in the forward pass. For the backward pass we implement two methods, one based on unrolling the forward implementation and one based on implicit differentiation results from the [Deep Declarative Networks](https://doi.ieeecomputersociety.org/10.1109/TPAMI.2021.3059462) paper.\n", "\n", "Let us write the entropy regularized optimal transport problem in the following form,\n", "\n", "$$\n", "\\begin{array}{ll}\n", "\\text{minimize (over $P \\in \\mathbb{R}^{m \\times n}_{+}$)} & \\langle P, M\\rangle + \\frac{1}{\\gamma} \\text{KL}(P \\| rc^T) \\\\\n", "\\text{subject to} & P 1 = r \\\\ & P^T 1 = c \n", "\\end{array}\n", "$$\n", "\n", "where $r \\in \\mathbb{R}_{+}^m$ and $c \\in \\mathbb{R}_{+}^n$ with $r^T 1 = c^T 1 = 1$. Here $x = M \\in \\mathbb{R}^{m \\times n}$ is the input to the declarative node and $y = P \\in \\mathbb{R}^{m \\times n}_{+}$ is the output.\n", "The above problem leads to a solution of the form\n", "\n", "$$\n", "P_{ij} = \\alpha_i \\beta_j e^{-\\gamma M_{ij}}\n", "$$\n", "\n", "where $\\alpha \\in \\mathbb{R}^m$ and $\\beta \\in \\mathbb{R}^n$ are found by iteratively applying row and column normalizations.\n", "\n", "Variants of differentiable optimal transport have been used in several prior works, including:\n", "\n", "* [Santa Cruz et al.](https://ieeexplore.ieee.org/document/8481554), Permutation Learning, TPAMI 2018. ([code](https://github.com/rfsantacruz/deep-perm-net)).\n", "* [Campbell et al.](https://link.springer.com/chapter/10.1007/978-3-030-58536-5_15), Solving the Blind Perspective-n-Point Problem End-To-End with Robust Differentiable Geometric Optimization, ECCV 2020. ([code](https://github.com/dylan-campbell/bpnpnet)).\n", "* and many others." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Forward function\n", "\n", "The forward function performs Sinkhorn normalization until convergence (or a maximum number of iterations is reached)." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2021-05-01T05:25:14.975693Z", "start_time": "2021-05-01T05:25:14.126220Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.13.1\n", "GeForce RTX 2080 Ti\n", "tensor([[-1.0054, -0.3531, -1.1701, -4.6355, -0.4190],\n", " [-1.6365, -0.0507, -0.3729, -0.2017, -0.2777],\n", " [-0.2888, -0.3748, -1.3610, -2.6995, -0.0981]])\n", "tensor([[0.0353, 0.0458, 0.0483, 0.1550, 0.0490],\n", " [0.1329, 0.0678, 0.0436, 0.0037, 0.0853],\n", " [0.0318, 0.0864, 0.1081, 0.0413, 0.0657]])\n", "tensor([0.3333, 0.3333, 0.3333])\n", "tensor([0.2000, 0.2000, 0.2000, 0.2000, 0.2000])\n" ] } ], "source": [ "import torch\n", "print(torch.__version__)\n", "print(torch.cuda.get_device_name() if torch.cuda.is_available() else \"No CUDA\")\n", "torch.manual_seed(22)\n", "\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", "def sinkhorn(M, r=None, c=None, gamma=1.0, eps=1.0e-6, maxiters=10):\n", " '''Solve the entropy regularized optimal transport problem.'''\n", " \n", " m, n = M.shape\n", " if r is None: r = torch.ones((m, 1)) / m\n", " if c is None: c = torch.ones((n, 1)) / n\n", " assert r.shape == (m, 1) and c.shape == (n, 1)\n", " \n", " P = torch.exp(-1.0 * gamma * M)\n", " for i in range(maxiters):\n", " alpha = torch.sum(P, 1).reshape(m, 1)\n", " P = r / alpha * P\n", " \n", " beta = torch.sum(P, 0)\n", " if torch.all(torch.isclose(beta, c, atol=eps, rtol=0.0)):\n", " break\n", " P = P * c.T / beta.T\n", " \n", " return P\n", "\n", "#\n", "# --- testing ---\n", "#\n", "\n", "M = torch.log(torch.rand((3, 5), dtype=torch.float))\n", "P = sinkhorn(M)\n", "\n", "print(M)\n", "print(P)\n", "\n", "print(torch.sum(P, 1))\n", "print(torch.sum(P, 0))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Back Propagating by Unrolling Sinkhorn\n", "\n", "One way to back-propagate through optimal transport is by unrolling the Sinkhorn algorithm and applying the chain rule of differentiation to each iteration. Let's write out the calculations in the forward and backward pass:\n", "\n", "$$\n", "\\begin{array}{rl|rl}\n", "P_{ij}^{(0)} &= \\exp(-\\gamma M_{ij})\n", "&\n", "\\frac{\\partial P_{ij}^{(0)}}{\\partial M_{kl}} &= \\begin{cases}\n", " -\\gamma P_{ij}^{(0)} & \\text{if $ij = kl$} \\\\ 0 & \\text{otherwise}\n", "\\end{cases}\n", "\\\\\n", "\\alpha_i^{(t)} &= \\sum_{j=1}^{n} P_{ij}^{(t-1)}\n", "&\n", "\\frac{\\partial \\alpha_i^{(t)}}{\\partial P_{kl}^{(t-1)}} &= \\begin{cases}\n", " 1 & \\text{if $i = k$} \\\\ 0 & \\text{otherwise}\n", "\\end{cases}\n", "\\\\\n", "\\tilde{P}_{ij}^{(t)} &= \\frac{r_i}{\\alpha_i} P_{ij}^{(t-1)}\n", "&\n", "\\frac{\\partial \\tilde{P}_{ij}^{(t)}}{\\partial P_{kl}^{(t-1)}} &= \n", "\\frac{\\partial \\tilde{P}_{ij}^{(t)}}{\\partial P_{ij}^{(t-1)}} \\frac{\\partial P_{ij}^{(t-1)}}{\\partial P_{kl}^{(t-1)}} +\n", "\\frac{\\partial \\tilde{P}_{ij}^{(t)}}{\\partial \\alpha_i} \\frac{\\partial \\alpha_i^{(t)}}{\\partial P_{kl}^{(t-1)}}\n", "\\\\\n", "& & &=\n", "\\begin{cases} \\frac{r_i}{\\alpha_i^{(t)}} & \\text{if $ij = kl$} \\\\ 0 & \\text{otherwise} \\end{cases}\n", "- \\begin{cases} \\frac{r_i P_{ij}^{(t-1)}}{\\left(\\alpha_i^{(t)}\\right)^2} & \\text{if $i = k$} \\\\ 0 & \\text{otherwise} \\end{cases}\n", "\\\\\n", "\\beta_j^{(t)} &= \\sum_{i=1}^{m} \\tilde{P}_{ij}^{(t)}\n", "&\n", "\\frac{\\partial \\beta_j^{(t)}}{\\partial P_{kl}^{(t-1)}} &=\n", "\\sum_{i=1}^{m} \\frac{\\partial \\tilde{P}_{ij}^{(t)}}{\\partial P_{kl}^{(t-1)}}\n", "\\\\\n", "& & &=\n", "\\begin{cases} \\frac{r_k}{\\alpha_k^{(t)}} & \\text{if $j = l$} \\\\ 0 & \\text{otherwise} \\end{cases}\n", "- \\frac{r_k P_{kj}^{(t-1)}}{\\left(\\alpha_k^{(t)}\\right)^2}\n", "\\\\\n", "P_{ij}^{(t)} &= \\frac{c_j}{\\beta_j^{(t)}} \\tilde{P}_{ij}^{(t)}\n", "&\n", "\\frac{\\partial P_{ij}^{(t)}}{\\partial P_{kl}^{(t-1)}} &=\n", "\\frac{\\partial P_{ij}^{(t)}}{\\partial \\tilde{P}_{ij}^{(t)}} \\frac{\\partial \\tilde{P}_{ij}^{(t)}}{\\partial P_{kl}^{(t-1)}} +\n", "\\frac{\\partial P_{ij}^{(t)}}{\\partial \\beta_j} \\frac{\\partial \\beta_j^{(t)}}{\\partial P_{kl}^{(t-1)}}\n", "\\\\\n", "& & &=\n", "\\frac{c_j}{\\beta_j^{(t)}} \\frac{\\partial \\tilde{P}_{ij}^{(t)}}{\\partial P_{kl}^{(t-1)}}\n", "- \\frac{{P}_{ij}^{(t-1)}}{\\beta_j^{(t)}} \\frac{\\partial \\beta_j^{(t)}}{\\partial P_{kl}^{(t-1)}}\n", "\\end{array}\n", "$$\n", "\n", "Note that we need to store the $\\alpha_i^{(t)}$ and $\\beta_j^{(t)}$ in the forward pass. Then in the backward pass we can use the above equations and $\\tilde{P}_{ij}^{(t)} = \\frac{\\beta_j}{c_j} P_{ij}^{(t)}$ and $P_{ij}^{(t-1)} = \\frac{\\alpha_i}{r_i} \\tilde{P}_{ij}^{(t)}$ along with the incoming gradient $\\frac{\\partial J}{\\partial P_{ij}^{(T)}}$ to compute the necessary derivatives in the chain rule to eventually arrive at $\\frac{\\partial J}{\\partial M_{ij}}$.\n", "\n", "**This is essentially what `torch.autograd` will do when $P$ is caculated from the `sinkhorn` function above.**\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Gradients\n", "\n", "An alternative is to back propagate using the implicit function theorem applied to the optimality conditions. From Corollary 4.9 of [Deep Declarative Networks](https://doi.ieeecomputersociety.org/10.1109/TPAMI.2021.3059462) we have\n", "\n", "$$\n", "\\text{D} P(M) = (H^{-1} A^T (A H^{-1} A^T)^{-1} A H^{-1} - H^{-1})B\n", "$$\n", "\n", "Let $f(P) = \\sum_{ij} M_{ij} P_{ij} + \\frac{1}{\\gamma} \\sum_{ij} P_{ij} \\left(\\log P_{ij} - \\log r_i c_j\\right)$ be the entropy regularized optimal transport objective. We can compute the following derivatives,\n", "\n", "$$\n", "\\frac{\\partial f}{\\partial P_{ij}} = M_{ij} + \\frac{1}{\\gamma} \\log P_{ij} + \\frac{1}{\\gamma} - \\frac{1}{\\gamma} \\log r_i c_j\n", "\\\\\n", "H_{ij,kl} = \\frac{\\partial^2 f}{\\partial P_{ij} \\partial P_{kl}} = \\begin{cases}\n", " \\frac{1}{\\gamma P_{ij}} & \\text{if $ij = kl$} \\\\\n", " 0 & \\text{otherwise}\n", "\\end{cases}\n", "\\\\\n", "B_{ij,kl} = \\frac{\\partial^2 f}{\\partial P_{ij} \\partial M_{kl}} = \\begin{cases}\n", " 1 & \\text{if $ij = kl$} \\\\\n", " 0 & \\text{otherwise}\n", "\\end{cases}\n", "$$\n", "\n", "Therefore $H^{-1} = \\text{diag}(\\gamma P_{ij})$ and $B = I_{mn \\times mn}$. (Note that these are diagonal makes sense, since if not for the linear equality constraints each $P_{ij}$ would only depend on $M_{ij}$ and not any other $M_{kl}, kl \\neq ij$.)\n", "\n", "Now consider the constraints\n", "\n", "$$\n", "\\begin{array}{ll}\n", "\\sum_{j} P_{ij} = r_i & \\text{for } i = 1, \\ldots, m \\\\\n", "\\sum_{i} P_{ij} = c_j & \\text{for } j = 1, \\ldots, n\n", "\\end{array}\n", "$$\n", "\n", "Writing this as a matrix $A$ where $P_{ij}$ has been flattened rowwise, we have\n", "\n", "$$\n", "A = \\begin{bmatrix}\n", "1_n^T & 0_n^T & \\cdots & 0_n^T \\\\\n", "0_n^T & 1_n^T & \\cdots & 0_n^T \\\\\n", "\\vdots & \\vdots & \\ddots & \\vdots \\\\\n", "0_n^T & 0_n^T & \\cdots & 1_n^T \\\\\n", "I_{n \\times n} & I_{n \\times n} & \\cdots & I_{n \\times n}\n", "\\end{bmatrix} \\in \\mathbb{R}^{(m+n)\\times mn}\n", "$$\n", "\n", "Note, here that $A$ has rank $m + n - 1$ (by observing that the last row is the sum of the first $m$ rows minus the next $n - 1$ rows). To apply Corollary 4.9 we therefore must remove one row (i.e., one constraint). Redefining $A$ with the first row removed, we have\n", "\n", "$$\n", "A = \\begin{bmatrix}\n", "0_n^T & 1_n^T & \\cdots & 0_n^T \\\\\n", "\\vdots & \\vdots & \\ddots & \\vdots \\\\\n", "0_n^T & 0_n^T & \\cdots & 1_n^T \\\\\n", "I_{n \\times n} & I_{n \\times n} & \\cdots & I_{n \\times n}\n", "\\end{bmatrix} \\in \\mathbb{R}^{(m+n-1)\\times mn}\n", "$$\n", "\n", "Consider the $(p,q)$-th entry of $AH^{-1}A^T$ for $p, q \\in 1, \\ldots, m+n-1$,\n", "\n", "$$\n", "(A H^{-1} A^T)_{pq} = \\sum_{ij} \\frac{A_{p,ij} A_{q,ij}}{H_{ij,ij}}\n", "$$\n", "\n", "Therefore,\n", "\n", "$$\n", "\\begin{align*}\n", "AH^{-1}A^T\n", "&=\n", "\\begin{bmatrix}\n", "\\text{diag}(\\sum_{j=1}^{n} H_{pj,pj}^{-1} \\mid p = 2, \\ldots, m)\n", "& \n", "(H_{ij,ij}^{-1})_{i=2,\\ldots,m \\times j=1,\\ldots,n} \n", "\\\\\n", "(H_{ij,ij}^{-1})_{j=1,\\ldots,n \\times i=2,\\ldots,m} \n", "&\n", "\\text{diag}(\\sum_{i=1}^{m} H_{ip,ip}^{-1} \\mid p = 1, \\ldots, n)\n", "\\end{bmatrix}\n", "\\\\\n", "&=\n", "\\gamma \\begin{bmatrix}\n", "\\text{diag}{(r_{2:m})}\n", "&\n", "P_{2:m,1:n}\n", "\\\\\n", "P_{2:m,1:n}^T\n", "&\n", "\\text{diag}{(c)}\n", "\\end{bmatrix}\n", "\\end{align*}\n", "$$\n", "\n", "Now we can directly compute $(AH^{-1}A^T)^{-1}$ in $O((m+n-1)^3)$ time using Cholesky factorization or we can go even further and make use of more efficient [block matrix inversion](https://en.wikipedia.org/wiki/Block_matrix) results to compute in $O((m-1)^3)$ time,\n", "\n", "$$\n", "\\begin{bmatrix}\n", "\\Lambda_{11} & \\Lambda_{12} \\\\ \\Lambda_{21} & \\Lambda_{22}\n", "\\end{bmatrix}\n", "=\n", "\\begin{bmatrix}\n", "\\text{diag}{(r_{2:m})}\n", "&\n", "P_{2:m,1:n}\n", "\\\\\n", "P_{2:m,1:n}^T\n", "&\n", "\\text{diag}{(c)}\n", "\\end{bmatrix}^{-1}\n", "$$\n", "\n", "where\n", "\n", "$$\n", "\\begin{align*}\n", "\\Lambda_{11} &= (R - P_{2:m,1:n} C^{-1} P_{2:m,1:n}^T)^{-1} \\\\\n", "\\Lambda_{12} &= -\\Lambda_{11} P_{2:m,1:n} C^{-1} \\\\\n", "\\Lambda_{21} &= \\Lambda_{12}^T \\\\\n", "\\Lambda_{22} &= C^{-1} - C^{-1} P_{2:m,1:n}^T \\Lambda_{12}\n", "\\end{align*}\n", "$$\n", "\n", "with $C = \\text{diag}{(c)}$ and $R = \\text{diag}{(r_{2:m})}$.\n", "\n", "A similar derivation and corresponding algorithm for efficiently differentiating Sinkhorn was presented in [Luise et al., 2018](https://arxiv.org/abs/1805.11897).\n", "\n", "## Backward Pass Implementation\n", "\n", "We are now ready to compute the gradient of the loss function with respect to the input $\\text{D} J(M) \\in \\mathbb{R}^{m \\times n}$ given the gradient of the loss function with respect to the output $\\text{D} J(P) \\in \\mathbb{R}^{m \\times n}$ by multiplying from left-to-right, maintaining an $m$-by-$n$ matrix, and making the following observations,\n", "\n", "* the $(1,1)$-block of $(AH^{-1}A^T)^{-1}$ is symmetric positive definite (so use cholesky)\n", "* multiplication by $H^{-1}$ scales each entry by $\\gamma P_{ij}$\n", "* right-multiplication by $A^T$ concatenates summed rows and columns\n", "* right-multiplication by $A$ distributes corresponding entries across rows and columns\n", "* multiplication by $B$ does nothing\n", "\n", "We have coded an efficient implementation of this in the `OptimalTransportLayer` of the `ddn.pytorch.optimal_transport` module. The code also back propagates through $r$ and $c$ if provided (and with `requires_grad` set to `True`)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Example\n", "\n", "We demonstrate an example of back propagating through optimal transport by finding a matrix $M$ that will result in a given doubly stochastic matrix $P_{\\text{true}}$. We generate $P_{\\text{true}}$ by randomly sampling a matrix $M_{\\text{true}}$ and running it through the Sinkhorn algorithm. We then randomly sample a new matrix $M$ and iteratively updated it with gradient descent to minimize, $\\|\\text{OT}(M) - P_{\\text{true}}\\|^2$.\n", "\n", "Note that since optimal transport is a many-to-one mapping the $M$ found by our optimization will not necessarily be the same as $M_{\\text{true}}$. We plot the learning curve for different variants of back propagation.\n", "\n", "We evaluate two variants of the problem, one where the model class is calibrated with the problem and one where it is mis-calibrated. For the latter we generate $P_{\\text{true}}$ assuming non-uniform $r$ and $c$ but train assuming that they are uniform.\n", "\n", "Finally, we also measure running time on different size problems." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2021-05-01T05:25:44.290634Z", "start_time": "2021-05-01T05:25:14.977689Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "\n", "import torch\n", "import torch.optim as optim\n", "from torch.nn.functional import normalize\n", "\n", "torch.manual_seed(22)\n", "\n", "import sys\n", "sys.path.append(\"../\")\n", "\n", "from ddn.pytorch.optimal_transport import sinkhorn, OptimalTransportLayer\n", "\n", "import matplotlib.pyplot as plt\n", "\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "\n", "def learnM(fcn, M_init, P_true, iters=500):\n", " \"\"\"Find an M such that sinkhorn(M) matches P_true. Return M and the learning curve.\"\"\"\n", " M = M_init.clone()\n", " M.requires_grad = True\n", "\n", " optimizer = optim.AdamW([M], lr=1.0e-2)\n", "\n", " h = []\n", " for i in range(iters):\n", " optimizer.zero_grad(set_to_none=True)\n", " P = fcn(M)\n", " J = torch.linalg.norm(P - P_true)\n", " h.append(J.item())\n", " J.backward()\n", " optimizer.step()\n", "\n", " return M, h\n", "\n", "def plot_learning_curves(title, h1, h2, h3):\n", " \"\"\"Plots learning curves for autograd, approx and implicit.\"\"\"\n", "\n", " plt.figure()\n", " plt.semilogy(h1)\n", " plt.semilogy(h2)\n", " plt.semilogy(h3)\n", " plt.xlabel('iteration'); plt.ylabel('loss (log scale)')\n", " plt.legend(['autograd', 'approx', 'implicit'])\n", " plt.title(title)\n", "\n", "# test sinkhorn, approximate gradient and implicit gradient for calibrated model\n", "\n", "M_true = torch.randn((2, 100, 100), dtype=torch.float)\n", "P_true = sinkhorn(M_true)\n", "\n", "M_init = torch.log(torch.rand_like(M_true))\n", "\n", "M1, h1 = learnM(sinkhorn, M_init, P_true, iters=1000)\n", "M2, h2 = learnM(OptimalTransportLayer(method='approx'), M_init, P_true, iters=1000)\n", "M3, h3 = learnM(OptimalTransportLayer(), M_init, P_true, iters=1000)\n", "\n", "plot_learning_curves('Calibrated model', h1, h2, h3)\n", "\n", "# test sinkhorn, approximate gradient and implicit gradient for mis-calibrated model\n", "\n", "M_true = torch.randn((2, 100, 100), dtype=torch.float)\n", "P_true = sinkhorn(M_true, normalize(torch.rand(1, M_true.shape[1])), normalize(torch.rand(1, M_true.shape[2])))\n", "\n", "M_init = torch.log(torch.rand_like(M_true))\n", "\n", "M1, h1 = learnM(sinkhorn, M_init, P_true, iters=1000)\n", "M2, h2 = learnM(OptimalTransportLayer(method='approx'), M_init, P_true, iters=1000)\n", "M3, h3 = learnM(OptimalTransportLayer(), M_init, P_true, iters=1000)\n", "\n", "plot_learning_curves('Mis-calibrated model', h1, h2, h3)\n", "plt.show()\n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that the *autograd* and *implicit* curves coincide since they produce the same gradients (up to numerical precision)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2021-05-01T05:26:57.560135Z", "start_time": "2021-05-01T05:25:44.294624Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Running on cpu with batch size of 1...\n", "Timing on 5-by-5 problem...\n", "Timing on 10-by-10 problem...\n", "Timing on 25-by-25 problem...\n", "Timing on 50-by-50 problem...\n", "Timing on 100-by-100 problem...\n", "Timing on 200-by-200 problem...\n", "Timing on 300-by-300 problem...\n", "Timing on 500-by-500 problem...\n", "...done\n", "Running on cuda with batch size of 16...\n", "Timing on 5-by-5 problem...\n", "Timing on 10-by-10 problem...\n", "Timing on 25-by-25 problem...\n", "Timing on 50-by-50 problem...\n", "Timing on 100-by-100 problem...\n", "Timing on 200-by-200 problem...\n", "Timing on 300-by-300 problem...\n", "Timing on 500-by-500 problem...\n", "...done\n" ] }, { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# running time\n", "from timeit import timeit\n", "\n", "def wrapper(func, *args, **kwargs):\n", " def wrapped():\n", " return func(*args, **kwargs)\n", " return wrapped\n", "\n", "def plot_running_time(batch_size, device):\n", " \"\"\"Plot running time for given device.\"\"\"\n", " \n", " torch.manual_seed(22)\n", " print(\"Running on {} with batch size of {}...\".format(device, batch_size))\n", "\n", " n = [5, 10, 25, 50, 100, 200, 300, 500]\n", " t1, t2, t3, t4, t5 = [], [], [], [], []\n", " \n", " for ni in n:\n", " print(\"Timing on {}-by-{} problem...\".format(ni, ni))\n", " M_true = torch.randn((batch_size, ni, ni), dtype=torch.float)\n", " P_true = sinkhorn(M_true).to(device)\n", "\n", " M_init = torch.log(torch.rand_like(M_true)).to(device)\n", "\n", " t1.append(timeit(wrapper(learnM, sinkhorn, M_init, P_true), number=1))\n", " t2.append(timeit(wrapper(learnM, OptimalTransportLayer(method='approx'), M_init, P_true), number=1))\n", " t3.append(timeit(wrapper(learnM, OptimalTransportLayer(method='full'), M_init, P_true), number=1))\n", " t4.append(timeit(wrapper(learnM, OptimalTransportLayer(method='fullchol'), M_init, P_true), number=1))\n", " t5.append(timeit(wrapper(learnM, OptimalTransportLayer(), M_init, P_true), number=1))\n", "\n", " print(\"...done\")\n", "\n", " plt.figure()\n", " plt.plot(n, t1, '--', n, t2, ':', n, t3, '-.', n, t4, '-.', n, t5, '-')\n", " plt.xlabel('problem size'); plt.ylabel('running time')\n", " plt.legend(['autograd', 'approx', 'implicit (full inv)', 'implicit (full chol)', 'implicit (blk chol)'])\n", " plt.title('Running time on {} with batch size {}'.format(device, batch_size))\n", " #plt.savefig(\"op_runtime_{}.png\".format(device), dpi=300, bbox_inches='tight')\n", "\n", "\n", "plot_running_time(1, torch.device(\"cpu\"))\n", "if torch.cuda.is_available():\n", " plot_running_time(16, torch.device(\"cuda\"))\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that in addition to potential runtime advantages the implicit differentiation method (i.e., Deep Declarative Networks) also saves a significant amount of memory by not having to store intermediate Sinkhorn iterates. A GeForce RTX 2080 GPU (11GB) runs out of memory for problems above 500-by-500.\n", "\n", "The following plots show memory usage for a single backward pass as a function of:\n", " 1. number of sinkhorn iterations for a random problem of size 500-by-500, and\n", " 2. problem size for a fixed number (10) of sinkhorn iterations.\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2021-05-01T05:27:00.367548Z", "start_time": "2021-05-01T05:26:57.562120Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import torch.autograd.profiler as profiler\n", "\n", "M_init = torch.randn((1, 500, 500), dtype=torch.float)\n", "\n", "maxiters_range = list(range(1, 11))\n", "probsize_range = [5, 10, 25, 50, 100, 200, 500, 800, 1000]\n", "\n", "memory_by_maxiters = [[], []]\n", "memory_by_probsize = [[], []]\n", "\n", "for maxiters in maxiters_range:\n", " # profile autograd\n", " M = M_init.clone(); M.requires_grad = True\n", " with profiler.profile(profile_memory=True) as prof:\n", " P = sinkhorn(M, eps=0.0, maxiters=maxiters)\n", " torch.linalg.norm(P - torch.eye(M.shape[1])).backward()\n", " memory_by_maxiters[0].append(prof.total_average().cpu_memory_usage / (1024 * 1024)) \n", "\n", " # profile implicit\n", " M = M_init.clone(); M.requires_grad = True\n", " f = OptimalTransportLayer(eps=0.0, maxiters=maxiters)\n", " with profiler.profile(profile_memory=True) as prof:\n", " P = f(M)\n", " torch.linalg.norm(P - torch.eye(M.shape[1])).backward()\n", " memory_by_maxiters[1].append(prof.total_average().cpu_memory_usage / (1024 * 1024)) \n", "\n", "for n in probsize_range:\n", " M_init = torch.randn((1, n, n), dtype=torch.float)\n", "\n", " # profile autograd\n", " M = M_init.clone(); M.requires_grad = True\n", " with profiler.profile(profile_memory=True) as prof:\n", " P = sinkhorn(M, eps=0.0, maxiters=10)\n", " torch.linalg.norm(P - torch.eye(n)).backward()\n", " memory_by_probsize[0].append(prof.total_average().cpu_memory_usage / (1024 * 1024)) \n", "\n", " # profile implicit\n", " M = M_init.clone(); M.requires_grad = True\n", " f = OptimalTransportLayer(eps=0.0, maxiters=10)\n", " with profiler.profile(profile_memory=True) as prof:\n", " P = f(M)\n", " torch.linalg.norm(P - torch.eye(n)).backward()\n", " memory_by_probsize[1].append(prof.total_average().cpu_memory_usage / (1024 * 1024)) \n", " \n", "\n", "plt.figure()\n", "plt.plot(maxiters_range, memory_by_maxiters[0], '--')\n", "plt.plot(maxiters_range, memory_by_maxiters[1])\n", "plt.xlabel('num. iterations'); plt.ylabel('memory used (MB)')\n", "plt.legend(['autograd', 'implicit'])\n", "plt.title(\"Memory usage for problem of size 500-by-500\")\n", "#plt.savefig('op_memory_fixed_size.png', dpi=300, bbox_inches='tight')\n", "\n", "plt.figure()\n", "plt.plot(probsize_range, memory_by_probsize[0], '--')\n", "plt.plot(probsize_range, memory_by_probsize[1])\n", "plt.xlabel('problem size'); plt.ylabel('memory used (MB)')\n", "plt.legend(['autograd', 'implicit'])\n", "plt.title(\"Memory usage for 10 Sinkhorn iterations\")\n", "#plt.savefig('op_memory_fixed_sinkhorn.png', dpi=300, bbox_inches='tight')\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.16" } }, "nbformat": 4, "nbformat_minor": 4 }