diff --git a/CNMP.png b/CNMP.png new file mode 100644 index 0000000..c9a8c4e Binary files /dev/null and b/CNMP.png differ diff --git a/CNP.png b/CNP.png new file mode 100644 index 0000000..70f550c Binary files /dev/null and b/CNP.png differ diff --git a/Conditional Neural Movement Primitives.ipynb b/Conditional Neural Movement Primitives.ipynb new file mode 100644 index 0000000..e17898e --- /dev/null +++ b/Conditional Neural Movement Primitives.ipynb @@ -0,0 +1,738 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Using TensorFlow backend.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.\n", + "For more information, please see:\n", + " * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n", + " * https://github.com/tensorflow/addons\n", + "If you depend on functionality not listed there, please file an issue.\n", + "\n" + ] + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import os\n", + "os.environ[\"CUDA_DEVICE_ORDER\"] = \"PCI_BUS_ID\"\n", + "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\" # Delete above if you want to use GPU\n", + "import tensorflow as tf\n", + "import keras\n", + "from keras.layers import Softmax,Input,TimeDistributed,Dense,Average,GlobalAveragePooling1D,Concatenate,Lambda,RepeatVector\n", + "from keras.models import Model, load_model\n", + "from keras.optimizers import Adam\n", + "from keras.utils import plot_model\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import math\n", + "import time\n", + "import pylab as pl\n", + "from IPython import display\n", + "from IPython.core.display import HTML\n", + "from IPython.core.display import display as html_width\n", + "import tensorflow_probability as tfp\n", + "html_width(HTML(\"\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generating example demonstration:\n", + "These demonstrations are used in the first experiment of the Conditional Neural Movement Primitives (RSS 2019) by Yunus Seker, Mert Imre, Justus Piater and Emre Ugur\n", + "\n", + "This experiment does not involve external parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "training X (6, 200, 1)\n", + "training Y (6, 200, 1)\n", + "validation X (4, 200, 1)\n", + "validation Y (4, 200, 1)\n" + ] + } + ], + "source": [ + "def dist_generator(d, x, param, noise = 0):\n", + " f = (math.exp(-x**2/(2.*param[0]**2))/(math.sqrt(2*math.pi)*param[0]))+param[1]\n", + " return f+(noise*(np.random.rand()-0.5)/100.)\n", + "\n", + "def generate_demonstrations(time_len = 200, params = None, title = None):\n", + " fig = plt.figure(figsize=(5,5))\n", + " x = np.linspace(-0.5,0.5,time_len)\n", + " times = np.zeros((params.shape[0],time_len,1))\n", + " times[:] = x.reshape((1,time_len,1))+0.5\n", + " values = np.zeros((params.shape[0],time_len,1))\n", + " for d in range(params.shape[0]):\n", + " for i in range(time_len):\n", + " values[d,i] = dist_generator(d,x[i],params[d])\n", + " plt.plot(times[d], values[d])\n", + " plt.title(title+' Demonstrations')\n", + " plt.ylabel('Starting Position')\n", + " plt.show()\n", + " return times, values\n", + "\n", + "X, Y = generate_demonstrations(time_len=200, params=np.array([[0.6,-0.1],[0.5,-0.23],[0.4,-0.43],[-0.6,0.1],[-0.5,0.23],[-0.4,0.43]]), title='Training')\n", + "v_X, v_Y = generate_demonstrations(time_len=200, params=np.array([[0.55,-0.155],[0.45,-0.32],[-0.45,0.32],[-0.55,0.155]]), title='Validation')\n", + "print 'training X ', X.shape\n", + "print 'training Y ',Y.shape\n", + "print 'validation X ', v_X.shape\n", + "print 'validation Y ',v_Y.shape\n", + "np.save('training_X',X)\n", + "np.save('training_Y',Y)\n", + "np.save('validation_X',v_X)\n", + "np.save('validation_Y',v_Y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading model inputs\n", + "Input Requirements:\n", + "\n", + "* obs_max: Hyperparameter that decides to the maximum number of observations CNMP uses. In this experiment, it is set to 5\n", + "* d_N: Number of demonstrations\n", + "\n", + "* d_x: X vector feature dim (NOTE THAT: external parameters are assumed to be inside of the X vector, concatenated to time value. This experiment does not use external parameters so d_x = 1)\n", + "\n", + "* d_y: Y vector feature dim\n", + "\n", + "* time_len: length of the demonstrations, if all demonstrations does not have same length, use array and edit methods using time_len, or preprocess your data to interpolate into same time length (check numpy.interp)\n", + "\n", + "* X: shape=(d_N,time_len,d_x) --- time (and external parameter) values for each timestep for ith demonstration. d_x = 1+d_external_parameters\n", + "\n", + "* Y: shape=(d_N,time_len,d_y) --- corresponding values of f(X) for ith demonstration\n", + "\n", + "* obs_mlp_layers: Hidden neuron numbers of the dense layers inside of the Observation multi layer perceptron. Layer numbers can adapt to the list size. Last layer is always Linear, others are ReLU activated.\n", + "\n", + "* decoder_layers: Hidden neuron numbers of the dense layers inside of the Decoder multi layer perceptron. Layer numbers can adapt to the list size. Last layer size is always 2*d_y and activation is Linear, others are ReLU activated." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "d_N= 6\n", + "obs_max= 5\n", + "X (6, 200, 1) , Y (6, 200, 1)\n", + "d_x= 1\n", + "d_y= 1\n", + "time_len= 200\n" + ] + } + ], + "source": [ + "#Loading demonstrations and necessary variables\n", + "X, Y = (np.load('training_X.npy'), np.load('training_Y.npy'))\n", + "v_X, v_Y = (np.load('validation_X.npy'), np.load('validation_Y.npy'))\n", + "obs_max = 5 \n", + "d_N = X.shape[0] \n", + "d_x , d_y = (X.shape[-1] , Y.shape[-1])\n", + "time_len = X.shape[1] \n", + "obs_mlp_layers = [128,128,128]\n", + "decoder_layers = [128,128,d_y*2]\n", + "\n", + "print 'd_N=', d_N\n", + "print 'obs_max=', obs_max\n", + "print 'X',X.shape,', Y',Y.shape\n", + "print 'd_x=',d_x\n", + "print 'd_y=',d_y\n", + "print 'time_len=', time_len " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conditional Neural Movement Primitives" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### get_train_sample(): \n", + "* Selects a random observation number, n\n", + "* Selects a random demonstration id, d\n", + "* Permutes demonstration d, so the first n data can be observation. Selects (n+1)th data to be the target point\n", + "* Returns observations and target_X as inputs to the model to predict target_Y" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def get_train_sample():\n", + " n = np.random.randint(0,obs_max)+1\n", + " d = np.random.randint(0, d_N)\n", + " observation = np.zeros((1,n,d_x+d_y)) \n", + " target_X = np.zeros((1,1,d_x))\n", + " target_Y = np.zeros((1,1,d_y*2))\n", + " perm = np.random.permutation(time_len)\n", + " observation[0,:n,:d_x] = X[d,perm[:n]]\n", + " observation[0,:n,d_x:d_x+d_y] = Y[d,perm[:n]]\n", + " target_X[0,0] = X[d,perm[n]]\n", + " target_Y[0,0,:d_y] = Y[d,perm[n]]\n", + " return [observation,target_X], target_Y" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### predict_model(): \n", + "* Predicts whole trajectory according to the given observation batch\n", + "* observation: observation points as a batch. \n", + " * Dimension must be -> (1, obs_n, d_x+d_y) where obs_n is the number of observations for this prediction\n", + "* target_X: target X points as a batch. Model can predict one, multi, partial or whole trajectory/points as long as input is shaped as a batch\n", + " * Dimension must be -> (1, target_n, d_x) where target_n is the number of points to predict\n", + " * For whole trajectory give all X points through time length as a batch (for ex. the first demonstration = X[0].reshape=(1,time_len,d_x) \n", + "* prediction: Output that holds predicted means and standart deviations for each time point in the X. Later splitted into predicted_Y and predicted_std\n", + "* plot: if True, plots demonstrations and predicted distribution\n", + "* Returns predicted means and stds" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def predict_model(observation, target_X, plot = True):\n", + " predicted_Y = np.zeros((time_len,d_y))\n", + " predicted_std = np.zeros((time_len,d_y))\n", + " prediction = model.predict([observation,target_X])[0] \n", + " predicted_Y = prediction[:,:d_y]\n", + " predicted_std = np.log(1+np.exp(prediction[:,d_y:]))\n", + " if plot: # We highly recommend that you customize your own plot function, but you can use this function as default\n", + " for i in range(d_y): #for every feature in Y vector we are plotting training data and its prediction\n", + " fig = plt.figure(figsize=(5,5))\n", + " for j in range(d_N):\n", + " plt.plot(X[j,:,0],Y[j,:,i]) # assuming X[j,:,0] is time\n", + " plt.plot(X[j,:,0],predicted_Y[:,i],color='black')\n", + " plt.errorbar(X[j,:,0],predicted_Y[:,i],yerr=predicted_std[:,i],color = 'black',alpha=0.4)\n", + " plt.scatter(observation[0,:,0],observation[0,:,d_x+i],marker=\"X\",color='black')\n", + " plt.show() \n", + " return predicted_Y, predicted_std" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### custom_loss():\n", + "* Calculates log probability of the true value of the target point according to the multivariate Gaussian constructed by predicted means and stds\n", + "* Returns minus of that value" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def custom_loss(y_true, y_predicted):\n", + " mean, log_sigma = tf.split(y_predicted, 2, axis=-1)\n", + " y_true_value, temp =tf.split(y_true,2,axis=-1)\n", + " sigma = tf.nn.softplus(log_sigma)\n", + " dist = tfp.distributions.MultivariateNormalDiag(loc=mean, scale_diag=sigma)\n", + " loss = -tf.reduce_mean(dist.log_prob(y_true_value))\n", + " return loss" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### MLP():\n", + "\n", + "* Constructs a multilayer perceptron according to the given input dimension and layer sizes.\n", + "* input_dim: dimension of the input feature vector\n", + "* layers: Constructs a dense layer for each number in the list. Layer numbers are flexible to list size. Except for the last layer, all layers are ReLU activated.\n", + " * ex: (2,[128,128,128]) Constructs a multi layer perceptron with each dense layer's neuron sizes correspond to (2->128->128->128) from input to output\n", + " * ex: (4,[128,4]) Constructs a multi layer perceptron with each dense layer's neuron sizes correspond to (4->128->4) from input to output\n", + "* parallel_input:\n", + " * if False, MLP acts as classical fully connected MLP. Output is a single result.\n", + " * if True, MLP acts as a single parameter-sharing network. Every tuple in the input batch passes through MLP paralelly, independently from each other. Output is a batch which every row is the result of the corresponding tuple from the input batch passing through the parameter-sharing network.\n", + " * TLDR; use parallel input for encoding observations into representations, and fully connected MLP for every any other dense networks." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def MLP(input_dim, layers, name=\"mlp\", parallel_inputs=False):\n", + " input_layer = Input(shape=(None, input_dim),name=name+'_input')\n", + " for i in range(len(layers)-1):\n", + " hidden = TimeDistributed(Dense(layers[i], activation='relu'), name=name+'_'+str(i))(input_layer if i == 0 else hidden) if parallel_inputs else Dense(layers[i], activation='relu', name=name+'_'+str(i))(input_layer if i == 0 else hidden)\n", + " hidden = TimeDistributed(Dense(layers[-1]), name=name+'_output')(hidden) if parallel_inputs else Dense(layers[-1], name=name+'_output')(hidden)\n", + " return Model(input_layer, hidden, name=name)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## CNMP model:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "As proposed in the paper, the model is created. Layers can be tracked from figure below:\n", + "
\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "colab_type": "code", + "id": "xoe9zlfGwCts", + "outputId": "b21a1f80-9d22-422f-efaa-83dbf1a5cca3", + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n", + "Instructions for updating:\n", + "Colocations handled automatically by placer.\n", + "Model: \"model_1\"\n", + "__________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "==================================================================================================\n", + "observation (InputLayer) (None, None, 2) 0 \n", + "__________________________________________________________________________________________________\n", + "obs_mlp (Model) (None, None, 128) 33408 observation[0][0] \n", + "__________________________________________________________________________________________________\n", + "global_average_pooling1d_1 (Glo (None, 128) 0 obs_mlp[1][0] \n", + "__________________________________________________________________________________________________\n", + "target (InputLayer) (None, None, 1) 0 \n", + "__________________________________________________________________________________________________\n", + "Repeat (Lambda) (None, None, 128) 0 global_average_pooling1d_1[0][0] \n", + " target[0][0] \n", + "__________________________________________________________________________________________________\n", + "merged (Concatenate) (None, None, 129) 0 Repeat[0][0] \n", + " target[0][0] \n", + "__________________________________________________________________________________________________\n", + "decoder_mlp (Model) (None, None, 2) 33410 merged[0][0] \n", + "==================================================================================================\n", + "Total params: 66,818\n", + "Trainable params: 66,818\n", + "Non-trainable params: 0\n", + "__________________________________________________________________________________________________\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "observation_layer = Input(shape=(None,d_x+d_y), name=\"observation\") # (x_o,y_o) tuples\n", + "target_X_layer = Input(shape=(None,d_x), name=\"target\") # x_q\n", + "\n", + "ObsMLP = MLP(d_x+d_y, obs_mlp_layers, name='obs_mlp', parallel_inputs=True) # Network E\n", + "obs_representations = ObsMLP(observation_layer) # r_i\n", + "general_representation = GlobalAveragePooling1D()(obs_representations) # r\n", + "general_representation = Lambda(lambda x: tf.keras.backend.repeat(x[0],tf.shape(x[1])[1]), name='Repeat')([general_representation,target_X_layer]) # r in batch form (same)\n", + "\n", + "merged_layer = Concatenate(axis=2, name='merged')([general_representation,target_X_layer]) # (r,x_q) tuple\n", + "Decoder = MLP(d_x+obs_mlp_layers[-1], decoder_layers, name = 'decoder_mlp', parallel_inputs=False) # Network Q\n", + "output = Decoder(merged_layer) # (mean_q, std_q)\n", + "\n", + "model = Model([observation_layer, target_X_layer],output)\n", + "model.compile(optimizer = Adam(lr = 1e-4),loss=custom_loss)\n", + "model.summary()\n", + "\n", + "plot_model(model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### generator():\n", + "\n", + "* Generates data using get_train_sample function during training" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def generator():\n", + " while True:\n", + " inp,out = get_train_sample()\n", + " yield (inp, out)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### CNMP_Callback:\n", + "\n", + "* CNMP_Callback is a customizable class that manages the CNMP training process.\n", + "* on_train_begin(): Initializes the training process\n", + " * step: training step counter \n", + " * losses: holds the training losses for every loss_checkpoint \n", + " * smooth_losses: holds the means of losses[] for every plot_checkpoint \n", + " * loss_checkpoint: hyperparameter for loss recording\n", + " * plot_checkpoint: hyperparameter for loss smoothing and on-train example plotting\n", + " * validation_checkpoint: hyperparameter for validation checking to record best model\n", + "* on_batch_end(): \n", + " * End of every training iteration, step counter increases\n", + " * Customized checkpoints are handled if step counter gets to the corresponding checkpoint\n", + " \n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "class CNMP_Callback(keras.callbacks.Callback):\n", + " def on_train_begin(self, logs={}):\n", + " self.smooth_losses = [0]\n", + " self.losses = []\n", + " self.step = 0\n", + " self.loss_checkpoint = 1000\n", + " self.plot_checkpoint = 10000\n", + " self.validation_checkpoint = 100\n", + " self.validation_error = 9999999\n", + " return\n", + "\n", + " def on_batch_end(self, batch, logs={}):\n", + " if self.step % self.validation_checkpoint == 0:\n", + " ### Here, you should customize our own validation function according to your data and save your best model ###\n", + " current_error = 0\n", + " for i in range(v_X.shape[0]):\n", + " # predicting whole trajectory by using the first time step of the ith validation trajectory as given observation\n", + " predicted_Y,predicted_std = predict_model(np.concatenate((v_X[i,0],v_Y[i,0])).reshape(1,1,d_x+d_y), v_X[i].reshape(1,time_len,d_x), plot= False)\n", + " current_error += np.mean((predicted_Y - v_Y[i,:])**2) / v_X.shape[0]\n", + " if current_error < self.validation_error:\n", + " self.validation_error = current_error\n", + " model.save('cnmp_best_validation.h5')\n", + " print ' New validation best. Error is ', current_error\n", + " ### If you are not using validation, please note that every large-enough nn model will eventually overfit to the input data ###\n", + " \n", + " if self.step % self.loss_checkpoint == 0:\n", + " self.losses.append(logs.get('loss'))\n", + " self.smooth_losses[-1] += logs.get('loss')/(self.plot_checkpoint/self.loss_checkpoint)\n", + " \n", + " if self.step % self.plot_checkpoint == 0:\n", + " print self.step\n", + " #clearing output cell\n", + " display.clear_output(wait=True)\n", + " display.display(pl.gcf())\n", + " \n", + " #plotting training and smoothed losses\n", + " plt.figure(figsize=(15,5))\n", + " plt.subplot(121)\n", + " plt.title('Train Loss')\n", + " plt.plot(range(len(self.losses)),self.losses)\n", + " plt.subplot(122)\n", + " plt.title('Train Loss (Smoothed)')\n", + " plt.plot(range(len(self.smooth_losses)),self.smooth_losses)\n", + " plt.show()\n", + " \n", + " #plotting on-train examples by user given observations\n", + " for i in range(v_X.shape[0]):\n", + " #for each validation trajectory, predicting and plotting whole trajectories by using the first time steps as given observations. \n", + " predict_model(np.concatenate((v_X[i,0],v_Y[i,0])).reshape(1,1,d_x+d_y), v_X[i].reshape(1,time_len,d_x))\n", + " \n", + " if self.step!=0:\n", + " self.smooth_losses.append(0)\n", + " \n", + " self.step += 1\n", + " return" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Starting the training" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1000000/1000000 [==============================] - 1492s 1ms/step - loss: -3.2519\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "max_training_step = 1000000\n", + "model.fit_generator(generator(), steps_per_epoch=max_training_step, epochs=1, verbose=1, callbacks=[CNMP_Callback()])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Loading the Best Model " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "import keras.losses\n", + "keras.losses.custom_loss = custom_loss\n", + "model = load_model('cnmp_best_validation.h5', custom_objects={ 'tf':tf })" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Testing the Model" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "predicted_Y,predicted_std = predict_model(np.concatenate(([[0.8]],[[-0.38]]), axis=1).reshape(1,-1,d_x+d_y), X[0].reshape(1,time_len,d_x))\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "name": "ANP.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.15+" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/Learning of 2D obstacle avoidance skill shown in categor-ically different ways/Learning of 2D obstacle avoidance skill shown in categorically different ways.ipynb b/Example Experiments/Learning 2D Obstacle Avoidance/Learning of 2D obstacle avoidance skill shown in categorically different ways.ipynb similarity index 100% rename from Learning of 2D obstacle avoidance skill shown in categor-ically different ways/Learning of 2D obstacle avoidance skill shown in categorically different ways.ipynb rename to Example Experiments/Learning 2D Obstacle Avoidance/Learning of 2D obstacle avoidance skill shown in categorically different ways.ipynb diff --git a/Learning of 2D obstacle avoidance skill shown in categor-ically different ways/demonstrations/egg_demonstrations.npy b/Example Experiments/Learning 2D Obstacle Avoidance/demonstrations/egg_demonstrations.npy similarity index 100% rename from Learning of 2D obstacle avoidance skill shown in categor-ically different ways/demonstrations/egg_demonstrations.npy rename to Example Experiments/Learning 2D Obstacle Avoidance/demonstrations/egg_demonstrations.npy diff --git a/Learning of 2D obstacle avoidance skill shown in categor-ically different ways/demonstrations/egg_times.npy b/Example Experiments/Learning 2D Obstacle Avoidance/demonstrations/egg_times.npy similarity index 100% rename from Learning of 2D obstacle avoidance skill shown in categor-ically different ways/demonstrations/egg_times.npy rename to Example Experiments/Learning 2D Obstacle Avoidance/demonstrations/egg_times.npy diff --git a/Learning of 2D obstacle avoidance skill shown in categor-ically different ways/promp.py b/Example Experiments/Learning 2D Obstacle Avoidance/promp.py similarity index 100% rename from Learning of 2D obstacle avoidance skill shown in categor-ically different ways/promp.py rename to Example Experiments/Learning 2D Obstacle Avoidance/promp.py diff --git a/Online Sensor Conditioning and MovementPrimitive Classification/Demonstrations/endpoints.npy b/Example Experiments/Online Sensor Conditioning and Movement Primitive Classification/Demonstrations/endpoints.npy similarity index 100% rename from Online Sensor Conditioning and MovementPrimitive Classification/Demonstrations/endpoints.npy rename to Example Experiments/Online Sensor Conditioning and Movement Primitive Classification/Demonstrations/endpoints.npy diff --git a/Online Sensor Conditioning and MovementPrimitive Classification/Demonstrations/gripper_values.npy b/Example Experiments/Online Sensor Conditioning and Movement Primitive Classification/Demonstrations/gripper_values.npy similarity index 100% rename from Online Sensor Conditioning and MovementPrimitive Classification/Demonstrations/gripper_values.npy rename to Example Experiments/Online Sensor Conditioning and Movement Primitive Classification/Demonstrations/gripper_values.npy diff --git a/Online Sensor Conditioning and MovementPrimitive Classification/Demonstrations/sensor_values.npy b/Example Experiments/Online Sensor Conditioning and Movement Primitive Classification/Demonstrations/sensor_values.npy similarity index 100% rename from Online Sensor Conditioning and MovementPrimitive Classification/Demonstrations/sensor_values.npy rename to Example Experiments/Online Sensor Conditioning and Movement Primitive Classification/Demonstrations/sensor_values.npy diff --git a/Online Sensor Conditioning and MovementPrimitive Classification/Demonstrations/timestamps.npy b/Example Experiments/Online Sensor Conditioning and Movement Primitive Classification/Demonstrations/timestamps.npy similarity index 100% rename from Online Sensor Conditioning and MovementPrimitive Classification/Demonstrations/timestamps.npy rename to Example Experiments/Online Sensor Conditioning and Movement Primitive Classification/Demonstrations/timestamps.npy diff --git a/Summary.txt b/Example Experiments/Summary.txt similarity index 100% rename from Summary.txt rename to Example Experiments/Summary.txt diff --git a/Task Parameterization and Generalization/Task Parameterization and Generalization.ipynb b/Example Experiments/Task Parameterization and Generalization/Task Parameterization and Generalization.ipynb similarity index 100% rename from Task Parameterization and Generalization/Task Parameterization and Generalization.ipynb rename to Example Experiments/Task Parameterization and Generalization/Task Parameterization and Generalization.ipynb diff --git a/Task Parameterization and Generalization/demonstrations/joints.npy b/Example Experiments/Task Parameterization and Generalization/demonstrations/joints.npy similarity index 100% rename from Task Parameterization and Generalization/demonstrations/joints.npy rename to Example Experiments/Task Parameterization and Generalization/demonstrations/joints.npy diff --git a/Task Parameterization and Generalization/demonstrations/parameters.npy b/Example Experiments/Task Parameterization and Generalization/demonstrations/parameters.npy similarity index 100% rename from Task Parameterization and Generalization/demonstrations/parameters.npy rename to Example Experiments/Task Parameterization and Generalization/demonstrations/parameters.npy diff --git a/Task Parameterization and Generalization/demonstrations/sizes.npy b/Example Experiments/Task Parameterization and Generalization/demonstrations/sizes.npy similarity index 100% rename from Task Parameterization and Generalization/demonstrations/sizes.npy rename to Example Experiments/Task Parameterization and Generalization/demonstrations/sizes.npy diff --git a/Task Parameterization and Generalization/demonstrations/timestamps.npy b/Example Experiments/Task Parameterization and Generalization/demonstrations/timestamps.npy similarity index 100% rename from Task Parameterization and Generalization/demonstrations/timestamps.npy rename to Example Experiments/Task Parameterization and Generalization/demonstrations/timestamps.npy diff --git a/README.md b/README.md index a7dad25..6c58aee 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,16 @@ # Conditional Neural Movement Primitives -This repository includes the supplementary material for the paper: +![CNMP.png](CNMP.png) + +This repository includes the CNMP implementation and example material from the experiments of the paper: + +M. Yunus Seker, Mert Imre, Justus Piater, Emre Ugur, [Conditional Neural Movement Primitives](http://www.roboticsproceedings.org/rss15/p71.pdf), RSS 2019 + +\*\***NEW**\*\* + +CNMP is now available as a complete and ready-to-use notebook package with enhanced structure, including features like: one, multi points or whole trajectory batch prediction at once, and dynamic input size implementation with a re-designed model via Keras. + -M. Yunus Seker, Mert Imre, Justus Piater, Emre Ugur, Conditional Neural Movement Primitives, RSS 2019 ### Requirements: @@ -21,6 +29,8 @@ M. Yunus Seker, Mert Imre, Justus Piater, Emre Ugur, Conditional Neural Movement ### Contact Information: -* M. Yunus Seker , yunus.seker1@boun.edu.tr +* M. Yunus Seker , m.yunusseker@hotmail.com, yunus.seker1@boun.edu.tr * Mert Imre , mert.imre@boun.edu.tr + +* Emre Ugur, emre.ugur@boun.edur.tr diff --git a/cnmp_best_validation.h5 b/cnmp_best_validation.h5 new file mode 100644 index 0000000..07a15b8 Binary files /dev/null and b/cnmp_best_validation.h5 differ diff --git a/training_X.npy b/training_X.npy new file mode 100644 index 0000000..f9c33fe Binary files /dev/null and b/training_X.npy differ diff --git a/training_Y.npy b/training_Y.npy new file mode 100644 index 0000000..c1f6c83 Binary files /dev/null and b/training_Y.npy differ diff --git a/validation_X.npy b/validation_X.npy new file mode 100644 index 0000000..08e089e Binary files /dev/null and b/validation_X.npy differ diff --git a/validation_Y.npy b/validation_Y.npy new file mode 100644 index 0000000..f3dd9ce Binary files /dev/null and b/validation_Y.npy differ